Fuel Conservation StrategiesThrough Flight Operation Optimization at PGA

Simão Serôdio Trincheiras

Thesis to obtain the Master of Science Degree in

Aerospace Engineering

Supervisor(s): Prof. José Raúl Carreira AzinheiraEng. Miguel Vaz Pinto

Examination Committee

Chairperson: Prof. João Manuel Lage de Miranda LemosSupervisor: Prof. José Raúl Carreira Azinheira

Member of the Committee: Prof. Pedro da Graça Tavares Alvares Serrão

November 2016

ii

Acknowledgments

First and foremost, I would like to thank my family and my girlfriend for all their support, not only during

this final stage of my academic record, but throughout all the difficulties I faced along the way, and for

giving me the opportunity to pursue my dreams and be where I am today.

I would also like to thank all the professors I had during these years, for they have shaped me into

who I am today, either by helping me, challenging me or simply giving me an example to follow.

This work would not be possible without the cooperation of PGA, where I found exceptional workers

and brilliant minds.

From the people who worked closer to me and helped me progress in my work I would like to thank:

Francisco Freitas

Joao Guerreiro

Joao Morais Almeida

Jose Raul Carreira Azinheira

Luiz Placido Lapa

Miguel Vaz Pinto

Pedro Figueira

Finally, I would like to extend my gratitude to all my close friends who, directly or indirectly, made this

work possible - for helping me give my best, for supporting me through the hard times and cheering me

through the good ones. This work would not be possible without you.

To all of you,

Thank You

iii

iv

Resumo

A conservacao de combustıvel e um topico importante para as companhias aereas, nao so como forma

de reduzir os custos operacionais e de manutencao, como tambem de reduzir emissoes. Mesmo com

a actual expansao do mercado de transporte aereo e precos de combustıvel baixos, estima-se que um

plano de poupanca bem implementado ajude a atingir consumos de combustıvel 2% a 5% inferiores, o

que se traduz em margens de lucro superiores.

Para este trabalho a companhia aerea regional portuguesa PGA foi utilizada como objecto de estudo,

fornecendo dados da sua nova frota de nove Embraer 190. Um conjunto de cinco medidas operacionais

sugeridas pelo fabricante (como Single Engine Taxi e Idle Descent) foram estudadas e analisadas

utilizando gravacoes de dados de sessenta voos, ao longo de tres frequentes rotas com diferentes

distancias - cada uma com duas pernas (partida e chegada), para que a amostra fosse representativa.

O objectivo deste trabalho foi estudar e implementar este conjunto de medidas operacionais numa

ferramenta de software utilizando MATLAB que fosse capaz de analisar os voos e estimar o potencial

de poupanca se as medidas tivessem sido cumpridas.

Os resultados deste trabalho sao muito animadores, e ainda que seja improvavel alcancar o poten-

cial total de poupanca devido a natureza e imprevisibilidade do trafego aereo, permite a PGA prioritizar

determinadas medidas que oferecam um retorno maior com menor esforco. O impacto financeiro destas

poupancas tambem foi estimado, e pode chegar a cerca de 877ke (3.62% do consumo de combustıvel)

no caso especıfico da PGA.

Palavras-chave: Conservacao de Combustıvel, Companhia Aerea Regional, Medidas Op-

eracionais, Analise de Dados de Voo.

v

vi

Abstract

Fuel conservation is an important topic for airlines, not only as a way of reducing operating and main-

tenance costs, but also emissions. Even with the current expansion of the airline industry and low fuel

prices, it is estimated that a well implemented savings plan can help achieve 2% to 5% reduced fuel

consumptions, which translates into higher profit margins.

For this work, a Portuguese regional airline – PGA - was used as a case study, providing data on its

new fleet of nine Embraer 190. A set of five operating measures suggested by the manufacturer (like

Single Engine Taxi and Idle Descent) were studied and analyzed using data recordings from sixty flights,

over three frequent and different length city pairs, with two flight legs each (outbound and inbound), in

order for the sample to be representative. The goal of this work was to study and implement this set of

operational measures in a software tool using MATLAB that was able to analyze the flights and estimate

the potential savings if the measures had been fulfilled.

The results of this work are very encouraging, and even though its full saving potential is unlikely

to be achieved in a real-world scenario due to the nature and unpredictability of air traffic, it allows for

PGA to understand and prioritize certain measures that provide greater return with a lower effort. The

financial impact of these savings is also estimated, and can reach up to around 875ke (3.62% of the

fuel consumption) for PGA specific case.

Keywords: Fuel Conservation, Regional Airline, Operational Measures, Flight Data Analysis.

vii

viii

Contents

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Resumo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii

Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv

1 Introduction 1

1.1 PGA - Portugalia Airlines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.2.1 1% Fuel Conservation Estimations . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.3 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

1.4 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2 State of the Art & Analysis Tools 9

2.1 Market offer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.1.1 Honeywell - Aviaso . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.1.2 OpenAirlines - SkyBreathe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.1.3 Embraer fuel conservation strategies . . . . . . . . . . . . . . . . . . . . . . . . . . 12

2.2 Data capture and extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

2.2.1 Quick Access Recorder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

2.2.2 Analysis Ground Station . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

3 Methodology 15

3.1 Fuel Savings Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

3.1.1 Auxiliary Power Unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

3.1.2 Single Engine Taxi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

3.1.3 Thrust Reversal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

3.1.4 Idle Descent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

3.2 Route choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

ix

4 Results 23

4.1 Route Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

4.1.1 LIS-OPO & OPO-LIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

4.1.2 LIS-BCN & BCN-LIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

4.1.3 LIS-NCE & NCE-LIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

4.2 Total Sample Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

4.3 Savings Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

4.3.1 Additional Savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

5 Conclusions 43

5.1 Achievements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

5.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Bibliography 45

A Economic Scenario Data A.1

A.1 IATA - Economic Performance of the Airline Industry [3] . . . . . . . . . . . . . . . . . . . A.1

B Simulation Results B.1

C Technical Datasheets C.1

C.1 Embraer 190 Weights and Dimensions Datasheet [19] . . . . . . . . . . . . . . . . . . . . C.1

C.2 Embraer 190 Performance Datasheet [20] . . . . . . . . . . . . . . . . . . . . . . . . . . . C.5

x

List of Tables

1.1 Fuel expenses for the airline industry [3] - Appendix A. . . . . . . . . . . . . . . . . . . . . 3

1.2 Economic performance of the airline industry [3] - Appendix A. . . . . . . . . . . . . . . . 3

1.3 Typical Operational Profile for a 600 NM trip [4] . . . . . . . . . . . . . . . . . . . . . . . . 6

1.4 Embraer 1% Savings Estimation [4] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.1 OpenAirlines Awards [8] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

3.1 PGA Embraer E190 Lisbon outbound flights (as of 30th June 2016) . . . . . . . . . . . . . 21

4.1 LIS-OPO and OPO-LIS average phase time and fuel consumption . . . . . . . . . . . . . 25

4.2 LIS-OPO and OPO-LIS average savings estimates . . . . . . . . . . . . . . . . . . . . . . 26

4.3 LIS-BCN and BCN-LIS average phase time and fuel consumption . . . . . . . . . . . . . 30

4.4 LIS-BCN and BCN-LIS average savings estimates . . . . . . . . . . . . . . . . . . . . . . 31

4.5 LIS-NCE and NCE-LIS average phase time and fuel consumption . . . . . . . . . . . . . 34

4.6 LIS-NCE and NCE-LIS average savings estimates . . . . . . . . . . . . . . . . . . . . . . 35

4.7 Total average phase time and fuel consumption . . . . . . . . . . . . . . . . . . . . . . . . 36

4.8 Total average savings estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

4.9 Total average savings estimates aggregate . . . . . . . . . . . . . . . . . . . . . . . . . . 39

4.10 Final savings estimates results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

B.1 Savings, in kg, for all the files run through the simulation . . . . . . . . . . . . . . . . . . . B.2

xi

xii

List of Figures

1.1 Embraer E190 - CS-TPS [1] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Brent prices in Europe from 1988 to 2016 [2] . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.3 Economic performance of the airline industry [3] - Appendix A. . . . . . . . . . . . . . . . 4

1.4 Current price of aviation jet fuel (23 September 2016) [5] . . . . . . . . . . . . . . . . . . . 6

2.1 Aviaso method breakdown [6] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.2 Example of Aviaso dashboard [6] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.3 SkyBreathe method breakdown [8] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.4 Example of SkyBreathe dashboard [8] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.5 Simplified QAR architecture [11] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.6 AGS flight database with filters applied . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.7 AGS manual analysis feature for individual flight . . . . . . . . . . . . . . . . . . . . . . . 14

3.1 Embraer 190 APU system schematic [12] . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

3.2 Embraer 190 thrust reverser system schematic [12] . . . . . . . . . . . . . . . . . . . . . . 18

3.3 Idle Fuel Flow variation with Altitude . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

4.1 LIS-OPO route example (from file QAR1767) . . . . . . . . . . . . . . . . . . . . . . . . . 23

4.2 LIS-OPO flight profile example (from file QAR1767) . . . . . . . . . . . . . . . . . . . . . . 24

4.3 LIS-OPO phase time and fuel consumption . . . . . . . . . . . . . . . . . . . . . . . . . . 24

4.4 OPO-LIS phase time and fuel consumption . . . . . . . . . . . . . . . . . . . . . . . . . . 25

4.5 LIS-OPO average savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

4.6 OPO-LIS average savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

4.7 Relative savings in % for the LIS-OPO city-pair. . . . . . . . . . . . . . . . . . . . . . . . . 27

4.8 LIS-BCN route example (from file QAR154) . . . . . . . . . . . . . . . . . . . . . . . . . . 28

4.9 LIS-BCN flight profile example (from file QAR154) . . . . . . . . . . . . . . . . . . . . . . 28

4.10 LIS-BCN phase time and fuel consumption . . . . . . . . . . . . . . . . . . . . . . . . . . 29

4.11 BCN-LIS phase time and fuel consumption . . . . . . . . . . . . . . . . . . . . . . . . . . 29

4.12 LIS-BCN average savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

4.13 BCN-LIS average savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

4.14 Relative savings in % for the LIS-BCN city-pair. . . . . . . . . . . . . . . . . . . . . . . . . 31

4.15 LIS-NCE route example (from file QAR98) . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

xiii

4.16 LIS-NCE flight profile example (from file QAR98) . . . . . . . . . . . . . . . . . . . . . . . 32

4.17 LIS-NCE phase time and fuel consumption . . . . . . . . . . . . . . . . . . . . . . . . . . 33

4.18 NCE-LIS phase time and fuel consumption . . . . . . . . . . . . . . . . . . . . . . . . . . 33

4.19 LIS-NCE average savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

4.20 NCE-LIS average savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

4.21 Relative savings in % for the LIS-NCE city-pair. . . . . . . . . . . . . . . . . . . . . . . . . 35

4.22 Total average phase time and fuel consumption . . . . . . . . . . . . . . . . . . . . . . . . 36

4.23 Total average savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

4.24 Total relative savings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.25 Average saving per route in % . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.26 Average saving per route in kg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

4.27 Average saving for Outbound and Inbound flights (LIS) . . . . . . . . . . . . . . . . . . . . 40

4.28 Expected fuel burn increase adding 200kg of extra fuel [4] . . . . . . . . . . . . . . . . . . 42

xiv

Glossary

AGIFORS Airline Group of the International Federation of

Operational Research Societies

AOM Aircraft Operating Manual

APU Auxiliary Power Unit

ARINC Aeronautical Radio, Incorporated

ATC Air Traffic Control

BCN IATA code for Barcelona Airport

CG Center of Gravity

CIO Chief Information Officer

COC Cash Operating Costs

CVR Cockpit Voice Recorder

DVDR Digital Voice and Data Recorder

FDAU Flight Data Acquisition Unit

FDR Flight Data Recorder

FF Fuel Flow

FL Flight Level

FMS Flight Management System

FOD Foreign Object Damage

GPU Ground Power Unit

IAS Indicated Air Speed

IATA International Air Transport Association

ICAO International Civil Aviation Organization

IT Information Technology

LIS IATA code for Lisbon Airport

MAU Modular Avionics Unit

NCE IATA code for Nice Airport

NM Nautical Mile

NOTAM Notice to Airmen

OPO IATA code for Oporto Airport

xv

PCMCIA Personal Computer Memory Card International

Association

PGA Portugalia Airlines

QAR Quick Access Recorder

SETI Single Engine Taxi In

SETO Single Engine Taxi Out

SOP-M Standard Operating Procedures Manual

TAP Transportes Aereos Portugueses

xvi

Chapter 1

Introduction

Globalization is a topic of the present in today’s constant changing world. Adaptability is key to success

for any industry and accountability for human actions is felt not only nationwide, but worldwide. That is

why when the 2008 crisis hit, it hit everybody from very established to emerging countries, making it a

global crisis.

The aviation industry in itself was one of the main players when it came to making globalization

possible. However, for an industry as sensitive as this one, the global crisis has left its toll with losses of

several billions from which the industry is only recently giving the first real signs of recovery. The crisis

reflected in a lower demand for tickets, as well as a very significant rise in fuel prices, which resulted in

an excessive offer for the market needs and the growth of low-cost airlines.

To remain competitive, airlines were forced to lower their fares, resulting in marginal profit operations

for many, in an effort to remain afloat. However, with this decrease in revenue, a corresponding reduction

in expenses was also due, and in this sense it became of the utmost importance to develop sustainable

policies for the airlines operation, not only to provide a more efficient and optimized activity, but also to

make it more robust and a little less dependent on the market fluctuations. This was first addressed by

low-cost airlines, who made use of the crisis to increase competition within the sector even more.

It was with this objective in mind that PGA - Portugalia Airlines, a portuguese regional airline - started

several years ago its first studies developing tools to help identify and address different cost reduction

and operation optimization strategies. This work illustrates some of these efforts, applied to a new

fleet just recently acquired by the company, and focuses on fuel conservation optimization through the

implementation of a set of operational measures.

1

1.1 PGA - Portugalia Airlines

Portugalia Airlines is a portuguese regional airline based in Lisbon International Airport, operating both

domestic and international routes.

The company was founded on the 25th July 1988, but only started operating two years later, on the

7th July 1990, with a domestic flight between Lisbon and Oporto. That same day, the route connecting

Lisbon and Faro was also initiated. After another two years, in June 1992, the first international flight

was accomplished establishing routes to Cologne, Turin and Strasbourg, and by 1993 a full fleet of six

Fokker 100 was completed.

In 1997, PGA received the first of what would end up being a fleet of eight Embraer ERJ-145, com-

pleting a total fleet of 14 aircraft.

By mid 2007, PGA was bought by TAP Portugal, a major portuguese airline. Integrating the TAP

Group, which was also a member of Star Alliance, PGA no longer works the regional market inde-

pendently, and starts working within a group logic. Though still flying with its own livery, the company

now charges TAP for the lease of its aircrafts, while still providing the flight crews, maintenance and

insurance.

This allowed both companies to grow with each other and to expand the offer, reaching market niches

otherwise inaccessible, and improving the group network. Despite this contractual relation, PGA always

remained an independent company, with both TAP and Portugalia having their own legal identity.

On the 14th January 2016 TAP Portugal announced PGA would be rebranded to TAP Express, as

part of a restructuring within the group.

With the rebranding came a new fleet, phasing out the previous one, and eight ATR 72-600 and nine

Embraer E-190 were bought from Azul, with only two of the latter left to deliver by the end of August

2016. While the ATR fleet is currently operated by White Airways, the E-190 started flying on the 23rd

May 2016, in a flight connecting Lisbon and Nice.

Figure 1.1: Embraer E190 - CS-TPS [1]

2

1.2 Motivation

Through the last years, especially since the year 2000, the airline industry has faced some of its biggest

challenges to date. The world big economical crisis combined with the ever-growing competitiveness

within the sector has led to smaller and smaller profit margins, making it difficult for even the most

experienced and established airlines to survive.

In fact, since the beginning of the century, hundreds of airlines have filed for bankruptcy, resulting

in the extinction of many airlines or in some cases the creation of global code sharing alliances and

merging of many companies into big groups. The only way for airlines to survive is to achieve the best

economical performance optimization possible.

Figure 1.2: Brent prices in Europe from 1988 to 2016 [2]

Worldwide Airline Industry 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015F 2016FExpenses ($ billion) 376 409 450 490 571 474 536 623 687 695 716 659 647Fuel ($ billion) 65 91 127 146 204 134 152 191 228 230 226 181 127Fuel (% of expenses) 17.3 22.2 28.4 29.8 35.7 28.3 28.3 30.8 33.1 33.1 31.6 27.5 19.7Brent ($/barrel) 38.3 54.5 65.1 73.0 99.0 62.0 79.4 111.2 111.8 108.8 99.9 53.9 45.0CO2 emissions (million tonnes) 628 651 658 675 669 634 665 685 693 709 739 781 817

Table 1.1: Fuel expenses for the airline industry [3] - Appendix A.

Since the year 2000, jet fuel has faced tremendous variations in price due to its high volatility (Table

1.1, Figure 1.2). Political and economic factors, as well as wars, all influence the crude price, which can

be very unpredictable. It is even possible to look at the evolution of Brent prices and identify reactions to

important events through history, like the small peak in late 1990 due to the war in Iraq (one of the most

important crude producers); the growing tendency since 2001, after the terrorist attacks of 9/11, and

even the highest peak in 2008, a very critical time for the airline industry, coincident with the beginning

of the current global economic crisis.

Worldwide Airline Industry 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015F 2016FRevenue ($ billion) 379 413 465 510 570 476 564 642 706 720 751 718 709Expenses ($ billion) 376 409 450 490 571 474 536 623 687 695 716 659 647Operating Profit ($ billion) 3.3 4.4 15.0 19.9 -1.1 1.9 27.6 19.8 18.4 25.3 35.1 59.5 62.2Net Profit ($ billion) -5.6 -4.1 5.0 14.7 -26.1 -4.6 17.3 8.3 9.2 10.7 13.7 35.3 39.4

Table 1.2: Economic performance of the airline industry [3] - Appendix A.

The variation in fuel prices directly influences the expenses of airlines, representing around 30%

of the overall expenses since 2006 (Table 1.1). In turn, the expenses along with the revenue dictate

3

the profits of the industry, illustrated in Table 1.2 and Figure 1.3. The global crisis impact on the in-

dustry is undeniable and represented several billions of losses since the beginning of the century, from

which it seems to be only recovering in the last couple of years. Note that for 2015 and 2016 the data

corresponds to forecasts, still to be fully confirmed.

Figure 1.3: Economic performance of the airline industry [3] - Appendix A.

For a small airline like PGA, operating a fleet of regional jets on short and medium-haul routes, the

operational conditions are made even worse and shall therefore be analyzed.

The fact that regional jets compete with large jet aircraft but, by definition, fly shorter distances,

means they spend less time flying and more time at airports, taxiing, idling and maneuvering on turnarounds

- measured in block hours. Airplanes are optimized for the cruise phase of flight, and regional jets are

no different, which means they spend a lot more time in non-optimum stages of flight, making them less

efficient. A good way to quantify this inefficiency is to calculate the ratio between block hours and flight

hours, and the higher the ratio, the less ground efficient an airplane is.

This is made worse for regional jets because, like larger aircraft, they usually focus on major urban

airports that not only mean higher costs, but also much more air traffic, stricter ATC rules, which in turn

leads to more delays, higher taxi and idle times, and a smaller variety in terms of operational procedures

availability (e.g., different climb, descent or approach procedures).

Not only are regional jets less efficient on the ground, they are also less efficient in the air. Because

they are technologically similar to larger aircraft, many times employing the same systems and engines,

they have similar performance charts when it comes to altitude. This means both types of aircraft usually

have very similar optimal flight levels. However, due to the nature of regional jets, flying shorter routes,

the cruise phase is substantially reduced and so is the efficiency. And the shorter the route is, the lower

its efficiency, both in the air and on the ground.

Another big limitation of regional jets is the comparatively high flight cycle per flight hour ratio. Again,

from flying shorter routes, regional jets complete much more cycles than regular larger aircraft in the

4

same amount of time, and because a lot of maintenance interventions are scheduled based on flight cy-

cles and not on flight hours, inspections are carried out more often. The outcome is higher maintenance

costs, reaching up to 20% of direct operating costs.

Despite all of the above, regional jets still present some advantages, especially when it comes to

passenger comfort. Unlike their main competitors (i.e., turboprops), regional jets fly much faster and

silently, making for higher customer satisfaction and load factors.

When flying a particular airplane, airlines define a Cash Operating Cost (COC) relating to that oper-

ation. For a given route, it involves three main components:

• Fixed Costs: fixed expenses of each leg, i.e. landing, navigation and airport fees;

• Time Related Costs: all the costs that are a function of flight time, i.e. maintenance costs, crew

costs, etc. ($/hour);

• Fuel Related Costs: cost of fuel burned in a given leg ($/kg or $/lb).

Fuel Related Costs can reach up to 40% of the total COC of a flight, and are usually where the most

flagrant saving opportunities are identified. Because of this, the implementation of fuel consumption op-

timization through fuel conservation measures becomes one of the most important tools when it comes

to cost reduction strategies.

Even with jet fuel prices considerably lower since 2008, and the sector giving its first signs of recovery

since the beginning of the crisis, it is still of the utmost importance for airlines to optimize their operation.

Marginal profit margins imply not only small profits, but more importantly, the smallest variation in costs

(e.g., jet fuel prices) can mean non-profitable operation and losses of millions in this industry.

Even though there are complete fuel efficiency package tools available on the market (to be dis-

cussed in Section 2.1), they invariably come with a hefty price tag. This work is a preliminary way for

PGA to evaluate the potential of implementing fuel conservation strategies on their new fleet, focusing

on what were considered the most important and readily available operational procedures.

5

1.2.1 1% Fuel Conservation Estimations

One interesting value to calculate is the amount of savings, both in kg of jet fuel and in euros, that could

be obtained for the company if it reduced its fuel consumption by 1%. To do this, a typical operational

profile of the company is needed, and Embraer provides Table 1.3 with the common operation scenario

in Europe and North America for its E-jets (only the E-190 is presented here), on a 600 NM trip [4].

TypicalOperational

Profile

Embraer 190FAA Reserves EASA Reserves

lb kgTakeoff Weight 94 946 42 925

Trip Fuel 6949 3147Trip Time 90 min

Table 1.3: Typical Operational Profile for a 600 NM trip [4]

Reducing trip fuel by 1% would result in the trip savings presented in Table 1.4, which by themselves

can seem like an insignificant value, but multiplied by the number of flights an airline with a fleet of twenty

of these aircraft performs during a year yields the surprising value of 1180 metric tons of jet fuel saved

per year.600 NM Trip Embraer 190

1% Fuel Savingsper Leg

kg 31lb 69

Annual Savings(20 Airplane Fleet)

kg 1 180 000lb 2 600 000

Table 1.4: Embraer 1% Savings Estimation [4]

However, for the time being, PGA still has a slightly more modest fleet of only nine aircraft, and

therefore these estimates must be adjusted for that reality. Still, this returns the impressive value of 531

metric tons of potential fuel savings a year.

Figure 1.4: Current price of aviation jet fuel (23 September 2016) [5]

Considering the current jet fuel price in Europe of 446.6 $/metric ton (Figure 1.4), this means a

total yearly saving estimate of approximately 237k$, equivalent to 212ke. Note that apparently small

amounts of fuel economy translate to very significant financial differences, making this a very important

topic when it comes to cost reduction.

6

1.3 Objectives

The main objective of this work is to evaluate the impact of fuel conservation strategies on a regional

airline performance. By optimizing the available resources, the goal was to estimate the potential saving

in fuel consumption and associated costs.

For this work, the focus was set on operation optimization not because it has the highest saving

potential, but because it is the most simple and direct way for an airline to start implementing fuel

conservation. Of course, this optimization has to be studied for each aircraft model separately, and

eventually even for different routes and airports.

Optimizing the flight planning would also potentially yield very good results in terms of fuel econ-

omy, but this is a field already extensively studied and with plenty of solutions presented by different

companies, mostly software tools that integrate data from many sources (aircraft data, loading data,

meteorological data, ATC requirements, NOTAM, among many others) to calculate the optimal flight

plan. It is substantially harder to implement due to the amount of variables involved, and because every

flight phase influences the others, the optimization must be made accounting for the whole flight (i.e.,

optimizing the climb phase for fuel saving could mean more fuel burned during cruise).

As for maintenance optimization, it is relatively simple to implement, but must be studied for each

aircraft separately. Additionally, it requires a certain amount of data from operating the fleet continuously

for a long enough period of time, in order to properly analyze and predict aircraft degradation during a

real and particular operation scenario. Although the new Embraer 190 fleet is not exactly new, as the

airplanes bought have almost 5 years of operation, only a couple of months ago has PGA started flying

them with their own operation standards and routes, therefore operational optimization should be the

first step towards full airline efficiency.

Therefore, the whole process was divided into three main objectives:

• Data collection from the aircraft recorder systems;

• Data selection, processing, and estimation of savings;

• Statistical data analysis, with the evaluation of each saving measure.

1.4 Structure

This document is divided into five different chapters. The second chapter discusses the state of the art

in this industry, an overview of the current available solutions and the tools used during the execution

of this work. The third chapter enumerates the methods used for such analysis, the savings measures

and the associated fuel economy metrics. The fourth chapter details the results of the analysis on the

provided sample, discussing the various routes and measures. Finally, the fifth and last chapter presents

the conclusions of this work, leaving suggestions for future work in the area.

7

8

Chapter 2

State of the Art & Analysis Tools

2.1 Market offer

Nowadays, due to the growing fuel economy and environmental sustainability awareness, the number of

companies offering complete software solutions to elevate airlines efficiency has faced a great expan-

sion. This includes Crew and Fleet optimization, as well as Maintenance and, most important for this

work, Fuel Efficiency.

Two of the most important suppliers of these services are world-renown aerospace product developer

Honeywell and OpenAirlines, the latter being a company with 10 years of experience in airline planning

and operation optimization.

2.1.1 Honeywell - Aviaso

Aviaso was founded in 2003, in Switzerland, based on the needs of airlines to reduce their expenses,

optimizing the available resources [6]. In September 2015, Honeywell acquired Aviaso, empowering one

of the already most important companies in the airline efficiency industry.

Figure 2.1: Aviaso method breakdown [6]

9

Aviaso method to take on the Fuel Efficiency theme is divided into four main steps [7] (Figure 2.1).

First, it is important to collect the relevant data from the many airline departments and IT infrastructures,

from flight planning, to operations, maintenance, etc... Then, the data must be checked for quality

assurance - if corrupted or incomplete data is inserted into the system, the results cannot reflect the real

savings potential. After having all the relevant data properly checked, fuel savings potential is calculated

and the current fuel conservation program progress is monitored. Finally, it is imperative to convey this

data to each of the responsible entities, customized for their necessities.

Figure 2.2: Example of Aviaso dashboard [6]

Besides fuel efficiency solutions, Honeywell Aviaso also provides software for emissions reporting

as well as consulting and training for fuel efficiency, operational efficiency and emissions management.

Another very important milestone for Aviaso, and the aviation industry worldwide, was attracting DFS as

a customer, the German ATC authority, making it clear that a transverse effort is required for the entire

industry in order to have an efficient ecosystem.

Honeywell Aviaso customers include Aer Lingus, Air Baltic, Air Berlin, Air Transat, Belair Airlines,

Cargolux Airlines, CityJet, Condor, DFS (German ATC), Lufthansa, Etihad Airways, Europe Airpost,

Germanwings, KLM Cityhopper, LOT Polish Airlines, Lufthansa Cargo, Monarch Airlines, Thomas Cook

Airlines Belgium, Thomas Cook Airlines Scandinavia, Thomas Cook Airlines UK, Wideroe, among others

[6].

10

2.1.2 OpenAirlines - SkyBreathe

Founded in 2006, OpenAirlines is a company focusing on three main aspects of airline efficiency [8]:

• Fuel efficiency;

• Crew efficiency;

• Fleet efficiency.

By optimizing the resources across the various airline departments, OpenAirlines promises fuel sav-

ings in the region of 2% to 5% [8], corroborated by IATA estimates of 3% to 5% for a systematic airline

optimization [9].

Figure 2.3: SkyBreathe method breakdown [8]

Much like the competition, Skybreathe also presents a few steps in its fuel conservation optimization

analysis, five in this case. Both the data integration and quality control are similar, in terms of concept,

with the difference that the analysis is separated into two different steps here - savings computation

and data analysis. Finally, the data communication step to the different entities is given a great deal of

importance, with fully customizable reports and dashboards for all types of users ([8], [10]).

Figure 2.4: Example of SkyBreathe dashboard [8]

11

As seen in Figure 2.4, SkyBreathe dashboard allows for a comprehensive understanding of the

airline efficiency. It allows for a route analysis, flight phase analysis, best and worst practices (the best

being the ones where the fuel saving potential is being fulfilled), individual aircraft savings and even pilot

savings [10].

Besides counting with 22 different customers, Skybreathe has also been distinguished with 5 different

awards since it began its operations [8] (Table 2.1).

Year Award2006 Leader of 3 Clean Sky Projects2008 Best Innovative AGIFORS2010 Best Innovative AGIFORS2013 Sustainable Development Trophies - La Melee2015 International Digital Trophies - Frenchtech2015 Top 20 Most Promising Aerospace Providers - CIO

Table 2.1: OpenAirlines Awards [8]

2.1.3 Embraer fuel conservation strategies

Like most aircraft manufacturers, Embraer provides manuals and technical sheets that focus on re-

source optimization either in terms of planning, operation or maintenance. As stated earlier, this work

focused on operation optimization and therefore Embraer recommended savings procedures constituted

the foundation of this study. These procedures are presented and analyzed further in depth in Chapter

3.

2.2 Data capture and extraction

2.2.1 Quick Access Recorder

For fuel efficiency measures to be analyzed and implemented, it is necessary to have flight data re-

garding the flight planning and operations. In order to obtain the data from the various sensors and

parameters computed by the airplane, the Quick Access Recorder (QAR) was used.

The QAR is a flight data recorder system that receives inputs from the FDAU and records the data on

a PCMCIA unit that can later be downloaded to an external computer. It is used by airlines to improve

flight safety and operational efficiency.

Since usually a QAR most of the times is not a mandatory system on commercial flights, it is not

designed to survive a crash, like the Flight Data Recorder (FDR). This also means that it is a more

flexible system for airliners, as it can process data at much higher rates than the FDR can, and frequently

for longer periods of time.

The QAR unit used on PGA Embraer 190 fleet is manufactured by SAGEM, and its part number is

ED35E109-04-00. This QAR dataframe, like most others, is fully configurable. Which parameters to be

12

Figure 2.5: Simplified QAR architecture [11]

recorded and the sample rates are all programmable, as is the start and stop logic for the recording,

default being when any of the following conditions are active:

• Left Engine Starter Valve Opened - eng1AtsV lOp = 1;

• Right Engine Starter Valve Opened - eng2AtsV lOp = 1;

• Left Engine Low Pressure (LP) Compressor Shaft Speed over 20% - N1L ≥ 20%;

• Right Engine Low Pressure (LP) Compressor Shaft Speed over 20% - N1R ≥ 20%;

• Left Engine High Pressure (HP) Compressor Shaft Speed over 20% - N2L ≥ 20%;

• Right Engine High Pressure (HP) Compressor Shaft Speed over 20% - N2R ≥ 20%.

However, for PGA aircraft, the QAR is set to record whenever the plane is energized, in order to keep

a more comprehensive record for safety and fuel consumption analysis, allowing, for example, for APU

usage statistics. The electrical energy for the plane systems can come from the engines, the APU or an

external GPU.

2.2.2 Analysis Ground Station

To analyze, extract and produce reports with the QAR raw data, a special software tool is necessary,

one that reads the QAR configuration and dataframe specification. For this work, the Analysis Ground

Station (AGS) software by the QAR manufacturer SAGEM was used.

Allowing for a multitude of data processing, parameter creation, graphical representation and many

others, this software is mainly used by the Safety Department at PGA in order to produce reports and

analyze events triggered by the aircraft, such as incorrect operation, faulty equipment or maintenance

warnings.

13

Figure 2.6: AGS flight database with filters applied

Figure 2.7: AGS manual analysis feature for individual flight

Due to the complexity of the software, only a small part of its potential was used for this study. In

this work, the program was essentially used to filter the flights by routes and aircraft (Figure 2.6), then

to produce reports based on the relevant variables (Figure 2.7), and finally to export this data as .ENG

files (formatted like a .csv) later to be read and processed by MATLAB.

14

Chapter 3

Methodology

In order to evaluate the fuel saving potential for this airline, and in particular for the E190 fleet, a group

of significant measures that were simultaneously easy to evaluate and to put to practice were chosen

and characterized. To do this, many articles by several aircraft producers and industry associates ([4],

[11],[12], [13], [14], [15], [16], [17], [9]) were analyzed and compared, with special emphasis on three

documents:

• GP1999 by Embraer [4];

• AOM by Embraer [12];

• SOP-M by PGA [13].

Then, to analyze the effect of each of the measures on the airline operations, a set of routes (city-

pairs) was defined. This allowed for a rough statistical analysis of various flight scenarios and corre-

sponding fuel savings, evaluating the financial viability of the previously defined measures.

3.1 Fuel Savings Measures

For this work, according to the suggestions from GP1999 [4], five main fuel saving measures were

chosen for representing relatively simple day-to-day operational procedures that can help reduce fuel

costs. These are:

• Auxiliary Power Unit - turning it on only when necessary and shutting it down as soon as one

engine is turned on;

• Single Engine Taxi Out;

• Single Engine Taxi In;

• Thrust Reversal - once again reducing its use to the absolute minimum necessary and shutting it

down before reaching taxi speeds;

• Idle Descent - consisting of setting the engines to idle thrust during the descent phase.

15

It should be stressed that all the savings estimated in this work are calculated for optimal conditions

and thus, their full saving potential can be very hard to achieve under real-life operation. Be it because

of ATC, flight delays, meteorological aspects, mechanical condition of the aircraft or many other rea-

sons, the important result is to recognize how much fuel could be saved by simply accomplishing these

measures, if all the unpredictable aspects of flying went according to plan.

3.1.1 Auxiliary Power Unit

The APU, or Auxiliary Power Unit, is a device designed to generate pneumatic and electrical AC power

for the various systems of the aircraft. It consists of a gas turbine engine, located in the airplane tailcone,

that runs on regular jet fuel and can provide bleed air for starting the engines and for the air conditioning

packs, coupled with an electrical AC generator that supplies 115V 40kVA to the electrical system [4].

Figure 3.1: Embraer 190 APU system schematic [12]

Considering jet fuel prices, using the APU on ground is much more expensive than running a GPU

as an electrical power source, except on very rare occasions. Similarly, external air carts can be used

to power the air conditioning packs, saving valuable fuel on ground.

Companies are invited to evaluate if continuous use of APU at the gate instead of GPU is the best

option, considering that [4]:

• Main APU components fail by cycle, and therefore, for really short turnarounds, the marginal fuel

saving might not justify the extra APU maintenance costs;

• GPU power is most of the time leased from ground handling companies and can be exces-

sively priced in some situations, or charged by the hour, turning it into a pricier option for short

turnarounds;

• External air carts may not be provided at all airports or, when available, may be rent by ground

handling companies, with the same eventual limitations as the GPU.

16

For when APU continuous use on the ground is actually the most cost effective measure, it is rec-

ommended its usage time should be minimized. This means only turning the APU on after landing and

turning it off immediately after starting up the engines.

Conditions

Unfortunately, due to the way in which data is saved in the QAR, it is very hard to evaluate the savings

potential on turnarounds. Not only that, but it would require a constantly up-to-date database of fuel

prices, GPU and external air leasing prices in every airport and all the conditions associated with the

lease.

Therefore, the only condition set for the savings analysis of the APU, is that it should be turned

off whenever there is at least one engine running. This means turning off the APU as soon as the

first engine is started (using the engine to provide pneumatic and electrical power) and turning it on

only immediately before shutting the last engine down. A buffer time of 60s is granted in both of these

situations, for the crew start-up/shutdown checklist time.

Savings estimates

Whenever the above condition is not met, and the APU is running simultaneously with the engines, a

fuel saving can be estimated.

This is done by converting the APU Fuel Flow from PPH (pounds per hour) to kg/s and integrating it

over that time interval. The result is the amount of kg of fuel that could have been saved, had the APU

been used efficiently.

3.1.2 Single Engine Taxi

In order to improve fuel savings, a single engine taxi can be used, delaying the start of the second engine

prior to takeoff and shutting one engine just after landing when taxiing in. Applying these measures

requires, however, some consideration ([4], [12]):

• Ramp Weight - the higher the weight, the more power is needed to taxi the airplane;

• Ramp Gradient - steep taxiways require more power;

• Engine warm up and cooling down period - a minimum interval of 2min should be applied;

• Taxi time to active runway should be estimated in order to start the second engine on time;

• Slippery or contaminated taxiways - single engine taxi should be avoided in this scenario;

• Higher pilot workload - second engine start while taxiing is unadvised.

For the most part, the Ramp Weight and Gradient don’t pose a problem to E190 aircraft, which are

relatively light and thus require less power to taxi. The engine warm up and cooling down periods,

however, must be met to allow for engine thermal stabilization - the second engine must be kept running

for at least 2 minutes at idle before selecting high thrust settings or shutdown. It is also advised that,

17

when taxiing out, the second engine is started with the airplane static to avoid pilot heads down condition

(start-up checklist) during taxi.

During single engine taxi, the fuel flow is approximately 5 kg/min or 300 kg/h, due to an increment in

thrust compared to normal taxi thrust per engine [4].

Conditions

For SETO (Single Engine Taxi Out), the only limitation is the second engine warm up time, and therefore,

the only condition is to start the second engine 2 minutes before takeoff [4].

Similarly, for SETI (Single Engine Taxi In), the only condition is to shutdown the second engine 2

minutes after landing, in other words, 2 minutes after taxi out starts [4].

Savings estimates

Whenever the above conditions aren’t met (i.e. the second engine is running more than 2 minutes before

takeoff or after landing) a fuel saving can be estimated.

This is done by calculating the difference between the actual aircraft fuel flows (FF1 + FF2) and the

average SET fuel flow (which, as stated before, is approximately 5 kg/min or 300 kg/h [4] - this is the

value assumed during the computation) and integrating them.

3.1.3 Thrust Reversal

Reverse thrust can be used to stop the aircraft in a shorter runway length. This is essentially accom-

plished by redirecting the engine’s exhaust forward, rather than backward, providing deceleration, as

shown in Figure 3.2.

Figure 3.2: Embraer 190 thrust reverser system schematic [12]

Even though this system can help reduce wear on the brakes, it also usually means higher fuel

consumptions and engine wear, depending on the amount of reverse thrust selected by the pilot. With

full reverse thrust, fuel flow can reach 3200kg/h, a value similar to takeoff thrust configuration [4].

The higher the aircraft speed, the more efficient reverse thrust is, since it uses more air mass and

therefore produces bigger brake forces. However, applying high reverse thrust at lower speeds can

18

induce an inlet vortex, exhaust gas and FOD1 ingestion, especially in contaminated runways, and should

therefore be avoided. On snow or ice covered runways, it can even lead to low forward visibility due to a

”whiteout” (snow being propelled forward by the engines) [13].

Conditions

One should note that, considering fuel efficiency, the thrust reversers should only be engaged when

absolutely necessary, due to short runway length or other limiting factors (e.g. inoperative brakes).

According to the GP1999 by Embraer [4], FOD ingestion can occur below 80 KIAS, so it is advised to

turn off maximum reverse thrust below that speed. As the airspeed reduces, so does the thrust reversers

efficiency, and so it is stated that at 60 KIAS reverse should be canceled altogether in such way that it

will be completely stowed when reaching normal taxi speed.

Savings estimates

”Keeping full reverse thrust actuated until airplane stops completely will increase approach and landing

fuel by 10kg [4].” Therefore, it is expected that the savings calculated with this method fall below that

number.

Whenever reverse thrust usage does not comply with the above stated conditions, a saving is calcu-

lated by subtracting to the actual engines fuel flow, the average idle fuel flow, and integrating it over that

period of time.

3.1.4 Idle Descent

The descent phase usually represents a lower fuel consumption than the climb or cruise phases, with a

trip time percentage that should be around 10% for short and medium range flights, and fuel flows many

times smaller [4].

From a fuel consumption point of view, the descent should be done as fast as possible, using high

speeds. However, this can cause passenger discomfort, due to the cabin pressure rate of change, and

for really high speeds, can cause the trip fuel to actually increase due to the extended cruise period and

high fuel flows during descent.

To maximize fuel savings, idle thrust coupled with a constant flight path angle is recommended by

Embraer and enforced by PGA in their SOP-M [13], due to the lower fuel flows, effectively decreasing

descent fuel. This procedure is called Idle Descent.

Ideally Embraer recommends the following descent speed schedule [12]:

• Mach 0.77 above 30200 ft;

• 290 KIAS between 30200 ft and 12000 ft, decreasing linearly to 250 KIAS at 10000 ft;

• 250 KIAS below 10000 ft (due to many existing worldwide operational regulations that impose this

limit).1Foreign Object Damage

19

The manufacturer stresses that the Embraer 190 was designed and flight tested for bird impacts up

to speeds of 300 KIAS, and can therefore fly those speeds below 10000 ft safely. It is estimated that the

elimination of these speed limits both in the descent and climb phase would result in savings between

14 and 25 kg of fuel per flight [4], while contributing to reducing the flight time (and therefore time costs).

Conditions

For the savings analysis, the engines thrust setting was taken into consideration. As such, whenever the

Thrust Lever was not set to idle in any of the engines during the descent phase, a fuel saving opportunity

was identified.

Savings estimates

Whenever at least one engine has its thrust setting different from idle during descent, the potential fuel

saving is calculated taking into account an average idle fuel flow per engine. However, idle fuel flow

depends linearly with the operation altitude, as shown by Nikoleris et al. in [18], and therefore must

be estimated every second. This estimation was made based on a flight in our database with a nearly

perfect idle descent, that resulted in the following linear fit:

FF (kg/h) = −0.01612× h(m) + 377.01293 (3.1)

Figure 3.3: Idle Fuel Flow variation with Altitude

This means calculating the extra fuel burned by adding both engines fuel flow, subtracting the average

estimated idle fuel flow for that altitude, and integrating it over the period in which the conditions were

not met.

20

3.2 Route choice

Having the savings measures correctly implemented, it became imperative to define a sample that could

represent this regional airline’s operation. In that sense, the flight data was analyzed and the various

flown routes departing from Lisbon were listed both by distance and number of flights with a little over

one month of operation (Table 3.1).

Flight Length Destination Number of Flights Ground Distance (NM)

Short (Dist. ≤ 300NM)Oporto 3 171Algier 2 243

Medium (300NM < Dist. ≤ 700NM)Madrid 2 314

Barcelona 14 581Nantes 2 651

Long (Dist. > 700NM)Marseille 29 769

Lyon 42 795Nice 50 865

Table 3.1: PGA Embraer E190 Lisbon outbound flights (as of 30th June 2016)

In order to obtain more homogeneous results, three city-pairs were chosen, one short, one medium

and one long-haul (for a regional airline standards), taking into account the number of flights in each

distance category. However, each city-pair represented an outbound and an inbound flight, which meant

the sample was comprised of 6 routes:

• LIS-OPO & OPO-LIS - flights connecting Lisbon and Oporto;

• LIS-BCN & BCN-LIS - flights connecting Lisbon and Barcelona;

• LIS-NCE & NCE-LIS - flights connecting Lisbon and Nice.

Then, for each of these routes, 10 flights were selected (20 per city-pair), completing a total of 60

flights. These were then run through the the tool developed in MATLAB, in order to have a significant

sample to analyze statistically.

21

22

Chapter 4

Results

4.1 Route Analysis

4.1.1 LIS-OPO & OPO-LIS

Figure 4.1: LIS-OPO route example (from file QAR1767)

Being the shortest route analyzed, it is to be expected that a flight between Lisbon and Oporto has

a fairly low efficiency, as less time is spent cruising and more time in non-optimal phases of flight like

taxiing, taking off and climbing. However, this does not necessarily mean higher saving potentials, but a

careful study of an average flight can help identify and justify the best savings to be implemented.

23

Figure 4.2: LIS-OPO flight profile example (from file QAR1767)

Figure 4.3: LIS-OPO phase time and fuel consumption

In this short route, taxi times are very prominent (Figures 4.2 and 4.3). We can see Taxi Out is

actually the longest flight phase for this route, reaching above 25% of the total trip time and Taxi In times

just under 10%. Still, the phase with the most fuel consumed is clearly Climb, with about 40% of the fuel

consumed, but only under 15% of the total time, which is very similar duration to Cruise.

Once again (Figure 4.4), for the Oporto to Lisbon flights, taxi times are very relevant, but here the

longest flight phase is actually Descent, which is a consequence of the very short distance of the flight.

Also like before, the phase with the most fuel consumption is Climb, which is explained by its rather high

relative duration combined with very high fuel flows.

It is also relevant noticing Taxi Out times with a much shorter duration, nearly halved from 25.5% to

24

Figure 4.4: OPO-LIS phase time and fuel consumption

Variable Route Unit Taxi Out Take Off 2 Segment Initial Climb Climb Cruise Descent Approach Final Landing Taxi In

TimeLIS-OPO

s 790,6 33 111,4 0 430,1 474,4 673,2 130 143,6 47,7 269,2% 25,5 1,1 3,6 0,0 13,9 15,3 21,7 4,2 4,6 1,5 8,7

OPO-LISs 382,1 30,1 113,8 0 387,4 637,7 810,2 125,8 152,6 48,6 362,3% 12,5 1,0 3,7 0,0 12,7 20,9 26,6 4,1 5,0 1,6 11,9

FuelLIS-OPO

kg 109,2 45,9 148,7 0 541,8 297,7 141,8 31,7 56,4 9,9 36,1% 7,7 3,2 10,5 0,0 38,2 21,0 10,0 2,2 4,0 0,7 2,5

OPO-LISkg 58,1 41,3 150,4 0 462 391 238 34,3 67,1 10,2 41,4% 3,9 2,8 10,1 0,0 30,9 26,2 15,9 2,3 4,5 0,7 2,8

Table 4.1: LIS-OPO and OPO-LIS average phase time and fuel consumption

12.5% (Table 4.1), as well as Taxi In times with a fairly higher duration, reaching 11.9%, compared to the

previous 8.7%. Both these differences come from the fact that Lisbon International Airport is much more

congested and with more complex and longer taxiways, therefore taxi times are usually much higher

than in Oporto.

Figure 4.5: LIS-OPO average savings

25

From Figure 4.5 it is possible to see that Single Engine Taxi Out is the highest potential saving mea-

sure for the LIS-OPO route, with nearly 2% total trip fuel that can be saved from correct implementation

of this measure. In fact, the difference to Figure 4.6 is pretty dramatic, with APU and SETO savings

practically halved for the reverse route (OPO-LIS), while Idle Descent reaches more than 3.5%.

Figure 4.6: OPO-LIS average savings

Idle Descent savings potential also relates to the higher traffic found in Lisbon International Airport,

because many times pilots are encouraged by ATC to accelerate or to keep a certain speed depending

on other departing and/or arriving aircraft. It is always preferable to adapt the descent phase than to be

forced to enter a holding pattern, thus Idle Descent savings potential more than doubles when landing

in Lisbon compared to Oporto.

Route Unit Thrust Reverser APU SETO SETI Idle Descent Total

LIS-OPOkg 0,49 10,56 26,57 1,92 19,55 59,09

Total % 0,03 0,74 1,87 0,14 1,38 4,16Relative % 0,83 17,87 44,96 3,24 33,09 100,00

OPO-LISkg 0,54 5,66 12,76 2,33 54,55 75,85

Total % 0,04 0,38 0,85 0,16 3,65 5,08Relative % 0,72 7,46 16,83 3,08 71,92 100,00

Table 4.2: LIS-OPO and OPO-LIS average savings estimates

As flight distances and durations are fairly similar for the inbound and outbound flights of the same

city-pair, comparing savings estimates in % between them is viable, however, it is always preferable to

analyze the results in absolute values, as in Table 4.2. This also allows for comparison across different

flight distances, presented further ahead.

Here, for example, it is possible to see that the inbound flight has a saving potential more than 15kg

higher, despite 26.57kg of fuel wasted in the Taxi Out phase for the outbound one, largely outweighed

by the fact that Idle Descent has a saving potential 35kg higher when landing in Lisbon.

26

(a) LIS-OPO (b) OPO-LIS

Figure 4.7: Relative savings in % for the LIS-OPO city-pair.

Finally, the graphic comparison between each measures relative percentage in terms of the total

saving is presented in Figure 4.7. As expected, SETO is the main focus for fuel conservation in the

LIS-OPO route (45%), followed by Idle Descent (33%). For the inbound flight, the preponderance goes

to Idle Descent measures, at 72%, with SETO down to a more reasonable 17%. For both flights, Thrust

Reverser operation and SETI have minimal relative percentages, the first because it is not used very

often, and the second because the procedure is nearly optimized.

27

4.1.2 LIS-BCN & BCN-LIS

Figure 4.8: LIS-BCN route example (from file QAR154)

On a medium-haul route like the connection between Lisbon and Barcelona, the efficiency is ex-

pected to be greater than that seen on the previous shorter routes. Due to the longer flight distances, a

bigger percentage of the time is spent cruising (Figure 4.9), with an expected percentage-wise reduction

of taxi times.

Figure 4.9: LIS-BCN flight profile example (from file QAR154)

In fact it is possible to identify in Figure 4.10 the three main flight phases - Climb, Cruise and Descent

- as the longest, which is to be expected for medium-haul flights. This is also valid for fuel consumption,

28

Figure 4.10: LIS-BCN phase time and fuel consumption

as these three phases represent around 90% of the total fuel consumed for the fight.

Despite this, Taxi Out times are still significant, with over 10% of the time spent on this phase, which

only proves that the Lisbon Airport has a low efficiency when it comes to taxiing, much due to the high

amount of traffic exceeding the airport capacity.

Figure 4.11: BCN-LIS phase time and fuel consumption

The main difference for the inbound flight in this route (Figure 4.11), is the slight reduction in Taxi Out

and Descent relative times, with the corresponding increase in the percentage of time spent cruising,

which usually means a more efficient flight.

29

Variable Route Unit Taxi Out Take Off 2 Segment Initial Climb Climb Cruise Descent Approach Final Landing Taxi In

TimeLIS-BCN

s 703,2 36,4 114 6 1044,7 2368,4 1415,7 216,8 153,7 42 348,4% 10,9 0,6 1,8 0,1 16,2 36,7 22,0 3,4 2,4 0,7 5,4

BCN-LISs 647,4 38,2 130,4 0 1104,1 2847,5 1233,8 177,8 142,1 47,2 361,8% 9,6 0,6 1,9 0,0 16,4 42,3 18,3 2,6 2,1 0,7 5,4

FuelLIS-BCN

kg 104,1 50,6 151,3 7,3 1032,7 1439 421,8 76,2 67,4 8,7 43,2% 3,3 1,6 4,8 0,2 32,5 45,3 13,3 2,4 2,1 0,3 1,4

BCN-LISkg 87,3 53,2 175,7 0 1185,6 1820,7 436 53,5 66,4 10 41,7% 2,5 1,5 5,1 0,0 34,4 52,8 12,6 1,6 1,9 0,3 1,2

Table 4.3: LIS-BCN and BCN-LIS average phase time and fuel consumption

Even though Barcelona airport is much bigger, complex and carries more traffic, Taxi Out times still

average around 50 seconds less than in Lisbon (Table 4.3), which only proves the latter’s lack of capacity

for the current traffic it deals with.

Figure 4.12: LIS-BCN average savings

For these routes, both departing from Lisbon (Figure 4.12) and Barcelona (Figure 4.13), Idle Descent

is clearly the fuel conservation strategy with the highest saving potential. It is to be expected that savings

measures for the three main phases of flight (Climb, Cruise and Descent) become more significant as the

flight distance increases, considering the amount of time spent on these phases is higher, percentage-

wise.

The fact that Idle Descent represents savings of 5.35% (169.97 kg) per outbound flight and only

2.94% (101.54 kg) for inbound ones (Table 4.4) has to do with a multitude of factors, including the ap-

proach procedure for each airport, the bigger experience with the maneuver in Lisbon airport, but more

importantly, because of ATC imposed limitations. Barcelona airspace is very crowded, and because of

that some of its regulations are stricter. Pilots are often encouraged to accelerate the aircraft engines in

order to keep a certain speed, descend faster or above all, avoid holding. Of course, this means longer

periods of time not complying with the idle thrust policy, therefore a fuel saving can be calculated by the

program for a longer period of time, resulting in higher fuel conservation estimates.

Looking at Table 4.4, it is hard to point to any specific measure as the cause for the big difference

of almost double the total savings percentage between the outbound and inbound flight legs. In fact,

almost every fuel conservation strategy potential is halved for flights arriving in Lisbon, which leads to

30

Figure 4.13: BCN-LIS average savings

Route Unit Thrust Reverser APU SETO SETI Idle Descent Total

LIS-BCNkg 0,23 8,84 25,64 4,14 169,97 208,83

Total % 0,01 0,26 0,75 0,12 5,00 6,14Relative % 0,11 4,23 12,28 1,98 81,39 100,00

BCN-LISkg 0,51 9,15 14,64 1,76 101,54 127,60

Total % 0,01 0,23 0,37 0,04 2,58 3,25Relative % 0,40 7,17 11,47 1,38 79,57 100,00

Table 4.4: LIS-BCN and BCN-LIS average savings estimates

think that the whole LIS-BCN route has a lower efficiency when compared to BCN-LIS.

(a) LIS-BCN (b) BCN-LIS

Figure 4.14: Relative savings in % for the LIS-BCN city-pair.

Despite the difference in absolute savings, the savings relative distribution between both flight legs

is relatively similar with around 80% coming from the Idle Descent procedure and 12% from the SETO

maneuver (Figure 4.14).

31

4.1.3 LIS-NCE & NCE-LIS

Figure 4.15: LIS-NCE route example (from file QAR98)

A flight connecting Lisbon and Nice is already considered a long-haul flight for many regional airlines,

even though the Embraer E190 has a range of nearly triple that distance (Appendix C). This makes for

a potentially more efficient flight, since the aircraft spends more time in the conditions it was designed

to operate - cruising - instead of maneuvering, accelerating or taxiing on the ground (Figure 4.16).

Figure 4.16: LIS-NCE flight profile example (from file QAR98)

32

Figure 4.17: LIS-NCE phase time and fuel consumption

For this route, Cruise really stands out as the longest and most fuel consuming phase of the flight

for both legs (Figures 4.17 and 4.18), which is to be expected. Fuel consumption in the three main

phases reaches above 90% of total values, and therefore, the longer the flight, the more important it is

to optimize operations and planning for these flight phases.

Figure 4.18: NCE-LIS phase time and fuel consumption

For the inbound flight, like before, Taxi Out times are reduced by almost 200 s (Table 4.5), and Taxi

In times are close to 40 s longer on average, strengthening the hypothesis that Lisbon airport is over

encumbered, and thus ground operations should be optimized.

33

Variable Route Unit Taxi Out Take Off 2 Segment Initial Climb Climb Cruise Descent Approach Final Landing Taxi In

TimeLIS-NCE

s 775,3 38,5 117,6 5,4 1221,1 4142,1 1331,7 178,8 213,9 37,7 279,6% 9,3 0,5 1,4 0,1 14,6 49,7 16,0 2,1 2,6 0,5 3,4

NCE-LISs 587,8 39 133,4 0 1195 5156,1 1220,9 142 138,6 50,1 322,6% 6,5 0,4 1,5 0,0 13,3 57,4 13,6 1,6 1,5 0,6 3,6

FuelLIS-NCE

kg 109,9 54,8 157,9 6,5 1536,6 2591,1 719,6 66,8 92,6 7,8 37,1% 2,0 1,0 2,9 0,1 28,6 48,2 13,4 1,2 1,7 0,1 0,7

NCE-LISkg 80,4 54,6 179,8 0 1268,8 3069,1 314,5 42,8 59,7 10,5 41,6% 1,6 1,1 3,5 0,0 24,8 59,9 6,1 0,8 1,2 0,2 0,8

Table 4.5: LIS-NCE and NCE-LIS average phase time and fuel consumption

Figure 4.19: LIS-NCE average savings

Concerning the actual savings estimations for each measure, it is possible to identify Idle Descent

as the highest potential procedure for the LIS-NCE flight (Figure 4.19), with close to 3% of the total trip

fuel that could be saved by correct implementation of this measure alone. Thrust reverser operation and

Single Engine Taxi In are fairly optimized, while APU usage and Single Engine Taxi In present potentials

of around 0.25% and 0.5% respectively.

Figure 4.20: NCE-LIS average savings

34

As for the flight leg landing in Lisbon, the distribution of the savings is rather similar (Figure 4.20),

however savings values are significantly lower. The exception seems to be the APU usage, which

presents a potential slightly above 0.2%, which is greater than that of the outbound leg, percentage-

wise.

Route Unit Thrust Reverser APU SETO SETI Idle Descent Total

LIS-NCEkg 0,35 8,80 25,24 3,33 157,39 195,11

Total % 0,01 0,16 0,47 0,06 2,93 3,63Relative % 0,18 4,51 12,94 1,71 80,67 100,00

NCE-LISkg 0,32 12,12 14,32 2,31 56,30 85,38

Total % 0,01 0,24 0,28 0,05 1,10 1,67Relative % 0,37 14,20 16,78 2,71 65,95 100,00

Table 4.6: LIS-NCE and NCE-LIS average savings estimates

In fact, analyzing Table 4.6, Idle Descent absolute savings drop from 157.39 kg when landing in Nice

to 56.30 kg for a landing in Lisbon, almost one third of the value, which is a very significant difference.

This is due to the previously discussed factors associated with this maneuver, aggravated by the fact

that due to noise abatement policies, aircraft cannot overfly the Cap d’Antibes peninsula unless weather

conditions make it absolutely necessary.

(a) LIS-NCE (b) NCE-LIS

Figure 4.21: Relative savings in % for the LIS-NCE city-pair.

On the other hand, the remaining maneuvers potential does not face such a big decline, as SETO

goes down to almost half and Thrust Reverser and SETI savings are relatively constant. APU usage,

however, faces almost 4 kg more savings for the inbound flight, an increase of nearly 50%.

The result is the reduction of Idle Descent supremacy in terms of relative percentage (Figure 4.21),

with a significant increase in APU contribution, as well as a small increment for SETO.

35

4.2 Total Sample Analysis

After studying all the routes one by one, a sample with all the 60 flights was constructed, and the same

type of analysis was put into practice to develop a baseline fuel conservation performance analysis for

the company as a whole, based on the five strategies applied in this work.

Figure 4.22: Total average phase time and fuel consumption

Analyzing all the flights, it is clear that Cruise is the longest and especially most fuel consuming

phase overall, followed by Climb and Descent (Figure 4.22). One special note regarding taxi times,

which reach a total of almost 16% of the total flight time - still a very significant value.

Variable Route Unit Taxi Out Take Off 2 Segment Initial Climb Climb Cruise Descent Approach Final Landing Taxi In

Time Totals 647,7 35,9 120,1 1,9 897,1 2604,4 1114,3 161,9 157,4 45,6 324,0% 10,6 0,6 2,0 0,0 14,7 42,6 18,2 2,6 2,6 0,7 5,3

Fuel Totalkg 91,5 50,1 160,6 2,3 1004,6 1601,4 378,6 50,9 68,3 9,5 40,2% 2,6 1,4 4,6 0,1 29,1 46,3 10,9 1,5 2,0 0,3 1,2

Table 4.7: Total average phase time and fuel consumption

Comparing Table 4.7 with the equivalent table for each route (4.1, 4.3 and 4.5), the similarity between

the total results and the LIS-BCN route strikes immediately. Being the intermediate-length flight, it makes

sense for the results of the three different routes average to fall somewhere in the middle, which explains

the similar flight phase durations and fuel consumption.

36

Figure 4.23: Total average savings

Idle Descent, with a little above 2.5% fuel to be saved (Figure 4.23), is clearly the most significant

saving measure, followed by SETO marginally above 0.5% and APU with about 0.25%. It is interesting

to note that the more a given measure is dependent on ATC coordination, the higher its saving potential,

as illustrated by the dominance of Idle Descent and SETO. This, however, is not a coincidence, and is

actually the main reason why state of the art software and companies (Section 2.1) are trying to attract

the ATC authorities for a transversal effort in the industry towards optimizing fuel conservation.

Route Unit Thrust Reverser APU SETO SETI Idle Descent Total

Totalkg 0,41 9,19 19,86 2,63 93,22 125,31

Total % 0,01 0,27 0,57 0,08 2,70 3,62Relative % 0,32 7,33 15,85 2,10 74,39 100,00

Table 4.8: Total average savings estimates

Regarding the fuel economy estimation through the different measures (Table 4.8), the similarity

seems contained only to the BCN-LIS flight, in terms of both kilograms and percentage. This is due to

the surprisingly high saving potential for the LIS-BCN flight, clearly the highest overall, percentage-wise.

One flight that is even closer to the total average sample value, in terms of the trip fuel to be saved in

percentage, is the LIS-NCE flight, at 3.63%.

Figure 4.24 reveals once again the dominance of the Idle Descent measure over all the others. The

only instance where this is not the case is the LIS-OPO outbound flight leg, in which SETO claims a

higher saving potential (Figure 4.7a)). Overall, this distribution follows the common trend among all the

routes, and allows for defining a priority list among the different measures, with Idle Descent coming

first, SETO and APU usage following relatively close to one another, and SETI and Thrust Reverser

operation with practically negligible contribution.

The fact that most of the implemented operational procedures, with the exception of Idle Descent, are

related to ground operations, allows to predict that the savings potential should decrease, in percentage,

with the increase of flight distance - as the relative time spent in the non-airborne stages of flight should

also decrease. Indeed, this tendency is confirmed by Figure 4.25, where the shortest city-pair links

37

Figure 4.24: Total relative savings

Figure 4.25: Average saving per route in %

present higher values of relative saving than that of the LIS-NCE route overall.

The fact that the LIS-BCN flight presents the highest saving potential, on average, has to do with the

substantial savings for the Idle Descent measure on all outbound flights, but especially on this route.

Looking again at Table 4.9 one can notice the absolute savings from the remaining measures, in kg, are

relatively constant, while the Idle Descent implementation tends to vary significantly from one city-pair

to another, and even between inbound and outbound flight legs for the same city-pair. This difference is

what explains the dominance of the LIS-BCN route, in terms of relative savings, as this route has more

kg of fuel to be saved in Idle Descent than any other.

38

Route Unit Thrust Reverser APU SETO SETI Idle Descent Total

LIS-OPOkg 0,49 10,56 26,57 1,92 19,55 59,09

Total % 0,03 0,74 1,87 0,14 1,38 4,16

OPO-LISkg 0,54 5,66 12,76 2,33 54,55 75,85

Total % 0,04 0,38 0,85 0,16 3,65 5,08

LIS-BCNkg 0,23 8,84 25,64 4,14 169,97 208,83

Total % 0,01 0,26 0,75 0,12 5,00 6,14

BCN-LISkg 0,51 9,15 14,64 1,76 101,54 127,60

Total % 0,01 0,23 0,37 0,04 2,58 3,25

LIS-NCEkg 0,35 8,80 25,24 3,33 157,39 195,11

Total % 0,01 0,16 0,47 0,06 2,93 3,63

NCE-LISkg 0,32 12,12 14,32 2,31 56,30 85,38

Total % 0,01 0,24 0,28 0,05 1,10 1,67

Totalkg 0,41 9,19 19,86 2,63 93,22 125,31

Total % 0,01 0,27 0,57 0,08 2,70 3,62

Table 4.9: Total average savings estimates aggregate

Figure 4.26: Average saving per route in kg

In terms of absolute savings, it is expected that the longer the flight distance is, the bigger its saving

potential, however this is not quite the case, as depicted in Figure 4.26. While the LIS-OPO route

presents the lowest saving potential in kg, as expected, flights departing to and from Barcelona outweigh

those that fly to Nice. Looking at Table 4.9 and comparing savings potentials for outbound and inbound

flights seem in line with each other, with the exception of Idle Descent. This proves the Idle Descent

maneuver has a big margin for improvement when it comes to the Barcelona flights, and while it is fairly

straightforward to explain why the OPO-LIS has a smaller saving potential for Idle Descent than the other

two inbound flights (due to lower cruising altitudes and therefore shorter descents), it is not quite clear

why flights landing in Lisbon coming from Barcelona and Nice have so distinct values, as both flights

cruise altitudes and even approach procedures are fairly similar.

39

Figure 4.27: Average saving for Outbound and Inbound flights (LIS)

Grouping all of the relative savings results into outbound and inbound flights (Figure 4.27), it is even

more apparent the under-optimization of all flights leaving Lisbon International Airport, and this is mainly

due to two reasons:

• Higher Single Engine Taxi Out average savings potential for all outbound flights, compared to

inbound flights for the same route, which proves Lisbon Airport difficulty to deal with the increasing

amounts of air traffic it receives, and therefore its lower ground efficiency;

• Higher Idle Descent average savings potential, especially in Barcelona and Nice, much due to

higher air and ground traffic, therefore stricter ATC requirements and regulations, as well as less

fuel efficient approach procedures, with the growing number of paths designed for noise abatement

in large cities.

The complete results in terms of kg of potential fuel savings for each of the analyzed flights is avail-

able in Appendix B.

40

4.3 Savings Estimation

Perhaps as important as calculating how many kg of fuel could be saved via the implementation of the

measures described in this work, is estimating how that translates into yearly savings, in financial terms.

Total

Distance (NM) 32 845Duration (s) 366 606

Fuel Burned (kg) 207 479Saving Potential (kg) 7 518

Average

Distance (NM) 547Duration (s) 6 110

Fuel Burned (kg) 3 458Saving Potential (kg) 125

Average Saving Potential (%) 3,62

Table 4.10: Final savings estimates results

Comparing Table 4.10 with the typical operational profile described by Embraer and presented in

Section 1.2.1 (Table 1.3), it is possible to see that in fact the estimates are not too far from reality,

regarding average Distance (547 NM vs. 600 NM), Duration (6110 s vs. 5400 s) and Fuel Burned (3458

kg vs. 3147 kg). Of course these estimates would represent the company operation better the more

flights and routes would be analyzed, and possibly come even closer to Embraer estimates since the

LIS-OPO route, for example, is less flown than the others and represents a much higher fuel to distance

ratio.

For a 1% savings estimation, according to the results obtained from the sample, there would be

0.01 × 3458 = 34.5kg of fuel saved per flight, which using Embraer estimates for a 600 NM flight would

result in approximately 591 metric tons of fuel saved per year for PGA fleet. In turn, this represents

around 591×446.6 = 263 941$, nearly 235ke, in yearly savings, which is fairly close to Embraer estimate

of 212ke.

However, for PGA case, applying just these five simple operational procedures an average total

saving of 3.62% was obtained. This means an average saving of 125 kg of fuel per flight, which for

a typical operational profile of 600 NM, according to Embraer, results in about 2141 metric tons yearly

savings in fuel. Considering the average curent price of jet fuel in Europe of 446.6 $/mt, this means

savings of 956k$, or 850ke per year.

Nearly one million euros in savings if the full potential of these five savings measures was attained

through its correct implementation is a very notable result, and certainly very significant for any airliner.

To note that this result is proportional to fleet size, and as PGA fleet is expected to grow over the years,

this savings value will also increase with it.

41

4.3.1 Additional Savings

If the full potential of these measures could be achieved under all operating conditions, then PGA would

be transporting 3.65% of unused extra fuel on each flight, equivalent to 125kg. In turn, this would

increase takeoff and landing weight, leading to trip fuel increase and even premature wear of the landing

gear, brakes and tires, increasing maintenance costs as well.

This means that if these measures could be reflected in flight planning, reducing the amount of fuel

that is uplifted to the aircraft without compromising safety, an additional fuel saving could be attained.

Figure 4.28: Expected fuel burn increase adding 200kg of extra fuel [4]

According to Embraer, for each 200kg of extra fuel uplifted to the aircraft, the trip fuel increase

changes depending on the trip distance as shown in Figure 4.28. Even though PGA E-190 is the least

influenced by extra weight when compared to the rest of the E-Jets family, it still presents some important

potential.

According to the estimations on this work, the average distance a PGA flight covers is 547NM, and

we can see according to the graph that would translate into approximately 0.25% of additional fuel saved,

if 200kg of extra fuel was not uplifted. However, the average fuel saving calculated is 125kg per flight,

so the only conclusion possible is that the real saving value would be somewhere below this number, as

there is no information about its variation with the weight.

If we assume, for the sake of this estimation, that the saving increases with the weight somewhat

linearly, then we can project an additional saving of about half that presented in the graph, as the weight

is reduced from 200kg to 125kg. This would result in a saving estimation of about 0.125%, or 4kg per

flight, which translates into 68 metric tons yearly, equivalent to an additional 27ke saved. This brings

the total saving estimate to an impressive 877ke.

42

Chapter 5

Conclusions

This project studied the impact that could be expected from the implementation of fuel efficient operating

measures on PGA new Embraer 190 fleet.

5.1 Achievements

The results obtained in this work are very encouraging, as they show that even with simple day-to-day

measures, big airlines can save a significant amount of fuel, and therefore, money.

However, the full savings potential obtained for this work is not attainable without the cooperation and

consequent optimization of local ATC itself. These results are important for airlines - in this case PGA in

particular - to show the local ATC the impact their operational procedures can have, as away to sensitize

them to this issue and count on their support.

5.2 Future Work

The next step in terms of airline optimization is applying the same philosophy to both flight planning - e.g.,

climb profile, cruise speed, CG position, etc. - and maintenance procedures optimization - evaluating

engine derate and planning engine washes, for example.

Another potentially significant step would be estimating and applying optimized Cost Index values for

the different most flown routes. Cost Index represents a ratio between the unit cost of time and the unit

cost of fuel, and is introduced into de FMS to optimize the aircraft speed for a given flight.

Also important would be to gather the pilots’ feedback regarding the implementation of the operational

measures described in this work, in order to assess its feasibility, ease of application and eventual

limitations. This would also sensitize the pilots to the potential overall saving that can come from their

direct actions, and thus help with the transverse effort that is required within the company to achieve

such goals. Unfortunately, such feedback was not possible to gather during this work duration, much

due to the constant training and flying the pilots were attending because of the new fleet.

43

44

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45

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46

Appendix A

Economic Scenario Data

A.1 IATA - Economic Performance of the Airline Industry [3]

A.1

www.iata.org/economics │ 2016 Mid-year report 1

ECONOMIC PERFORMANCE OF THE AIRLINE INDUSTRY

Industry Forecast - June 2016

Worldwide airline Industry 2014 2015F 2016F 2013 2012 2010 2011 2004 2007 2008 2009 2005 2006

REVENUES, $ billion 751 718 709 720 706 564 642 379 510 570 476 413 465

% change 4.3 -4.4 -1.3 2.1 9.8 18.4 14.0 17.7 9.6 11.7 -16.5 9.1 12.6

Passenger, $ billion 539 518 511 539 531 445 512 294 399 444 374 323 365

Cargo, $ billion 62.5 52.8 49.6 60.7 63.5 66.1 66.9 46.6 58.8 62.6 48.4 47.9 53.2

Traffic volumes

Passenger growth, rpk, % 5.7 7.4 6.2 5.2 5.3 8.0 6.3 14.8 7.9 2.4 -1.2 8.9 6.9

Sched passenger numbers, millions 3,328 3,568 3,783 3,152 2,999 2,700 2,864 1,997 2,456 2,493 2,483 2,139 2,258

Cargo growth, ftk+mtk, % 5.0 2.3 2.1 0.6 -0.9 19.4 0.4 11.6 4.7 -0.7 -8.8 2.3 6.3

Freight tonnes, millions 51.5 52.2 53.2 49.5 48.8 49.1 49.3 39.8 45.4 45.1 41.1 40.8 43.4

World economic growth, % 2.6 2.4 2.3 2.5 2.4 4.1 2.9 4.0 4.0 1.5 -2.0 3.5 4.0

Passenger yield, % -5.5 -10.7 -7.0 -3.9 -1.4 9.5 7.5 2.8 1.7 8.3 -13.7 1.0 6.6

Cargo yield % 3.9 0.5 4.4 5.6 7.0 -15.2 14.4 0.8 -4.2 -4.9 -2.0 -17.4 -8.0

EXPENSES, $ billion 376 409 450 490 571 474 536 623 687 695 716 659 647

% change 16.2 8.9 10.1 8.8 16.5 -16.9 13.1 16.2 10.4 1.1 3.1 -8.0 -1.9

Fuel, $ billion 65 91 127 146 204 134 152 191 228 230 226 181 127

% of expenses 17.3 22.2 28.4 29.8 35.7 28.3 28.3 30.8 33.1 33.1 31.6 27.5 19.7

Crude oil price, Brent, $/b 38.3 54.5 65.1 73.0 99.0 62.0 79.4 111.2 111.8 108.8 99.9 53.9 45.0

Jet kerosene price, $/b 49.7 71.0 81.9 90.0 126.7 71.1 91.4 127.5 129.6 124.5 114.8 66.7 55.4

Fuel consumption, billion gallons 66 68 69 71 70 66 70 72 73 74 78 82 86

CO2 emissions, million tonnes 628 651 658 675 669 634 665 685 693 709 739 781 817

Non-fuel, $ billion 311 318 324 344 367 340 384 431 460 465 490 478 519

cents per atk (non-fuel unit cost) 39.1 37.7 36.6 36.5 37.9 36.6 40.0 42.3 43.8 42.7 42.7 39.2 40.1

% change 1.0 -3.4 -3.0 -0.3 3.9 -3.4 9.1 5.8 3.5 -2.5 0.1 -8.3 2.2

Capacity growth, atk, % 10.1 6.1 4.8 6.6 2.7 -4.2 3.7 6.0 3.0 3.7 5.4 6.3 6.3

Flights, million 23.8 24.9 25.5 26.7 26.5 25.9 27.8 30.1 31.2 32.0 33.0 34.8 36.8

Break-even weight load factor, % 63.9 61.3 60.4 64.5 64.7 63.5 64.1 60.9 60.3 62.2 61.8 61.2 60.7

Weight load factor achieved, % 67.0 66.9 66.2 66.8 66.4 66.8 66.1 61.5 62.7 62.1 62.0 61.8 62.7

Passenger load factor achieved, % 79.9 80.4 80.0 79.7 79.4 78.7 78.5 73.6 77.1 76.1 76.2 75.0 76.1

OPERATING PROFIT, $ billion 3.3 4.4 15.0 19.9 -1.1 1.9 27.6 19.8 18.4 25.3 35.1 59.5 62.2

% margin 0.9 1.1 3.2 3.9 -0.2 0.4 4.9 3.1 2.6 3.5 4.7 8.3 8.8

NET PROFIT, $ billion -5.6 -4.1 5.0 14.7 -26.1 -4.6 17.3 8.3 9.2 10.7 13.7 35.3 39.4

% margin -1.5 -1.0 1.1 2.9 -4.6 -1.0 3.1 1.3 1.3 1.5 1.8 4.9 5.6

per departing passenger, $ -2.8 -1.9 2.2 6.0 -10.5 -1.9 6.4 2.9 3.1 3.4 4.1 9.9 10.4

RETURN ON INVESTED CAPITAL, % 5.9 9.3 9.8 4.8 4.6 6.2 4.7 3.3 5.7 1.3 1.9 3.3 4.7

Data sources: Historic data to 2014 from ICAO, except fuel detail and global passenger and freight. IATA forecasts 2016 and estimates for some 2014 & 2015 items. IATA Economic Industry Performance. IATA Economic Industry Performance (IATA Economics)

Note: Bankruptcy reorganization and large non-cash costs are excluded.

Updated: June 2016. Next update December 2016

A.2

www.iata.org/economics │2016 Mid-year report 2

Financial Results

Data sources: Global data to 2014 and regional data to 2010 from ICAO. IATA Economics estimates for regions in 2011-15 and forecasts 2016 figures. .

Note: Bankruptcy reorganization and large non-cash costs are excluded.

Traffic Results

System-wide global commercial airlines Passenger traffic (RPK) % change over year Passenger capacity (ASK) % change over year

2010 2011 2012 2013 2014 2016F 2010 2011 2012 2013 2014 2016F 2015 2015

Global 8.0 6.3 5.3 5.2 5.7 6.2 4.6 6.6 4.0 4.8 5.5 6.8 7.4 6.7

Regions

North America 4.5 2.9 1.0 2.3 2.7 4.0 2.3 2.8 0.0 2.0 2.5 4.3 5.3 5.0

Europe 4.3 8.4 4.6 3.9 5.7 4.9 1.7 8.9 2.6 2.7 5.1 5.8 6.0 4.8

Asia-Pacific 11.8 6.6 6.1 7.2 6.9 8.5 6.3 7.0 5.3 7.1 7.4 9.1 10.1 8.4

Middle East 17.6 10.0 14.7 11.6 12.1 11.2 13.3 9.8 12.0 12.3 10.9 12.2 10.4 12.9

Latin America 12.4 11.3 9.4 6.3 7.0 4.2 6.8 9.3 7.3 4.5 4.7 3.7 7.6 6.9

Africa 12.3 1.6 7.5 4.6 0.3 4.5 9.3 3.2 6.3 4.0 2.5 5.3 0.0 -0.2

Data sources: Historical data to 2015 from IATA Statistics. IATA Economics forecasts for 2016. Note: Includes domestic and international traffic.

System-wide global commercial airlines Net Profit, $ billion 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015E 2016F

Global -7.5 -5.6 -4.1 5 14.7 -26.1 -4.6 17.3 8.3 9.2 10.7 13.7 35.3 39.4

Regions

North America -3.4 -10 -6.7 1 5.5 -19.7 -2.7 4.2 1.7 2.3 7.4 11.2 21.5 22.9

Europe -1.5 1.1 1.6 2.4 6.4 0 -4.3 1.9 0.3 0.4 1.0 1.0 7.4 7.5

Asia-Pacific -0.7 3.4 1.2 1.7 3 -4.7 2.7 9.2 5.0 5.8 2.3 1.8 7.2 7.8

Middle East -0.1 0.2 0.2 -0.1 -0.1 -0.3 -0.6 0.9 1.0 1.0 0.3 0.4 1.4 1.6

Latin America -1 0.1 -0.1 0.1 0.1 -1.4 0.5 1.0 0.2 -0.2 0.2 0.0 -1.5 0.1

Africa -0.8 -0.3 -0.4 -0.2 -0.2 -0.1 -0.1 0.1 0.0 -0.1 -0.5 -0.8 -0.7 -0.5

System-wide global commercial airlines EBIT margin, % revenues EBIT (actual values),$ billion

2010 2011 2012 2013 2014 2016F 2010 2011 2012 2013 2014 2016F 2015E

2015E

Global 4.9 3.1 2.6 3.5 4.7 8.8 27.6 20.8 19.9 25.3 35.1 62.2 8.3 59.5

Regions

North America 5.7 3.0 3.4 6.8 11.1 15.4 10.6 5.9 7.0 14.3 24.4 32.4 14.7 32.1

Europe 2.4 0.8 0.7 2.0 2.0 5.6 3.9 1.5 1.4 4.0 4.3 10.5 5.3 10.4

Asia-Pacific 8.0 6.6 4.7 2.9 2.5 8.4 10.3 11.5 9.6 5.8 5.3 16.9 7.7 15.3

Middle East 3.7 3.1 3.0 0.9 1.2 2.8 1.3 1.3 1.4 0.5 0.7 1.8 2.5 1.5

Latin America 5.1 2.0 1.5 2.2 2.1 2.6 1.3 0.6 0.5 0.7 0.7 0.8 1.9 0.6

Africa 1.7 0.6 -0.4 -0.5 -2.1 -1.1 0.2 0.1 -0.1 -0.1 -0.3 -0.2 -2.5 -0.3

A.3

A.4

Appendix B

Simulation Results

B.1

Route File Name Thrust Rev. APU SETO SETI Idle Descent

LIS-OPO

’QAR 1708’ 0,00 23,75 26,93 1,95 14,28’QAR 1767’ 0,41 16,28 75,69 2,07 12,47’QAR 1773’ 0,36 8,22 19,58 0,50 16,56’QAR 1799’ 0,56 1,26 52,98 5,42 7,72’QAR 183’ 0,05 2,14 9,62 1,27 47,58

’QAR 1920’ 0,43 11,90 12,55 1,69 5,75’QAR 1949’ 1,01 17,44 8,35 0,98 16,49’QAR 360’ 0,00 4,98 11,88 1,50 22,80’QAR 66’ 2,09 17,09 34,53 1,08 10,13’QAR 757’ 0,00 2,52 13,55 2,71 41,77

OPO-LIS

’QAR 361’ 0,00 2,86 14,84 1,87 179,10’QAR 457’ 0,16 3,40 8,42 0,97 53,94’QAR 472’ 0,00 2,65 13,37 2,23 53,27’QAR 505’ 0,00 1,39 2,98 1,30 55,52’QAR 526’ 0,30 5,82 9,51 3,73 90,13’QAR 547’ 0,00 3,43 8,78 1,34 10,17’QAR 553’ 0,85 5,78 15,65 7,81 22,85’QAR 597’ 3,42 2,54 15,56 1,06 19,57’QAR 614’ 0,70 13,30 26,08 1,25 48,24’QAR 630’ 0,00 15,45 12,44 1,75 12,71

LIS-BCN

’QAR 100’ 0,05 1,18 5,30 2,23 161,78’QAR 1005’ 0,49 6,18 37,10 4,20 243,97’QAR 1068’ 0,10 13,82 6,15 8,23 128,98’QAR 1080’ 0,37 19,71 30,72 9,98 185,78’QAR 154’ 0,54 16,71 52,72 1,63 131,73’QAR 253’ 0,16 1,57 8,93 2,10 233,07’QAR 368’ 0,11 1,88 21,63 1,60 256,12’QAR 40’ 0,00 11,96 24,11 4,99 158,52’QAR 820’ 0,28 3,03 57,27 3,74 75,58’QAR 978’ 0,23 12,38 12,48 2,73 124,16

BCN-LIS

’QAR 1006’ 0,54 1,30 10,89 1,96 56,32’QAR 101’ 0,45 1,95 6,42 0,10 145,22’QAR 155’ 1,49 18,26 10,02 0,78 74,38’QAR 202’ 0,80 16,07 6,95 1,30 224,53’QAR 254’ 0,14 2,12 9,41 1,58 56,56’QAR 369’ 0,37 1,15 8,68 1,43 110,32’QAR 412’ 0,59 14,66 22,72 3,25 27,56’QAR 561’ 0,00 8,62 46,65 4,89 78,23’QAR 821’ 0,53 12,84 7,38 1,10 199,51’QAR 979’ 0,17 14,54 17,29 1,21 42,74

LIS-NCE

’QAR 1066’ 0,00 4,04 21,92 1,45 137,84’QAR 1078’ 0,54 24,46 20,13 1,69 186,96’QAR 120’ 0,66 1,87 8,20 5,68 136,46’QAR 527’ 0,00 2,77 31,25 1,37 234,35’QAR 535’ 0,97 1,40 26,80 1,71 87,45’QAR 55’ 0,43 13,69 21,11 1,33 62,07’QAR 70’ 0,05 5,69 33,11 6,93 200,51’QAR 72’ 0,00 3,38 52,47 1,88 363,19’QAR 818’ 0,48 20,98 18,68 8,35 96,36’QAR 98’ 0,34 9,68 18,75 2,92 68,72

NCE-LIS

’QAR 1067’ 0,00 1,30 21,33 6,77 4,53’QAR 1077’ 0,00 20,40 6,94 3,15 9,21’QAR 1180’ 0,00 13,38 14,89 1,54 45,70’QAR 121’ 0,09 13,79 10,42 3,55 47,24’QAR 260’ 0,00 12,57 13,30 1,34 179,18’QAR 528’ 0,00 1,26 10,18 1,08 41,14’QAR 536’ 1,50 16,04 8,44 0,72 20,82’QAR 56’ 0,41 11,33 16,75 1,26 112,19’QAR 819’ 1,18 28,26 25,92 1,04 65,90’QAR 88’ 0,00 2,87 15,05 2,66 37,12

Table B.1: Savings, in kg, for all the files run through the simulation

B.2

Appendix C

Technical Datasheets

C.1 Embraer 190 Weights and Dimensions Datasheet [19]

C.1

www.embraercommercialaviation.com

Weights June 2014

C.2

June 2014 www.embraercommercialaviation.com

(*) Fuel density: 0.803 kg/l (6.70 lb/gal)

STD LR AR

MRW kg 47,950 50,460 51,960

(lb) (105,712) (111,245) (114,552)

MTOW kg 47,790 50,300 51,800

(lb) (105,359) (110,893) (114,199)

MLW kg 43,000 44,000

(lb) (94,799) (97,003)

BOW (std) kg 27,737 27,837

(lb) (61,149) (61,370)

MZFW kg 40,800 40,900

(lb) (89,949) (90,169)

M. Payload kg 13,063

(lb) (28,800)

Max. Usable Fuel * kg 12,971

(lb) (28,596)

Max. Usable Fuel L 16,153

(gal) (4,267)

EMBRAER 190 | Design weights

C.3

June 2014 www.embraercommercialaviation.com

28.72 m (94 ft 3 in)

36.24 m (118 ft 11 in)

10.57 m (34 ft 8 in)

12.08 m (39 ft 8 in)

EMBRAER 190 Views Front and side

C.4

C.2 Embraer 190 Performance Datasheet [20]

C.5

www.embraercommercialaviation.com

Performance June 2014

C.6

June 2014 www.embraercommercialaviation.com

Notes: (*) Single-class seating at 32” pitch; Passengers at 100 kg (220 lb)

STD LR AR

Range Full PAX*, LRC, typical mission reserves

nm (km)

1,850 2,400 2,450

(3,426) (4,445) (4,537) Takeoff field length MTOW, ISA, SL - E5 engines for STD & LR; E5A1 engines for AR version

m 1,598 1,830 2,100

(ft) (5,243) (6,004) (6,890)

Landing field length MLW, ISA, SL

m (ft)

1,226 (4,022)

1,244 (4,081)

Takeoff field length TOW for 500nm, full PAX*, ISA, SL, E5 engines

m 1,267

(ft) (4,157)

Time to climb to FL350 TOW for 500 nm, full PAX*

min 16

Max. operating speed Mach 0.82

Service ceiling (ft) 41,000

EMBRAER 190 Performance Characteristics

C.7

June 2014 www.embraercommercialaviation.com

Cruise at M 0.78; typical mission reserves, 100 nm alternate

EMBRAER 190 Payload range

AR

98 pax @ 100 kg

114 pax @ 100 kg

0

5,000

10,000

15,000

20,000

25,000

30,000

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

0 500 1,000 1,500 2,000 2,500 3,000 3,500

PA

YL

OA

D [

lb]

PA

YL

OA

D [

kg

]

RANGE [nm]

C.8