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The Technical University of Munich has developed an electrical vehicle in the framework of VisioM. The Institute of Lightweight Structures has contributed to the layout process of the vehicle’s structure by performing optimization in consecutive stages of development. Topology optimization was applied at an early design phase to identify an advantageous geometry for the structure. For creating a safe and efficient vehicle, the performance of its structure is vital, as it has to withstand the loads while being lightweight. Hence, several load cases had to be considered in the optimization. Nonlinear Simulation of the crash behavior raises the computational costs in an unacceptable way. Therefore, quasi static loads via inertia relief analyses were used. In addition chassis loads as well as torsional and bending stiffness were considered. The results showed regions of plane geometry and regions of bar structures. This contributed to the decision of creating a hybrid construction, of a carbon fiber laminate moncoque combined with an aluminum space frame for the front, rear and roof of the vehicle. In this second phase the idea was to improve the monocoque by insertion of stiffeners. Again topology optimization was used to identify promising locations for fortifications. Based on the results the stiffeners were modeled as shell structure and a size optimization was performed, to define a manufacturable geometry. To obtain a reliable result for the design of the monocoque, it was important to include the orthotropic material properties of the laminate. Based on the monocoque a shell structure was modeled and sequentially several unidirectional patches were defined. Due to manufacturing constraints the monocoque was modeled as a symmetric fabric that was enforced by the patches. In this way a weight optimal design was found, that fulfilled the failure criterion under the given loads. Using optimization in the development of the structure has the advantage, to be able to better judge and understand the performance of the design, as one is always seeking the frontiers of the design instead of developing a structure that only satisfies the specifications. In this way challenges can be revealed earlier in the design process. Finding an optimal design is much more meaningful than just finding a better or satisfying design.
Citation preview
Technische Universität München
Lehrstuhl für Leichtbau (LLB)
Institute of Lightweight Structures
Multistage Structural Optimization in the
Design of the Lightweight Electrical
Vehicle VisioM
Dipl.-Ing. Bernhard Sauerer, Dipl.-Ing. Markus Schatz, Erich Wehrle M.Sc.,
Prof. Horst Baier
26.06.2014
Technische Universität München
Folie 2 Lehrstuhl für Leichtbau (LLB)
Institute of Lightweight Structures
Outline of the presentation
1. Design of the structure of the electrical vehicle VisioM
– Goals of the design process
– Load cases, that were considered
– Geometry/ design space
2. Topology optimization of the complete car structure
– Identifying loadpaths
– Results and interpretation
3. Sizing of the CFRP monocoque
– Definition of reinforcing patches
– Sizing of the patches
4. Conclusion
Technische Universität München
Folie 3 Lehrstuhl für Leichtbau (LLB)
Institute of Lightweight Structures
Design Task Goal:
• Determination of an weight optimal structure,
satisfying the constraints
• Identification of favorable structure
• Improving the existing design
Modeling:
Design space:
• Consideration of package (battery, motor,...)
• Outer surface from Mute (predecessor)
• Volume between the crashsystems
• Discretization with 1.5x106 solid elements
Load cases:
• Stiffness (Bending, Torsion)
• Chassis loads
• Crash loads quasistatic with inertia relief
Project of the TUM
Working together with:
• BMW
• IAV
• Several TUM Institutes
Technische Universität München
Folie 4 Lehrstuhl für Leichtbau (LLB)
Institute of Lightweight Structures
𝜎 ≤ 𝜎𝑚𝑎𝑥
∆𝑥 ≤ 𝑥𝑚𝑎𝑥
Crash: Quasistatic loads
Chasis loads
Stiffness Load Cases and Constraints
• Crash loads (4):
– Front, rear, sidecrash using
inertia relief
– Quasi static modeling of the
transient crash behavior
• Stiffness load cases (2):
– Bending and Torsional Stiffnes
– Stiffness was demanded to be
higher than in the preceeding
design
• Chassis loads (3):
– Breaking
– Maximum acceleration
– Curve combined with a bump
• Stress constraint
• Minimal member size
• 1-plane symmetry
Technische Universität München
Folie 5 Lehrstuhl für Leichtbau (LLB)
Institute of Lightweight Structures
Topology Optimization Results for the Structure
Shell geometry Truss structure
Result: Density distribution in the design space shows important load paths
Defining a density threshold
A monocoque is a favorable
choice under the given loads!
Technische Universität München
Folie 6 Lehrstuhl für Leichtbau (LLB)
Institute of Lightweight Structures
Optimization of the Monocoque
• Monocoque: shell structure
• Several optimization steps were performed
1. Topology opt.: Identifying locations for
reinforcements
2. Sizing of shell elements: Dimensions of patches
3. Sizing of fiber patches: CFRP design
Technische Universität München
Folie 7 Lehrstuhl für Leichtbau (LLB)
Institute of Lightweight Structures
Optimizing the Monocoque
1. Identifying heavily stressed regions (Free Size)
– Free sizing with isotropic material (vonMises)
– Defining patches to reinforce the areas
2. Sizing optimization of ply thickness
– Global basic material woven CFRP
– Additional unidirectional patches
– 3 crash load cases (Inertia relief)
– Constraint: Tsai-Wu failure criteria
– Use of global search option (GSO)
Unidirectional fiber patches
Technische Universität München
Folie 8 Lehrstuhl für Leichtbau (LLB)
Institute of Lightweight Structures
Sizing Optimization of the Fiber Monocoque
Result: Patch thicknesses
Strength evaluation via Tsai-Wu failure index
Critical areas
Force application areas
Mass: 61,8 kg
(Improvement 20 kg)
Local stress
concentrations
determine the
design
• Woven thickness at
lower bound
• Local unidirectional
patches upt to 11.6 mm
Technische Universität München
Folie 9 Lehrstuhl für Leichtbau (LLB)
Institute of Lightweight Structures
Specific challenges
1. High computational cost of topology opt.
Iterations: ~120 using 16 CPU (2.9 GHz) -> ~30 hours
2. Loading due to passenger mass in different
load cases
3. Finding appropriate constraining mass
4. High sensitivity of the topology to changes of:
– Boundary conditions and forces
– Mass constraint
m<120 kg m<150 kg
Technische Universität München
Folie 10 Lehrstuhl für Leichtbau (LLB)
Institute of Lightweight Structures
Conclusion
• The design process was accompanied by a series of different
optimizations, in OptiStruct
• Different optimization goals:
– identifying loadpathes/ locations for reinforcements
– increasing the stiffness
– reducing mass
• Optimization provides a learning process about the performance of
the structure, that one would not get from a pure analysis.
• The mass of the monocoque was drastically reduced!
• The additional effort for defining the optimization is justifiable
Technische Universität München
Lehrstuhl für Leichtbau (LLB)
Institute of Lightweight Structures
Thank you for your attention