Development of a Multidisciplinary Design Optimization Process for Automotive Components: Metamodel-Based Optimization of a Center Stack Display Bracket

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The design of automotive components requires balancing requirements from mul tiple engineering disciplines to arrive at a satisfactory design in increasingly short development cycles. Multidisciplinary Design Optimization (MDO) can facilitate learning and discovery of high-performing designs with conflicting requirements in a time-efficient manner. This thesis presents an MDO process for interior structural components subject to crash and noise, vibration, and harshness (NVH) requirements. Internal needs at Volvo Car Corporation for such a method are identified using semi-structured interviews. Relying on previous findings in the field of metamodel-based MDO, a sizing optimization workflow is developed in the software modeFRONTIER using a simple geometry subject to a head impact load case and a modal requirement. The presented process involves variable selection by parameterization and statisti cal variable screening, sampling using an experimental Uniform Latin Hypercube design, metamodeling with multiple metamodel algorithms, and subsequent global, nongradient optimization with the genetic algorithm MOGA-II. The MDO process is applied to a Center Stack Display bracket design problem subject to three head impact load cases and an NVH-related modal requirement. Significant performance increases for critical objectives are shown compared to a pre-optimized design; however, the optimization does not reach all performance tar gets, thus prompting a discussion about process limitations, including the need for global information and implications of geometry lock-in. Organizational, societal, ethical, and ecological aspects related to MDO in the automotive industry are briefly considered. Finally, recommendations regarding future work are given, including the implementation of finite element mesh morphing to allow for more complex design variables and method improvements for variable screening.

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Multidisciplinary Design Optimization, Variable Screening, Metamodel-Based Optimization, Design of Experiments, Latin Hypercube Sampling

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