Design optimization of multi-link suspension system for total vehicle handling and stability
Kikuo Fujita, Noriyasu HIROKAWA, Shinsuke Akagi, Takanori Hirata
Abstract
Kikuo Fujita, Noriyasu HIROKAWA, Shinsuke Akagi, Takanori Hirata
Abstract
This paper discusses the design problem of vehicles using multi-link suspension system with the aim of totally optimizing vehicle handling and stability. Since this problem includes many evaluation items, and multi-link suspension system has interconnected behavior, the optimization is so complicated. An efficient and computable model is indispensable for compromising the total optimization. This paper investigates a hierarchical structure of objectives, introduces appropriate simulation models for respective items, and formulates a mathematical optimization model based on them. Further, we apply a genetic algorithm based optimization method to this problem. The genetic algorithm is based on Simple GA and introduces several extensions such as fitness function for constrained multi-objective optimization problems, similarity-based selection, direct crossover within side constraints, etc. The result of optimization calculation shows the validity of the optimization model and the optimization algorithm as mathematical computation based design methods. 1
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This paper discusses the design problem of vehicles using multi-link suspension system with the aim of totally optimizing vehicle handling and stability. Since this problem includes many evaluation items, and multi-link suspension system has interconnected behavior, the optimization is so complicated. An efficient and computable model is indispensable for compromising the total optimization. This paper investigates a hierarchical structure of objectives, introduces appropriate simulation models for respective items, and formulates a mathematical optimization model based on them. Further, we apply a genetic algorithm based optimization method to this problem. The genetic algorithm is based on Simple GA and introduces several extensions such as fitness function for constrained multi-objective optimization problems, similarity-based selection, direct crossover within side constraints, etc. The result of optimization calculation shows the validity of the optimization model and the optimization algorithm as mathematical computation based design methods. 1
Key concepts: Link (geometry), Stability (learning theory), Suspension (topology), Computer science, Automotive engineering, Engineering, Computer network, Mathematics