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International Journal of Automotive Technology > Volume 23(4); 2022 > Article
International Journal of Automotive Technology 2022;23(4): 957-965.
doi: https://doi.org/10.1007/s12239-022-0083-1
Przemysław Sebastjan , Wacław Kuś
Department for Computational Mechanics and Engineering RMT4, Silesian University of Technology
PDF Links Corresponding Author.  Wacław Kuś  , Email. WKus@polsl.pl
Work presented in this article concerns an industrial example of a mass optimization problem, performed on automotive suspension components. Due to the fact, that the considered element, i.e. spring seat is a part of the vehicle suspension module, analyses are performed on the shock absorber assembly level with the mutual interaction of each body. To solve constrained optimization task, a combination of genetic and gradient-based algorithms are used, involving nonlinear static strength problem, represented by finite element method analysis. Parametric representation of considered component geometry is used, incorporating manufacturing restrictions and design assembly requirements. The final, optimized form of the spring seat is then compared with its initial shape, i.e. “working space”, especially under constraints fulfillment, which are specified by the customer. Performance comparison of used methods (or combination of such) is the aim of this paper, focusing on practical aspects of work, i.e. final mass decrease, number of function calls, or design space exploration capabilities. The optimization method presented hereby is universal and can be adapted to many fields of industry, wherever efficient mass reduction must be achieved incorporating the feasibility of the component. The hybrid optimization approach presented in the paper allows effective mass reduction and works well for multimodal objective functions typically found in industrial applications.
Key Words: Shape optimization, Hybrid optimization, Genetic algorithms, Finite element method, Automotive suspension, Non-linear optimization
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