Abstract
This paper presents an application of multi-objective optimisation for the design of an important component of automobiles, namely the suspension system. In particular, we focus on the double wishbone suspension, which is one of the most popular suspensions in use today and is commonly found on mid-range to high-end cars. The design of such mechanical systems is fairly complicated due to the large number of design variables involved, complicated kinematic model, and most importantly, multiplicity of design objectives, which show conflict quite often.
The above characteristic of the design problem make it ideally suited for a study in optimisation using non-classical techniques for multi-objective optimisation. In this paper, we use +NSGA-II+ [5] for searching an optimal solution to the design problem. We focus on two important performance parameters, namely camber and toe, and propose objective functions which try to minimise the variation of these as the wheel travels in jounce and rebound. The pareto-optimal front between these two objectives are obtained using multiple formulations and their results are compared.
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Arikere, A., Saravana Kumar, G., Bandyopadhyay, S. (2010). Optimisation of Double Wishbone Suspension System Using Multi-Objective Genetic Algorithm. In: Deb, K., et al. Simulated Evolution and Learning. SEAL 2010. Lecture Notes in Computer Science, vol 6457. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17298-4_48
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DOI: https://doi.org/10.1007/978-3-642-17298-4_48
Publisher Name: Springer, Berlin, Heidelberg
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