Mine car suspension parameter optimisation based on improved particle swarm optimisation and approximation model
by Jun Zhang; Xin Li; Duyou Liu
International Journal of Vehicle Design (IJVD), Vol. 80, No. 1, 2019

Abstract: A suspension parameter optimisation method is proposed in this paper to improve mine car ride comfort. The most influential parameters on vehicle ride comfort are chosen as optimisation variables by analysing parameter sensitivity using a 7-degrees-of-freedom vehicle model. A simplified regression model based on the response surface method accelerates the optimisation process. An improved chaos particle swarm optimisation (ICPSO) approach is proposed based on standard particle swarm optimisation to optimise suspension parameters in the regression model. The ideal match of suspension parameters is obtained. Simulation results show that improved suspension parameters can greatly ensure the weighted root mean square acceleration and tyre dynamic loads; additionally, suspension dynamic deflections are limited within an allowable range. Test results reveal that the suspension multi-parameter optimisation method based on ICPSO can improve vehicle ride comfort. Therefore, this method can be used to guide future research and development of suspension systems.

Online publication date: Sat, 08-Feb-2020

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