Title: Mine car suspension parameter optimisation based on improved particle swarm optimisation and approximation model

Authors: Jun Zhang; Xin Li; Duyou Liu

Addresses: School of Mechanical Engineering, Beijing Institute of Technology, 5. Zhongguancun South Street, Haidian District, Beijing 100081, China ' School of Mechanical Engineering, Beijing Institute of Technology, 5. Zhongguancun South Street, Haidian District, Beijing 100081, China ' China Automotive Technology & Research Center Co., Ltd., 68, Xianfengdong Road, Dongli Economic Development Zone, Tianjin, 300300, China

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.

Keywords: mine car; ride comfort; suspension parameter optimisation; multi-parameter optimisation; particle swarm optimisation; chaos particle swarm optimisation; approximation model.

DOI: 10.1504/IJVD.2019.105062

International Journal of Vehicle Design, 2019 Vol.80 No.1, pp.23 - 40

Accepted: 06 Aug 2019
Published online: 11 Feb 2020 *

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