基于工况识别的IWM-EV主动悬架MOPSO模糊滑模控制

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Abstract

The adaptive sliding-mode control based on road identification was applied to inhibit the negative vibration effect caused by the in-wheel motor (IWM) in an electric vehicle (EV) and a multi-objective particle swarm optimization (MOPSO) fuzzy sliding-mode controller based on working condition identification was designed.Firstly, the electromechanical model of the vertical unbalance excitation and the driving torque was established.Combining the electromechanical model with the vehicle dynamics model, a vertical-driving nonlinear dynamics coupling model for the motor and suspension was established.Based on the coupling model, the characteristics of the negative vibration effect in the electric vehicle were analyzed.Aiming at the issues of strong nonlinearity of the model, the non-linear controller based on working condition identification was designed.The simulation results show that the controller can effectively reduce the relative eccentricity of the motor, mitigate the unbalanced electromagnetic force of the in-wheel motor,improve the dynamic performance of the vehicle and effectively suppress the vibration negative effect of the in-wheel motor in the electric vehicle.

Key words： in-wheel motor(IWM) electric vehicle(EV) nonlinear electromechanical coupling model operating condition recognition multi-objective particle swarm optimization(MOPSO) sliding mode control

Received: 11 December 2019 Published: 28 March 2021

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	Articles by authors
	HU Yiming1
	LI Yinong1
	2
	LI Zhe3
	ZHENG Ling1
	2

Cite this article:

HU Yiming1,LI Yinong1,2, et al. MOPSO fuzzy sliding mode control of an IWM-EV active suspension based on operating condition recognition[J]. JOURNAL OF VIBRATION AND SHOCK, 2021, 40(6): 147-157.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2021/V40/I6/147

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