Preprint Article Version 1 This version is not peer-reviewed

Ride Comfort Optimization of In-Wheel-Motor Electric Vehicle with In-Wheel Vibration Absorber

Version 1 : Received: 20 September 2017 / Approved: 21 September 2017 / Online: 21 September 2017 (12:59:33 CEST)

A peer-reviewed article of this Preprint also exists.

Liu, M.; Gu, F.; Zhang, Y. Ride Comfort Optimization of In-Wheel-Motor Electric Vehicles with In-Wheel Vibration Absorbers. Energies 2017, 10, 1647. Liu, M.; Gu, F.; Zhang, Y. Ride Comfort Optimization of In-Wheel-Motor Electric Vehicles with In-Wheel Vibration Absorbers. Energies 2017, 10, 1647.

Journal reference: Energies 2017, 10, 1647
DOI: 10.3390/en10101647

Abstract

In this paper, an in-wheel vibration absorber for In-wheel-motor electric vehicle (IWM EV) is designed, and a comprehensive control strategy of in-wheel absorber and vehicle suspension is proposed to improve vehicle ride comfort. The proposed in-wheel vibration absorber, designed for suppressing the motor vibration, is composed of a spring and a controllable damper. The values of in-wheel spring stiffness and damper initial coefficient are determined by using the improved particle swarm optimization (IPSO) algorithm, which is carried on the typical driving condition. To deal with the negative interaction effects between vehicle suspension and in-wheel absorber, the linear quadratic regulator (LQR) algorithm is utilized to control suspension damper, and the fuzzy PID method is utilized to control in-wheel damper. Based on the four evaluation indexes including vehicle body vertical acceleration, suspension dynamic deflection, wheel dynamic load and motor wallop, the simulation results show that, the proposed LQR control of suspension effectively improves vehicle ride comfort, and the fuzzy PID control of in-wheel damper exhibits superior performance of motor vibration suppressing in comparison to conventional electric wheel.

Subject Areas

in-wheel-motor electric vehicle; ride comfort; improved particle swarm optimization; linear quadratic regulator; fuzzy PID control

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