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Cui et al. Complex Eng Syst 2023;3:3 Complex Engineering
DOI: 10.20517/ces.2022.57 Systems

Research Article Open Access

Parameters optimization of electro-hydraulic power steer-
ing system based on multi-objective collaborative method

1
2
Taowen Cui 1,2 , Shuaiyin Wang , Yuan Qu , Xiang Chen 2
1 Intelligent Vector Technology Control Lab, Chery Automobile Company Limited, Wuhu 241000, Anhui, China.
2 School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230041, Anhui, China.

Correspondence to: Dr. Taowen Cui, School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei
230041, Anhui, China. E-mail:nuaa_ctw@126.com

How to cite this article: Cui T, Wange S, Qu Y, Chen X. Parameters optimization of electro-hydraulic power steering system based
on multi-objective collaborative method. Complex Eng Syst 2023;3:3. http://dx.doi.org/10.20517/ces.2022.57
Received: 20 Dec 2022 First Decision: 19 Jan 2023 Revised: 3 Feb 2023 Accepted: 17 Feb 2023 Published: 9 Mar 2023

Academic Editors: Hamid Reza Karimi, Serdar Coskun Copy Editor: Fangling Lan Production Editor: Fangling Lan

Abstract

Electro-hydraulic power steering (EHPS) systems are widely used in commercial vehicles due to their adjustable
power assist and energy-saving advantages. In this paper, a dynamic model of the EHPS system is developed, and
quantitative expressions for three evaluation indexes, steering road feel, steering sensibility and steering energy loss,
are derived for the first time. A multi-objective collaborative optimization model of the EHPS system is then estab-
lished, which consists of one total system and three parallel subsystems, based on collaborative optimization theory.
Considering the coupled variables of each subsystem, the total system is optimized by a multi-objective algorithm,
while the subsystems are optimized by a single-objective algorithm. The optimization results demonstrate that the av-
erage frequency domain energy of the steering road feel is increased by 69.1%, the average frequency domain energy
of steering sensitivity is reduced by 19.2%, and steering energy consumption is reduced by 10.8% compared to the
initial value. The non-dominated sorting genetic algorithm-II (NSGA-II) shows superior comprehensive performance
compared to the other two multi-objective algorithms, and the optimization performance can be further improved by
setting appropriate algorithm parameters.

Keywords: Electro-hydraulicpowersteering, multi-objectiveoptimization, collaborative optimization, non-dominated
sorting genetic algorithm-II

© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0
International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, shar-
ing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you
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