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Optimal design of electro-hydraulic active steering system for intelligent transportation environment

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  • Cui, Taowen
  • Zhao, Wanzhong
  • Tai, Kang

Abstract

The steering system is an important link between driver and vehicle, and it has a significant impact on energy consumption and driving experience. In order to improve the system’s overall performance, the electro-hydraulic active steering (EHAS) system is taken as the design object, which involves steering energy loss, steering road feel, steering sensitivity and steering stability. According to the energy flow analysis of the steering system, the optimization of the parameters of assist motor and rotary valve is the key to improve steering economy. Based on the optimization of structure parameters of EHAS system, control parameters are innovatively introduced into the optimization of steering system performance. The influence of optimization parameters on these evaluation indexes is further explored. Then, the multi-objective optimization model of EHAS system is then established and optimized by a multi-objective genetic algorithm. The optimization results show that the energy loss of EHAS system with optimized structure and control parameters is 9.44% lower than before optimization, and the driving experience is further improved.

Suggested Citation

  • Cui, Taowen & Zhao, Wanzhong & Tai, Kang, 2021. "Optimal design of electro-hydraulic active steering system for intelligent transportation environment," Energy, Elsevier, vol. 214(C).
    • Handle: RePEc:eee:energy:v:214:y:2021:i:c:s0360544220320181
    DOI: 10.1016/j.energy.2020.118911
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    References listed on IDEAS

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    1. Cui, Taowen & Zhao, Wanzhong & Wang, Chunyan, 2019. "Design optimization of vehicle EHPS system based on multi-objective genetic algorithm," Energy, Elsevier, vol. 179(C), pages 100-110.
    2. Wang, Jianzhou & Yang, Wendong & Du, Pei & Li, Yifan, 2018. "Research and application of a hybrid forecasting framework based on multi-objective optimization for electrical power system," Energy, Elsevier, vol. 148(C), pages 59-78.
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