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Design optimization of vehicle EHPS system based on multi-objective genetic algorithm

Cui, Taowen, Zhao, Wanzhong, Wang, Chunyan
Energy 2019 v.179 pp. 100-110
algorithms, energy, models, system optimization
Electric hydraulic power steering (EHPS) system has been widely used in large and medium cars, which plays an important role in determining the energy loss, driving safety and driving comfort of vehicles. This work mainly discusses the parameter design of the EHPS system based on the multi-objective optimization method. Since there is no explicit standard for the performance indexes of EHPS system, this work takes the energy consumption, steering road feel, steering sensibility and steering stability as the main performance indexes of EHPS system. The quantization formula of each performance index is explored and deduced. Based on these, a multi-objective optimization model is established. Then, the non-dominated sorting genetic algorithm-III based on fitness function (NSGA-III-FF) is proposed, which has better convergence than the original non-dominated sorting genetic algorithm-III (NSGA-III). Besides, the technique for order preference by similarity to an ideal solution (TOPSIS) is applied to select the ideal optimization solution. Simulation results show that the NSGA-III-FF enhances the comprehensive performance of the EHPS system, which can successfully achieve the goal of multi-objective optimization for steering flexibility, steering road feel, and steering energy loss while ensuring the steering stability.