Parameters optimization of differential assisted steering for electric vehicle with motorized wheels based on NLPQL algorithm

The model of the differential assisted steering system with force and displacement coupled control for electric vehicle with motorized wheels was built.Based on these models of system,the quantitative expressions of the road feeling,sensitivity,operation stability and economy of the steering were proposed.According to the features of multi-constrained optimization of multi-objective function,NLPQL algorithm was designed.Taking the road feeling and energy consumption of the steering as optimization objectives,and operation stability and sensitivity of the steering as constraint,the system parameters were optimized.The results show that optimization based on NLPQL algorithm can improve the steering road feeling,reduce the steering energy consumption more effectively and can also guarantee the operation stability and steering sensibility,which provides theoretical basis for the design and optimization of the electric vehicle with motorized wheels system.