Intelligent Electric Vehicle Multi-source Information Perception and Active Ob-stacle Avoidance Control Method
The traditional intelligent electric vehicle motion trajectory planning method under emergency conditions is too conservative,resulting in the problem of interactive interference in the vertical and horizontal control of the gener-al tracking control method under composite inputs.Propose an intelligent electric vehicle multi-source information perception and active obstacle avoidance control method.Firstly,an intelligent electric vehicle multi-source information perception architecture is constructed through multi-source heterogeneous sensors and joint calibration.By preprocess-ing and optimizing multi-source information perception data,the accuracy and reliability of environmental information are improved.Divide the motion of electric vehicles into horizontal and vertical control.In terms of lateral control,a sliding mode controller is used to receive reference path information and vehicle heading angle information,and calcu-late the front wheel angle for lateral automatic control.The sliding mode controller must meet the constraint condi-tions to ensure operation within the set area.For longitudinal control,precise tracking of longitudinal position is achieved through vehicle acceleration and brake actuators.Finally,by combining the multi-source information percep-tion results of intelligent electric vehicles and effectively combining the horizontal and vertical control results,active obstacle avoidance control of intelligent electric vehicles during driving can be achieved.The experimental results show that the proposed method has good environmental perception ability and active obstacle avoidance control per-formance,and has low control delay and high driving reliability.
intelligent electric vehiclesmulti source information perceptionactive obstacle avoidance controlsynovial control algorithm
万方数据
维普
