| In recent years,with the continuous increase of vehicle ownership,traffic jam,frequent accidents and environmental pollution are beset with people’s auto life."Intelligent electric vehicle" has become a new theme for the development of the future auto industry.As a kind of intelligent driving assistance technology,adaptive cruise control system has been developing for many years,and it has been commercialization in the luxury traditional model.The adaptive cruise control system applied in pure electric vehicles is still relatively smal.The characteristics of the electric vehicle’s power system and braking system are quite different from those of the traditional gasoline vehicle.The traditional adaptive cruise control strategy is difficult to transplant directly to electric vehicle.In addition,control of electric vehicle is relatively flexible,and the regenerative braking can be realized,which has greater optimization space for the adaptive cruise control strategy.Therefore,based on the characteristics of electric vehicle driving and braking system,a multi-objective optimization adaptive cruise control strategy based on electric vehicle was designed to make the vehicle satisfied with the traditional adaptive cruise following,safety and comfort,and improved vehicle’s economy.Due to the great difference between electric vehicle power system and braking system and that in traditional vehicle,the characteristics of electric vehicle system was explained and analyzed.Based on the electric vehicle of front-engine front-wheel drive layout,the characteristics of the drive system was analyzed.Response characteristics of the motor was modeled.The characteristics and efficiency of permanent magnet synchronous motor were analyzed.generator response characteristics in braking was analyzed.superimposed braking energy recovery system was compared with front axle decoupling brake energy recovery system.Based on the braking energy recovery system configuration,driver mode and adaptive cruise control mode of braking force distribution strategy and work status was designed.the relationship between the braking intensity,speed,motor braking torque was set up.Based on the theory of model predictive control,an adaptive cruise control decision algorithm for multi-objective optimization was designed.The safe distance model was designed according to the distance strategy of fixed time interval.Longitudinal car following model and state space equation were established,and the state equation was discretized.performance indexes like economy,following,safety and comfort were chosen.Functions and constraints for performance indexes were designed.The prediction model of vehicle following model,performance index function and constraint were derived,which was formulated as a nonlinear programming problem.The problem was solved by interior point method.Based on the characteristics of electric vehicle drive system and braking system,an adaptive cruise longitudinal control algorithm was designed for electric vehicle,so that vehicle actual acceleration can follow the expected acceleration change stably.Considering the traditional mode switching strategy ignoring changes in external environment which would influence datum acceleration.By analyzing driving resistance model of electric vehicle,mode switching strategy based on weighted least squares fitting was designed,and through the joint simulation of Simulink and CarSim,verifying the accuracy of predicting datum acceleration in wind disturbance and gradient disturbance.Adaptive cruise control system strategy model was established in MATLAB/Simulink,road environment and vehicle model was defined by CarSim based on target vehicle configuration.cruise conditions,go stop condition,entry and exit conditions,following condition and NEDC condition was chosen to simulate,and the simulation results were analyzed. |
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