Study On Braking Force Distribution Performance Of Pure Electric Vehicle Based On Particle Swarm Optimization Algorithm

In 2019,the growth of the traditional automobile industry is weak,but new energy vehicles are bucking the trend in the city.The new energy automotive industry accelerated entering "subsidies after age" in the domestic market.Pure electric vehicles is an important part of the new energy automotive industry and an effective solution to alleviate the energy crisis.Regenerative braking energy recovery is of great significance in the key technology of the pure electric vehicles.This paper takes a certain kind of pure electric vehicles as the research basis,through the comparison of existing regenerative braking capacity recovery control strategies,a regenerative braking distribution control strategy based on multi-objective particle swarm optimization algorithm is proposed.The results show that the proposed algorithm can improve the SOC remaining amount of pure electric vehicles and has practical significance.This paper mainly studies:1)This paper firstly analyzes the research and application cases of the electric vehicle regenerative braking energy recovery at home and abroad.Besides,the advantages and disadvantages of each control strategy are analyzed based on the numerous braking energy recovery control strategies proposed by the predecessors.Then according to the force analysis of the braking process of the front-drive pure electric vehicle,the braking area included in the ideal braking force curve and the ECE line of the regulatory line is analyzed.Use MATLAB software to plan the areas where the regenerative braking,pure motor braking,hybrid braking,and pure mechanical braking conditions are located,providing a theoretical basis for the optimized boundary conditions.2)Using Simulink software to carry out forward simulation modeling for key components of pure electric vehicles,including driver model,motor model,battery model,etc.The motor model adopts three-phase permanent magnet synchronous motor and SVPWM control strategy,and the battery model adopts Rint model.Finally,under the input conditions based on speed conditions,the fixed ratio regenerative braking control strategy is simulated under ECE cycle conditions to analyze the SOC change,motor power change curve,and motor torque change curve.3)Based on the existing Simulink model of the whole vehicle,the particle swarm optimization strategy is proposed in the direction of multi-objective optimization that maximizes braking safety and regenerative braking energy recovery.After 200 iterations,athree-dimensional chart of motor braking,front wheel braking force,and rear wheel braking force is selected using a decision strategy.The braking intensity Z and the motor maximum braking force output is the relevant braking intensity.Then embed the three-dimensional chart on the regenerative braking control strategy,and finally simulate the SOC and other parameters under ECE cycle conditions.4)The experiment platform of permanent magnet synchronous motor(PMSM)hardware-in-the-loop was built based on the existing conditions in the laboratory to verify the motor control strategy.