Research And Optimization Of Vehicle Control Strategy For Pure Electric Vehicles

With the rapid growth of the world’s economy and the rapid development of the automotive industry,the global car ownership continues to increase,and the huge car ownership has also caused serious fuel shortage problems and environmental pollution problems.Therefore,we must vigorously develop new energy vehicles as alternatives to traditional fuel vehicles to cope with the current environmental and resource problems.Pure electric vehicles have low pollution,low energy consumption and good power.Vigorously developing pure electric vehicles is a good way to solve the current problems.However,the problems of low driving range and short battery life of electric vehicles have become an important factor restricting the development of electric vehicles.In the research on pure electric vehicles,the performance of the entire vehicle can be improved by optimizing the performance of auto parts or optimizing the auto’s own control system.Among them,the vehicle control strategy manages all components of the vehicle,and controls the torque output,gear,driving mode,and status monitoring of the vehicle,which are particularly critical to the performance of the vehicle.This topic studies the control system of pure electric vehicles,establishes a complete vehicle control strategy for pure electric vehicles,aims to improve power performance,extend battery life,and reduce electrical energy consumption.By establishing battery life prediction models and predicting driving intentions,the design drive Control optimization strategies.Firstly,according to the aging mechanism of the lithium-ion battery,the factors affecting its life decay are analyzed.According to the cycle life experimental data,a semi-empirical model for predicting the cycle life of the multi-factor battery is established,and the model parameters are obtained by the fitting method.On this basis,the semi-empirical model of battery life decay is applied to the driving conditions of vehicles to obtain the relationship between battery life and vehicle state parameters during the driving of electric vehicles.Then design the vehicle control strategy,including: power-on and power-off control strategy,gear management strategy,vehicle driving mode management strategy,fault diagnosis strategy and drive control strategy.Focusing on the study of drive control strategies,two drive control modes,power mode and economic mode,are designed.And formulate a torque control strategy based on driving intention,and divide the control torque into reference torque and compensation torque.Using empirical data,the accelerator pedal MAP is established as the reference torque,and then the fuzzy control algorithm is used to calculate the compensation torque of the power mode to reflect the driver’s dynamic intention,which improves the vehicle’s dynamic performance.Then optimize vehicle performance for economic mode,analyze the starting point of optimizing vehicle performance,and choose to optimize for motor efficiency and battery life in acceleration conditions.For the purpose of optimizing the three performance indicators of acceleration time,power consumption,and battery capacity decay,a multi-objective optimization model was established based on the battery life decay model and motor efficiency characteristics.Then use the dynamic programming algorithm to optimize the solution and obtain the optimal control strategy.Finally,establish a simulation model and conduct simulation experiments to verify the control strategy.Establish the battery equivalent circuit model,and use least squares method with forgetting factor to identify the model parameters.Combined with the relevant parameters of the vehicle and the motor,a vehicle simulation model is established.Use Dspace/Micro Auto Box for software-in-the-loop simulation,design test cases and verify the logic strategy of vehicle control.Design a variety of test conditions to compare the performance differences before and after optimization,proving that the drive control strategy can improve the vehicle’s dynamic performance and economic performance...