Research On Energy Management Strategy Of Four-Wheel-Drive Electric Vehicle Based On Energy Consumption Optimization

With the increasingly severe of energy shortage and environmental pollution,electric vehicles with the advantages of low carbon and environmental protection have ushered in unprecedented development opportunities,and have become the industrial transformation direction of many traditional automobile companies.Among the various configurations of electric vehicles,with the characteristics of high transmission efficiency and independently controllable of four-wheel torque,the four-wheel-independent-drive electric vehicles have become research focus in recent years.The four-wheel-independent-drive electric vehicle can make full use of its independent control ability without changing the total driving torque,in order to meet the safety and power requirements of the vehicle,and improve the energy-saving space.However,the key problem that needs to be solved at present is how to minimize the overall energy consumption of the vehicle,and increase the driving range through optimal control.Aiming at the above problems,this paper will focus on the energy management strategy of the four-wheel-independent-drive electric vehicles from the perspective of energy consumption optimization.Firstly,the parameters of the vehicle power system are matched,and the driving energy consumption is analyzed.First,according to the target design value,with the power requirements,the characteristic parameters and efficiency Map of the front and rear axle motors are further determined through the mathematical statistical analysis of common cycle conditions.Then,the power battery is matched according to the driving range requirements.Furthermore,the rationality of the matching results is verified by the AVL-Cruise simulation software.Finally,the driving energy consumption of the four-wheel-independent-drive electric is analyzed.Secondly,based on MATLAB/Simulink software,a simulation platform of the four-wheelindependent-drive electric vehicle is established.First,the longitudinal dynamics model of the whole vehicle is built,including the vehicle body and the wheels model.Then,the driver model is built.According to the characteristics of each component,the drive motor and power battery models are built.Finally,under the same test conditions,the accuracy of the simulation model built is verified,compared with the AVL-Cruise model.Thirdly,this paper takes the electric vehicle driven by the in-wheel motor as the research object,and based on the optimization of motor energy consumption,the vehicle energy management strategy is studied.First,a global energy management strategy based on dynamic programming algorithm is formulated,and the optimization result is taken as the theoretical optimal value.On this basis,an instantaneous energy management strategy based on genetic algorithm is formulated,the effectiveness and adaptability of this optimal control strategy is the focus of this paper.Finally,under the NEDC condition,the validity of the control strategy based on the genetic algorithm is verified.Furthermore,under the CLTC and WLTC conditions,the adaptability of the control strategy based on the genetic algorithm is verified.The simulation results show that,the energy management strategy based on genetic algorithm can effectively improve the vehicle economy,and reduce the motor energy consumption by 5.2%、6.1% and6.4% respectively under three test conditions.Finally,in order to further improve the energy saving potential of the four-wheelindependent-drive electric vehicle,the energy management strategy based on comprehensive energy consumption optimization is studied.First,the feasibility of the comprehensive energy consumption optimization problem is analyzed.On this basis,the motor energy consumption and tire slip energy consumption are taken as the comprehensive control objectives.Then,a fuzzy controller is designed to dynamically adjust the weight between the two control objectives.Furthermore,combined with the above control strategy based on genetic algorithm,an energy management strategy based on comprehensive energy consumption optimization is proposed.The optimization of motor energy consumption and slip energy consumption can be unified from the perspective of energy,which can effectively reduce the overall energy consumption of the vehicle.Finally,A joint simulation platform based on MATLAB/Simulink and Car Sim software is established.And the control effect of two different energy management strategies is verified and analyzed through simulation experiments.According to the simulation results,the comprehensive control strategy formulated in this paper can reduce the overall energy consumption of the vehicle by 4.9% and 23.5% respectively under the low adhesion road conditions and the butt road conditions.It can be seen that,on the premise of ensuring the stable driving of the vehicle,the control strategy based on comprehensive energy consumption optimization can effectively reduce the slip energy consumption of the tires,improve the energy-saving space of the vehicle and maximize the energy saving potential of electric vehicles.