Research On Shift Strategy For Two-Speed AMT Of Battery Electric Vehicle

Automatic shift technology is the core of transmission system development in the field of Battery Electric Vehicle(BEV).As requirements for endurance mileage and acceleration capacity of BEV increased,multi-shift has become an inevitable trend,vehicles equipped with two-speed Automatic Mechanical Transmission(AMT)has played a better role in acceleration of motor driving force,system energy loss can be decreased,and vehicle performance advantages are improved.This paper,based on BEV test platform equipped with two-speed AMT,researches optimal economic,dynamic,and comprehensive shift strategy.The main parts of this paper are as follows:(1)Based on two-speed transmission structure and data,and control system validation requirements,the kinetic model has been established to reflect main features of the transmission system,drive motor and vehicle.Meanwhile,theory and experiment are combined to establish the system efficiency model including battery,drive motor and transmission under driving conditions,which has laid the foundation for preparation of economic and dynamic shift schedule.(2)This paper takes two-speed AMT as the research object to establish the shift schedule which takes power consumption of 100 kilometers,accelerated speed and maximum energy recovery efficiency as evaluation index.For energy loss of each component in the system under driving conditions,based on optimal system efficiency,this paper considers effect of battery State of Charge(SOC)on system efficiency to prepare optimal economic up-shift schedule;this paper takes the acceleration as the optimal object and ensures minimum power loss and prepares optimal dynamic up-shift schedule;this paper also takes maximum regenerative braking force as the goal to prepare optimal economic down-shift schedule under regenerative braking conditions.By analyzing the influence of different SOC on shift schedule,the SOC influence interval is divided to lay a foundation for preparation of comprehensive shift strategy.(3)Comprehensive performance index composed of power consumption of 100 kilometers,acceleration time and dynamic demand factor are introduced,one dynamic demand factor calculation method is presented,and shift schedule switch controller is designed.Minimum comprehensive performance index is the goal.Based on the fuzzy theory,dynamic demand factor increment is calculated,and iterative learning controller of open PID-type learning law is used to optimize dynamic demand factor increment.The simulation result shows that compared to traditional shift strategy,comprehensive shift strategy under the switch controller can quickly and correctly recognize driving intention,execute shifting schedule,which can ensure vehicle power performance,improve system efficiency and effectively extend vehicle endurance mileage.(4)To verify the control effect of comprehensive shift strategy designed by this paper on real vehicles,based on real vehicle test platform,standard BEV economy and dynamic test method in China is used to conduct chassis hub test and road test.Test result shows that comprehensive shift strategy on the vehicle based on fuzzy controller and optimized iterative learning controller is feasible.Compared to traditional shift strategy,actual running vehicle comprehensive performance has been improved,and expected research objectives have been achieved.Compared to traditional shift strategy,comprehensive shift strategy based on the fuzzy controller and optimized open-type PID iterative learning controller can ensure vehicle dynamic and improve economy.The simulation shows that under the conditions of NEDC and FTP75,power consumption of 100 kilometers has decreased by 13.85% and 12.88%,accelerated speed has decreased by about 3.60% and 4.54%.When the acceleration meets the demands,effect of economy improvement is remarkable.The error between real vehicle test and simulation results is within 7%,which proves that the comprehensive shift strategy is effective for real vehicles.