Energy Optimization And Coordination Control Strategy For Dual Motors Planetary Coupling PHEV

Efficiency and energy saving are the main goals of automotive technology development.Hybrid Electric Vehicle(HEV)has become the focus of new energy vehicles because of its energy saving and low emission characteristics,especially plugin hybrid electric vehicle(PHEV)is suitable for suburban roads.It also shows excellent energy-saving characteristics,has both the advantages of pure electric drive and the convenience of fuel system,and achieves the balance of efficiency and practicability.The traditional HEV takes fuel economy as its main objective,and its dynamic performance is often unsatisfactory.Based on this,a new type of planetary coupling power shunt system with two motors is proposed,which is applied to PHEV.Aiming at the coordination and energy optimization of PHEV electromechanical coupling complex system.This paper mainly focuses on the following work.Firstly,the energy transfer path of the two-motors planetary-coupled hybrid power system is analyzed,and the mathematical models of PHEV components are constructed.Further,based on the platform of MATLAB/Simulink,the vehicle longitudinal dynamics model,driver model,engine model,motor model and power battery model are built by combining theoretical modeling method with quasi-steady state table lookup model.Secondly,an energy optimization method for ECMS based on the combination of equivalent factor optimization and genetic algorithm is proposed.Aiming at the fuel economy and the coupling mechanism between multi-power sources in planetary gear mechanism,an adaptive Equivalent Consumption Minimization Strategies/A-ECMS algorithm is established.On this basis,the influence of vehicle initial SOC and driving mileage on the equivalent factor of oil and electricity is further introduced.The genetic algorithm based on Equivalent Consumption Minimization Strategies/GA-ECMS is established by using genetic algorithm to optimize the equivalent factor offline according to different driving conditions.Further,the fuzzy adaptive PID is used to improve the tracking accuracy of the engine speed.The model in-the-loop simulation is carried out on the platform of Matlab/Simulink.The simulation results show that the GA-ECMS strategy can further optimize the working mode and gear of the system,and improve the fuel economy.Compared with traditional ECMS and A-ECMS,the proposed GA-ECMS algorithm reduces vehicle fuel consumption by 5.54% and 1.54% respectively.At the same time,the fuzzy adaptive PID optimizes the actual working point of the engine.Fuel economy has been further improved.Thirdly,considering the different characteristics of transient response of dual motors and engines,a PHEV mode switching coordinated control system is designed by using the method of fuzzy adaptive sliding mode.In order to improve driving comfort,a fuzzy adaptive sliding mode method is introduced to improve the performance of the clutch in the process of combination,considering the significant difference between the transient response characteristics of the engine and the motor.The model-in-the-loop simulation is carried out on Matlab/Simulink platform.The simulation results show that compared with uncoordinated control,the fuzzy adaptive sliding mode coordination controller can effectively reduce the vehicle impact and make the clutch engagement process more smoothly.Finally,in order to verify the validity and reliability of energy management strategy and coordinated control strategy,hardware-in-the-loop test was carried out.The simulation results of energy management strategy show that compared with traditional ECMS and A-ECMS,the proposed GA-ECMS algorithm reduces vehicle fuel consumption by 6.96% and 2.13% respectively.Furthermore,it provides a theoretical basis for solving the power allocation strategy of PHEV under different initial SOC and driving mileage.The simulation results of hardware-in-the-loop test of coordinated control strategy show that the proposed coordinated control strategy reduces 90.1% of the maximum longitudinal impact and 90.43% of the fluctuation range of impact when mode switching occurs compared with the non-coordinated control.The experimental results verified the effectiveness and reliability of the coordinated control strategy controller designed in this paper in real-time environment.