Configuration Optimization And Optimal Energy-Efficiency Control Strategy Based On Traffic Information Fusion For Battery Electric Vehicle Powertrain With Dual Motors

In the face of the increasingly acute contradiction among energy shortage,environmental pollution and social development,energy-saving and emission-reduction technology has been a hot topic in the automotive industry around the world.Electric vehicle technology is one of the important energy-saving and emission-reduction technology to alleviate the above severe situation effectively,the development trend of vehicle electrification has gradually become an international consensus.However,due to the problems of short driving distance,low operating efficiency and long charging time,the existing battery electric vehicle(BEV)products still cannot fully meet the daily needs of consumers,which makes it difficult for the BEV to be effectively popularized.Therefore,the development of a novel electric powertrain and its advanced control strategy is one of the key ways to effectively alleviate the above shortcomings and improve the comprehensive performance of BEV,which is also the urgent demand of the development of electric vehicle technology.Based on the technology of multi power resource coupling powertrain of electric vehicle,this paper studies the configuration and control strategy of BEV powertrain with dual motors.The main contents are as follows:(1)Based on the comparative analysis of the energy-saving potential of single power resource / multi power resource coupling powertrain of BEV,the coupling mechanism of speed / torque for coupling powertrain is deeply explored,the overall scheme of BEV powertrain with dual motors and the selection of component types and quantities are completed in this paper.(2)Taking the existing BEV multi-mode coupling powertrain configuration with dual motors as a reference configuration.And reference configuration is split and the main power resource components and mechanical coupling mechanism are retained to obtain the basic configuration scheme.(3)In order to systematically explore all feasible topological structures based on the basic configuration scheme,and quickly classify and combine the feasible topological structures / driving modes to generate configuration candidates,an improved general matrix topological design method is proposed based on the internal constraint relationship between mechanical coupling mechanism nodes and power resource components.(4)To screen the configuration with the optimal comprehensive performance from the configuration candidates,a global optimal control strategy based on dynamic programming algorithm is formulated,and the optimal economy and dynamic performance of all the configuration candidates are simulated.(5)In order to give full play to the energy saving potential of the optimal configuration scheme under complex operating conditions,taking the optimal configuration scheme as the research object,an optimal energy-efficiency control framework based on dynamic traffic information flow is proposed.The traffic information layer,target planning layer,vehicle prediction and control layer of the proposed control framework are completed.(6)To make the proposed control framework have excellent prediction,real-time control and robustness in complex conditions,a speed predictor based on generalized regression neural network(GRNN)is adopted,and an MPC rolling follow control method is proposed to be applied in the vehicle prediction and control layer.(7)In order to verify the effectiveness of the proposed control strategy,according to the real road and its historical traffic information,a simulation condition with dynamic updating characteristics of traffic information is established,and the comparative simulation and test for the proposed control framework and control method are completed under the simulation condition.