Research On Parameter Matching And Control Strategy Of PHEV

Energy shortage and environmental problems have become a stumbling block for global development.All countries in the world are studying new energy technologies.Plug in hybrid electric vehicle is a new energy vehicle with low fuel consu mption and unlimited mileage without battery power.The control strategy of PHEV is one of the difficult points in the current research.Excellent control strategy can greatly improve the fuel economy of the whole vehicle.In this paper,the control strate gy of dual motor PHEV is studied based on the lateral subject of dual motor plug-in hybrid electric vehicle.The details of the work are as follows:First,overall structure of PHEV is designed according to the requirements of design.The powertrain parameters are calculated and matched.The CAN network structure and the CAN communication protocol are formulated.Then,the dual motor PHEV vehicle object model is built by AVL CRUISE platform and inspect bus connection and model correctness,which laid the fou ndation for the development of key control strategies in this paper which lays a foundation for the development of the control strategy of this paper.A logic threshold control strategy is proposed b ased on the characteristics of PHEV power system.The motor drive-based control strategy and the optimized engine working interval-based control strategy are designed in the CD mode and CS mode.On this basis,a fuzzy logic controller with three inputs which are SOC,ΔSOC and ratio I and a output which is ratio O is designed.It has three inputs which are SOC,ΔSOC and ratio I and a output which is ratio O.Two control strategy models are built through Matlab/Simulink platform.Finally,the whole vehicle object model and control strategy model are used to establish the joint simulation of Interface mode.The dynamic performance and fuel economy of the logic threshold control strategy ar e simulated.The influence of preset travel on fuel economy is explored.The fuel economy of the two control strategies in different driving distance is compared and analyzed.The results show that the two control strategies achieve the design goals and the fuzzy logic control strategy has better robustness and fuel economy.