| Developing new energy vehicles has become the key strategy to solving environmental and energy problems,with the increasingly severe environmental and energy problems.Because of the development of electric vehicle battery don’t have major breakthrough in the research,Plug-in Hybrid Electric Vehicle has become an important part of China’s new energy development strategy.Energy management,as the core technology of the development of Hybrid Electric Vehicles,determines the power,economy and emissions of the vehicle.In this paper,we take a kind of Plug-in Hybrid Electric Vehicle as the object of study and propose a solution to optimal energy distribution problems of Plug-in Hybrid Electric Vehicle based on the blend of Moving Horizon Control algorithm.Forecasting energy management strategy is the core of this article.According to Markov prediction method and dynamic programming algorithm,we obtain the optimal value of local prediction.Then we make global programming of the State of Change(SOC)based on space domain.In addition,we take the programming as terminal constraints of local prediction.Last,using receding horizon control method and following the global optimal track of SOC,the optimal energy distribution problems of Plug-in hybrid electric vehicle is solved.Firstly,this paper analyzes driving types and characteristics of Plug-in hybrid electric vehicle,and makes a scheme of parameter matching of single-axle parallel Plug-in hybrid electric vehicle.For the scheme,all parameters of the whole vehicle are matched.Besides,the parameters matching of engine,motor,ATM and change are completed.And we build a quasi-static model for engine,motor and other parts of vehicles which lays foundations for the follow-up study of energy control strategy.Secondly,it is determined that the distance is the main factor that affects the battery SOC.Based on this theory,the global optimal SOC trajectory based on the space domain is established by the Dynamic Programming algorithm.And the SOC constraints for the short-term prediction conditions are determined for the Moving Horizon Control.Thirdly,the short-term vehicle driving conditions are forecasted based on Markov theory,which is used as the short-term disturbance of the Dynamic Programming algorithm.Furthermore,the short-term optimal control quantity is solved according to the dynamic programming algorithm,based on the short-term optimal control and the global optimal SOC trajectory.This step provide the amount of control at each moment for the Moving Horizon ControlFinally,the Moving Horizon Control theory is expressed,and the energy management strategy of Plug-in Hybrid Vehicle based on moving horizon control is established.The global energy management usage of plug-in hybrid vehicle is solved by global SOC optimal trajectory and local optimal control.Optimize the allocation problem.In this paper,the Moving Horizon Control method is used to make the local optimal quantity track the global optimal SOC trajectory,so as to solve the global energy optimization allocation problem.The experimental results show that the energy management control strategy of the plug-in hybrid vehicle based on rolling time domain achieves better fuel economy. |
