The Research On Predictive Control Strategy Of Plug-in Hybrid Electric Vehicle

During the development of the world today,energy shortage and environmental pollution are the two major problems for human beings.Although the pure electric vehicles can realize the purpose of energy conservation and environmental protection,however,because of the limitation of key technology,the popularity of electric vehicles needs a long time to go.With the development of Plug-in Hybrid Electric Vehicles(PHEV)in recent years,which is a kind of transition car to the pure electric vehicles,the main feature is that it can work in pure electric mode,also work in hybrid mode,engine can charge the battery when the battery power is low,thereby improving vehicle fuel economy and emissions and increasing driving distance.However,how to establish a suitable control strategy to achieve the switch between different modes of work is particularly important.Therefore,the study of PHEV control strategy has become a hot spot.This article is based on the MATLAB and ADVISOR.It takes the parallel plug-in hybrid electric vehicle as study object,with the main goal to reduce vehicle fuel consumption and emissions,we established the predictive control strategy based on the future vehicle speed information and optimized the control strategy parameters.Firstly,according to the parallel HEV vehicle parameters and PHEV target performance requirements to match parameter,determine the parameters of the engine,motor and power battery that meet the design requirements.Secondly,we analysis the impact of future traffic information on PHEV fuel consumption and emissions,and choose the vehicle future speed information of the driving condition as the research target,then we establish a future vehicle speed forecasting model,thereby lay the foundation for the establishment of predictive control strategy model.Then,according to the characteristic that PHEV has the power consumption and the power maintain,we establish the predictive control strategy model based on future vehicle speed information.And then we carry out the simulation for predictive control strategies based on ADVISOR.The results show that: in different stages,the predictive control strategy can reasonably allocate the engine and motor torque.While improving the fuel economy and emissions of the vehicle.As for the predictive control strategy impact the vehicle fuel consumption and emissions,we use a multi-objective genetic algorithm to optimize the predictive control strategy parameters under the premise of satisfying the vehicle's dynamic performance with the goal to minimize emissions and fuel consumption,while improving engine and motor efficiency,finding the optimal value of control strategy parameters,so as to achieve the goal of energy saving and emission reduction.