Research On Control Strategy Design And Optimization Algorithm Of Extended Range Electric Vehicle

Environmental pollution and energy crisis get worse and worse these years,with the rapid growth of the number of cars all over the world.Due to the short distance and inconvenient charging problem,the rapid growth of electric vehicles has been restricted.The extended range electric vehicle（E-REV）,however,has been paid close attention because the lower producing price and the longer driving distance,and the control strategy of energy management has become the hit on the reseach of extended range electric vehicle.This paper studies a kind of extended range electric commercial vehicle under the background of a innovate project of some province.The main point of this paper is: Finish the type choosing and the parameter matching of the key part of the powertrain,which is based on the basic designing goal of the vehicle.Then design and optimize the energy managing control strategy of E-REV,which is under the results of E-REV working mode analyzing.The detailed research content in this paper is as follows:1.Choose the type and match the parameter for the key part of the powertrain of E-REV,which is according to the basic vehicle parameter and the power performance target.Analyze the working mode of E-REV,then summarize and arrange the design principles and overall process of E-REV.The control process is divided into driving mode and braking mode.Based on the comparative analysis of the existing control strategies,the engine multi-point control strategy and braking mode control strategy are designed for the two modes respectively.2.Build the E-REV forward simulation model with the software CRUISE,then set the parameters of each component with the selected type and matched data.Build the control strategy model for the E-REV under the effect of the software MATLAB/Simulink and the Function module of CRUISE,then the dynamics of whole vehicle is simulated through the co-simulation platform of CRUISE / Simulink,and testify the result of parameter matching and the devised multi-operating point control strategy.The result shows that the designing request can be fit with the control strategy.3.Build the thermostat control strategy,which is popular currently.Finish the economical simulating under the same working condition with the multi-operating point control strategy,then compare and analyze the results of the comprehensive gasoline consumption of these two control strategy.Calculate the battery capacity fade data under the fade model,then compare the comprehensive gasoline consumption and the battery capacity fade consumption,which are unified together,under the two stratey.The result shows that the comprehensive price reduce 5.78% under the multiple working point control stratey,which is more economical than the other.4.In order to enchance the comprehensive economy of E-REV,optimize the multiple working point control strategy.Build the co-simulation platform with the Isight software and CRUISE software,then choose the optimizing variable and design the relevant target function and restraint condition.Optimize the engine output power of the multi-operating point control strategy,using the genetic algorithm as the optimization algorithm.The optimized simulation result shows that the comprehensive fuel consumption reduce 2.05%and 2.24%,in the working condition of NEDC and UDC,which indicates the optimization is working well.