Research On Energy Optimization Strategy Of Range Extended Electric Vehicle

Since the invention of the automobile,the movement of human being has become more and more convenient?but the rapid growth of the number of vehicles has brought a series of problems,such as resource consumption and environmental pollution.In order to realize the sustainable development of human society,new energy vehicles came into human being.Its development has great significance to reduce the consumption of oil resources and reduce environmental pollution.Range extended electric vehicle is one of the important models of new energy vehicles.Not only can range extended electric vehicle drive a short distance using pure electric,but also it can prolong the vehicle mileage by range extender greatly.This paper takes the range extended electric vehicle as the research object to realize the energy optimization strategy of the model.First of all,the electric vehicle controller is introduced.Based on the electric vehicle controller,the fuel consumption rate optimization problems of range extended electric vehicle is researched.The modeling and simulation of the range extender fuel consumption rate based on map and Differential Evolution algorithm are conducted with MATLAB and GUI.Firstly,the commonly used optimization strategy of fuel consumption rate and its deficiency are analyzed,then,three different models are built according to the practical engineering needs.According to the different models,simulation are conducted to optimize the fuel consumption rate based on Differential Evolution algorithm with the motor external characteristic,actual power demand and other parameters as constraint.The engine speed and generator torque are controlled according to the curve of optimal APU fuel consumption rate in real-time and accurately,making the range extender working at the best oprating point.The simulation results show that the proposed approach can reduce vehicle fuel consumption.The oil consumption-electricity conversion efficiency optimization problem of the range extender in electric vehicle is researched in this paper.Firstly,the vehicle power control strategy in different state of charge was generated by analyzing schematic diagram of the electric vehicle power train.Then,the speed-torque-fuel consumption model of engine and speed-torque-efficiency model of generator were established by linear interpolation.The oil consumption-electricity conversion efficiency was got later.Finally,the optimization of range extender working point was realized by vehicle power control strategy based on Genetic Algorithm.Verification results show that the model and method used in the article can realize the working point optimization control of the range extender of electric vehicle.The fuel economy and CO,HC emission problems of range extended electric vehicle is reseached in this paper.Firstly,the problem can be convert to simple target by normalization and weighted average.The modeling and simulation of a range extender fuel economy and CO,HC emission based on map are conducted with MATLAB and GUI with the motor external characteristic,actual power demand and other parameters as constraint.Modified Differential Evolution algorithm is used to solve the problem.Finally,experimental verification of fuel economy and CO,HC emission solved by the proposed approach is performed by bench under HWFET driving cycles.The experiment results show that the proposed approach aiming at fuel economy and CO,HC emission optimization can control engine speed and generator torque according to fuel consumption rate optimization in real-time and accurately to improve vehicle fuel economy and reduce CO,HC emission effectively.