Research On Energy Distribution Control Strategy Of Parallel Hybrid Electric Vehicle

The problem of environmental pollution and resource shortage has become a worldwide problem that needs to be solved urgently.Compared with traditional vehicles,parallel hybrid vehicles have the characteristics of reducing fuel consumption and pollutant emissions,and have become the innovation direction and development hotspot of the automotive industry.The parallel hybrid vehicle is driven by two power sources of engine and motor.By exerting the respective operating advantages of the engine and the motor,the operating efficiency of the whole vehicle is improved,and the purpose of energy saving and emission reduction is finally achieved.The energy distribution control of the parallel hybrid vehicle is a key link to improve the operating efficiency of the vehicle and achieve fuel economy and reduce emissions.However,the engine and motor energy distribution control methods that can be practically applied today have only a logic threshold control method,and the desired control effect can hardly be achieved.The ADVISOR2002 simulation software is selected as the model construction platform,and the simulation model of the parallel hybrid vehicle is built using Matlab/simulink software.The simulation model can test the operation of parallel hybrid vehicle engines and motors under different operating conditions,as well as fuel consumption and pollutant emissions.The working characteristics of the parallel hybrid vehicle are analyzed.According to its working characteristics,the engine and motor energy distribution control strategy based on fuzzy control is designed.The established fuzzy controller is loaded into the simulation software for preliminary simulation test,and the simulation test results are analyzed.Since fuzzy rules and membership functions are formulated by human experience,often due to insufficient experience of controller designer,and fail to achieve a great control result.Genetic algorithm is an evolutionary algorithm that mimics biological evolution and it is suitable for further optimization of fuzzy controllers.The genetic algorithm is designed to optimize the fuzzy rules of the fuzzy controller and the optimization method of the membership function.The fuzzy controllers before and after optimization are compared and analyzed.The analysis results show that the operating efficiency of the engine and the motor are improved.The fuzzy controller optimized by the genetic algorithm realizes the intelligent energy distribution of the engine and the motor,not only the entire vehicle power characteristics can be satisfied but also the goal of the reduction of fuel consumption and pollutant emissions can be achieved.