Simulation Optimization Research On Fuzzy Control Strategy Of P2 Configuration HEV Based On Genetic Algorithm

Human’s harsh requirements for economy and environment make the development of new energy vehicles an irresistible trend.At the current development stage,many key problems of battery technology have not been solved,so hybrid electric vehicles are the best choice for the development of new energy vehicles.As a basic configuration with good comprehensive performance and low difficulty among various configurations of HEV,P2 configuration has good practical value.However,at present,there are few relevant researches on P2 HEV,so it is of great significance to carry out research on it.This subject was mainly based on the traditional passenger car which has been tested and verified,the numerical simulation model of hybrid electric vehicle was built by combining this model and the structure principle of P2 configuration.With the goal of improving the fuel economy of vehicle,the fuzzy control strategy was designed and genetic algorithm was introduced to optimize it.The main research contents and results were as follows:(1)For a traditional passenger car,the engine universal characteristic test and the vehicle road NEDC cycle test were carried out respectively,and a large number of relevant test data were obtained.Based on the test data,the engine measured map module and the vehicle model were established.The whole vehicle model was verified.and the results showed that the simulation accuracy was within 5%,which verified the accuracy of the model.Then,the HEV numerical simulation model was built based on the traditional vehicle model and the structural principle of P2 configuration,and the modeling of its main components was comprehensively analyzed.(2)The fuzzy controller of the core of the fuzzy control strategy was designed with total demand torque and SOC as the input variables,engine torque as the output variables,and triangle as the membership function.The quantization factor and scale factor modules were established.the Simulink simulation model of fuzzy control system was built and it was coupled with the GT suite vehicle model.By comparing with the logic threshold control strategy,the results showed that the designed fuzzy control strategy reduced the fuel consumption of per 100 kilometers of the whole vehicle by 4.8%,which verified the superiority of the designed fuzzy control strategy.(3)Taking BSFC as the optimization goal,the membership function optimization based on genetic algorithm was realized through Matlab programming.By comparing the fuzzy control strategy before and after optimization,the results showed that the optimized fuzzy control strategy reduced the fuel consumption of per 100 kilometers by 4.5% under the premise of guaranteeing the dynamic performance of the vehicle basically unchanged,which basically realized the research purpose of this subject.The results of this research showed that using genetic algorithm to optimize the fuzzy control strategy can improve the performance of each component of hybrid electric vehicle,reduced the total fuel consumption of the whole vehicle,and achieved better energy saving and emission reduction effect.