Research On Energy Optimization Strategy Of Parallel Hybrid Electric Vehicle

With the increasingly serious problems of environmental pollution and energy shortage,Hybrid electric vehicle(HEV),which combines the advantages of traditional fuel vehicle and pure electric vehicle,has become the most promising vehicle at present.HEV refers to a vehicle whose power system is composed of two or more power sources.As a multi-energy vehicle,the energy control strategy of hybrid electric vehicles determines its performance,which is the main factor to judge the merits of vehicle.Taking parallel hybrid electric vehicle(PHEV)as the research object.Fuzzy logic control theory and genetic algorithm are used to research the energy control strategy.The main work is as follows:(1)The modeling method of HEV is introduced in this paper,and combines ADVISOR simulation software,the mathematical models of the whole vehicle dynamics,engine,motor,battery,wheel and other modules of PHEV are established.(2)According to the working mode of PHEV,an electric assist control strategy based on logic threshold is designed,then aimed at the deficient of its simple control,only promise the efficiency of the engine,without considering the motor efficiency,the fuzzy logic control is used to design a fuzzy logic control strategy which considering the motor speed factor,the fuzzy controller taking the difference value ?T between the required torque of the whole vehicle and the optimal torque of the engine at the current speed,the SOC of the battery and the motor speed as the inputs,the engine output torque factor K as the output.Simulation results show that the fuzzy logic control strategy is better in the fuel economy and emissions.(3)Aiming at the deficient of strong subjectivity of fuzzy controller design,unable to achieve the optimal,an improved adaptive genetic algorithm(IAGA)is used to optimize the membership functions parameters and control rules of fuzzy controller.In the algorithm,a kind of evaluation index is designed to reflect differences between relatively optimal individual of population in each generation,to improve crossover and mutation probability,and in the fitness function calculation,weighting method is used to converted the multi-objective optimization into single objective optimization problem,using combination weighting method of collective subjective and objective factors to determine the weight value of each target,the subjective weighting method use a method of determining the linear combination weights based on entropy,the objective weighting method use the entropy weight method,finally,using the linear weighting method for combined empowerment.Simulation results show that the optimized fuzzy logic control strategy is better than before,which proves the effectiveness of the optimized fuzzy controller.