Optimization Of Hybrid Electric Vehicle Control Strategy And HIL Test

As the energy crisis and environmental pollution problems continue to increase,China's requirements for fuel consumption and emissions of traditional fuel vehicles are getting higher and higher,forcing domestic major OEMs to develop new energy vehicles,thereby mitigating the environmental damage caused by vehicle exhaust.However,the power battery as the only power source has always restricted the development of pure electric vehicles,and the battery life of pure electric vehicles cannot fully meet the requirements.The hybrid vehicle uses two or more power sources,which can solve the problem of the short driving range of the pure electric vehicle.However,the structure of hybrid vehicles is relatively complicated,so good energy management strategies are particularly important.The vehicle control unit is the core of the hybrid vehicle,and its purpose is to control the energy management distribution between the internal combustion engine,the drive motor,the lithium ion battery and the ultracapacitor unit group,so as to ensure that the internal combustion engine works in the best effective area.Based on the premise of the vehicle's dynamic performance,the fuel economy of the hybrid vehicle is optimized and the emission value is minimized.The research object of this subject is a parallel hybrid electric vehicle.The goal is to design a relatively complete and practical fuzzy logic control strategy.The specific research content is as follows:1.This paper mainly studies the vehicle structure of hybrid vehicles,analyzes the characteristics of key components of the system,and determines the basic parameters and key component parameters of the vehicle;2.Developing a fuzzy control strategy and a vehicle system model,embed the developed fuzzy control strategy into the vehicle system model,simulate the vehicle system model offline,and analyze the fuel of the hybrid vehicle under NEDC and UDDS driving cycle consumption and emission values;3.Using the feature-based selection genetic algorithm to optimize the fuzzy control strategy that runs well in hybrid vehicles,to complete the optimization of the membership function parameters of the power distribution factor K_uc,and to complete the program design and simulation of the feature-based selection genetic algorithm in MATLAB,Obtain the fuel consumption and emission value of the hybrid vehicle under the NEDC and UDDS driving cycle;HIL hardware-in-the-loop test of the vehicle control unit,using the NI HIL/MATLAB platform to build a vehicle control unit simulation system,and complete the vehicle contro land the verification of the controller also proves the effectiveness of the fuzzy control strategy optimized feature-based selection genetic algorithm.Simulation and experimental results show that the optimized fuzzy control strategy can effectively reduce the fuel consumption and emissions of the entire vehicle.Under NEDC driving cycle,the fuel consumption of hybrid vehicles is reduced by 8.8%;HC in emissions is reduced by 14.7%,CO is reduced by 15.9%,and NOx is reduced by 17.9%;under UDDS driving cycle,hybrid vehicles fuel consumption has been reduced by 9.5%;HC in emissions has been reduced by 13.2%,CO has been reduced by 13.6%,and NO_x has been reduced by 15.5%.