| Energy saving, environmental protection and safety remain the three subjects intoday's world. With the development of modern technology, automobiles are becoming oneof the main traffic tools for peoples, but they also consume a large of oils. For example,automobiles consume 45% of the total oil consumption, and produce 7080% of the totalpollutants in Beijing in 2005. So, it is of great significance for us to release the energypressure and improve the air quality of city by taking efficient measures to reduce emissionsof vehicle. One of the most important researches on modern vehicle technologies focuses onhow to improve its performances and reduce the fuel consumption and emissions of vehicles.In the past ten year, some new technologies have become the hotspot because it comepossible to solve the above problems for electric vehicle, hybrid electric vehicle and fuel cellelectric vehicle etc. In a short run, the hybrid propulsion system may become the substituteof low emission vehicle (LEV), ultralowemission vehicle (ULEV) and zeroemissionvehicle (ZEV) because of its potentials in reducing emissions and bettering performances ofvehicle.The research of control strategy is the core of the hybrid electric vehicle, and it's alsothe crux of HEV's design and research at present. Compared with conventionaldeterministic rulebasedcontrol strategy, fuzzy control strategy is based on the expertexperiments to determine the fuzzy rules, and it has good control effect with bright future.Also, fuzzy control has its changeability because of expert experiments. Genetic algorithm isa feasible optimization method that has been used in multiobjectiveand nonlinearproblem.So, fuzzy control strategy is tuned by genetic algorithm and generates geneticfuzzycontrolstrategy, then it was used in actual control problem.HEV control strategies had been analyzed in this thesis and then summarized the formof control strategies and control targets. Geneticfuzzylogic control strategy has beenchoosed to constitute energy management system (EMS) in parallel hybrid electric vehicle.Then we analyzes the simulation results. The main contents are as follows: Firstly, the thesis analyzes the important of HEV control strategy research in detail,putting forward control target in HEV, categorizing elucidation the HEV control strategyfrom the angle of these control targets existed, at the same time this thesis involves thecurrent control strategy for a brief introduction.Firstly, the thesis analyzes the important of HEV control strategy research in detail,putting forward control target in HEV, categorizing elucidation the HEV control strategyfrom the angle of these control targets existed, at the same time this thesis involves thecurrent control strategy for a brief introduction.Secondly, the simulation models of parallel HEV and power train is builded inMATLAB/Simulink and ADVISOR2002, to make the foundation for the future research anddevelopment.Thirdly, the thesis construes torque distribution fuzzy controller in parallel hybridelectric vehicle. The design and research of parallel HEV fuzzy logic control strategy isbased on parallel HEV driving system and HEV logic threshold control strategies, using thefuzzy logic control to complete the design of control algorithm. In this thesis, fuzzy logiccontrol strategy has been systematically introduced and builded fuzzy logic control systemfor parallel HEV.Finally, geneticfuzzycontrol strategy is used in parallel HEV. The model is simulatedin ADVISOR environment, and research is done about optimized results. Different drivecycles, NEDC and UDDS, are used in simulation and results are analyzed. It has been findout that, compared with fuzzy logic control strategy, geneticfuzzycontrol strategy can getbetter control effects. The effectiveness of this approach can reduce fuel consumption andemissions without sacrificing vehicle performance.
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