Matching Optimization Of Power Train And Control Parameters For A Plug-in Parallel Hybrid Electric Vehicle

Plug-in Hybrid Electric Vehicle(PHEVs)is a hybrid vehicle whose battery packs can be charged by external power network.Compared to traditional hybrid buses,the PHEVs has a larger battery capacity,longer electric mileage,which has a much lower fuel consumption and emission.PHEV is one of the research hot spot in clean energy vehicle area.The fuel consumption and emission are determined by the parameters of power train, control strategy and their matching relationship. There are theoretical significance and application value to research the parameters of power train and control strategy. According to the requirements of vehicle performance and cycle driving power,several power trian parameter schemes are designed. The mathematical model of components of power train is established. Orthogonal test method is used,with the degree of hybridization, speed ratio,final rear ratio and vehicle control parameters chosen as orthogonal design factors. The best matching scheme of power train and control strategy parameters is acquired,with the minimal fuel consumption of vehicle driving cycle under 42 Chinese bus typical urban cycles as target.The simulation model of plug-in parallel hybrid vehicles with dual-clutch is established which based on Matlab/Simulink simulation platform that can be run in the Advisor. Simulation of vehicle performance and fuel economy are carried out, and the fuel consumption and engine operating spots layout and motor operating spots layout are acquired. The simulation results show that the parameters of power train and control by optimized can meet the performance demand, engine and motor are both working in good condition and in the optimal efficiency zone.The proper power distribution, start/stop of engine and motor,brake energy feedback,as well as maintaining SOC in the given zone can be realized reasonably based on control strategy.Fuel consumption is reduced by 5.58% by using orthogonal designing optimization for control parameters and power train.The effect of the mileage, curb mass and air drag coefficient on the vehicle was analyzed.