Development Of A Powertrain System Control Strategy For XL2000 Mild Hybrid Electric Vehicle

With two challenges of energy sources shortage and environment pollution toglobal vehicle industry, new clean energy concept vehicle should be researched rightnow. Compared to traditional ICE vehicle, hybrid electric vehicle has not onlycharacters of ICE vehicle, but also advantages of electric vehicle, and HEV has muchperspective to improve fuel economics and reduce emission. At present, HEV hasbeen developed much widely in Japan, Europe and American, and in China HEV alsohas been developed very apace.Several typical HEV configurations are introduced in the thesis. With the projectof XL2000 HEV, a scheme of control modes based on a layered structure and energymanagement and torque distribution strategy for powertrain system of the mild HEVare brought forward in this thesis, which is very convenient to be realized. Drivingmode identification, energy management and torque distribution strategy areperformed sequentially by a powertrain controller according to driving operation andvehicle state.In order to evaluate the control strategy and optimize its key control parameters,a simulation model based on AVL CRUISE and MATLAB/SIMULINK is set up. Thesimulation results under different driving cycles indicate that the control strategy caneffectively improve equivalent fuel consumption of the mild HEV by over15.8%~28.5% with the battery's state of charge (SOC) balance control.In the bench test, through start, idle, load characteristics and dynamic couplingcharacteristic experiments, functions of the powtrain controller and the controlstrategy have been test, and validity of the strategy has been verified from result ofbench test. From the chassis dynamometer test, start characteristics, brakingregeneration function and fuel economics of drive cycles have been evaluatedprimarily. The targets of drivability and power performance have been well realized,and fuel economics of the NEDC driving cycle can reach 5.85 L/100km, which canbe further improved through more optimization of the control strategy.