Research On Vehcile Control Of Range Extended Electric Vehciles

Resource shortage and environment pollution are two big challenges in the world nowdays. Electric vehicle has many adavantages, such as zero emission, zero fuel consumption. However, the driving range of Pure Electric Vehicle is limited, Range Extended Electric Vehicle (REEV) make up this weakness and is considered as most promising kind of vehicle for industrialization. The design of energy management strategy in charge sustained of REEV is one of important part for vehicle development. Therefore the energy management strategy becomes the research focus for REEV.The thesis takes rotor range extended/charge change compatible electric vehicle research and industrialization as background. The forward simulation model REEV was founded. The research on energy optimal management strategy for charge sustained of REEV based on model predictive control was studied. The vehicle controller was designed and control software was programmed based on uC/OS-Ⅱ. The hardware in loop simulation test was implemented based on dSPACE vehicle controller and driving simulator. The main research work and conclusions were summarized as following:Based on Matlab/Simulink, the REEV forward simulation model was developed to provide the simulation and verification foundation of energy management strategy. The Auxiliary Power Unit (APU) model, battery model and motor model were founded by using experimental data. The vehicle dynamic model was founded based on physical logic of oarameters.A method of exponential function was proposed to predict torque of the wheel. The energy management strategy was established by the rolling optimization for power efficiency based on the combination of model predictive control algorithm and dynamic programming. The APU power horizon was got by rolling optimization. The simulation for energy management strategy was developed based on the REEV model under the NEDC. The results show that it has good fuel economy.The structure of control system was analysised. Vehicle controller was designed based on function desire and industrial standard. Control software was programmed based on uC/OS-Ⅱ real-time operating system. Control tasks were divided based on function require and response time.A testing bench based on dSPACE, vehicle controller and driving simulator was built and the model predictive control algorithm energy management strategy of REEV was implemented. The energy management strategy was further verified by the test.