Hybrid Electric Vehicle Control Systems And Energy Management Strategy Study

The most challenging goals the automotive industry facing are energy crisis and environment pollution. The research on low energy consumption and low emissions vehicle has been involved in sustainable development of the country. Hybrid electric vehicle (HEV), which has combine many advantages of conventional vehicle and battery electric vehicle, such as low energy consumption, low emissions, long drive distance, mature technology, capable of mass production etc, is presently considered as a most promising kind of vehicle that alternate the conventional vehicle. Therefore, it is very important to study the key technologies of HEV.With the"Intelligent omni-directional hybrid electrical vehicle project"that sponsored by HongKong ITF, this study focuses on the following aspects: building the forward simulation model for a new kind of parallel HEV; developed a vehicle control unit (VCU) based on high performance DSP chip TMS320F2812 and implemented a multi operation modes switch control strategy on it. To optimize operation of HEV and get good fuel economy and emission reduction, the author presents several energy management strategies (EMS): EMS based on dynamic programming (DP); EMS based on stochastic dynamic programming (SDP); EMS based on neuro-dynamic programming (NDP). The author also gives a detailed comparison to the performance and characteristics among these three EMSs.First of all, a forward simulation model for the new kind of parallel HEV is constructed in MATLAB/Simulink environment using empirical modeling approach with the aid of theoretical modeling approach. It provides necessary simulation platform for the development of control strategy. Then the author designed multi-operation modes switch control strategy for this HEV. To verify the behavior of it, the parameters of transition rules are simulated based on the simulation model. The control strategy can be downloaded into the vehicle control unit (VCU) after being transferred to C code by automation code generation function of Matlab/RTW toolbox.VCU is the core component in a HEV system that is responsible to implement EMS, which assures the safe and efficient operation of HEV. Therefore the author designed a high performance VCU based on DSP chip TMS320F2812. It provides the hardware base to implement complex EMS algorithms. The road test has proved that the VCU can realize expect operation modes and switch between operation modes smoothly.The optimal EMS incorporates two substrategies: optimal gearbox shifting strategy and optimal torque split substrategy. This study applied DP approach to design EMS. The HEV EMS problem is modeled as a multi-stage decision problem given a certain driving cycle. Simulation results have shown that it can improve fuel economy evidently. Theoritically speaking, the results get by DP approach is the global optimal result. Therefore, its results can be used as a benchmark to evaluate the effect of other EMSs.As the limitation of DP approach that need to get the entire information of driving cycle beforehand, the results get by DP approach is meaningful to that driving cycle. To overcome this limitation, the author adopts SDP approach by modeling driver's power request as a Markov chain. The SDP problem can be solved by value iteration and policy iteration. The resulted SDP EMS takes the form of lookup table, which can easily implement in VCU in real time. It could be demonstrated that SDP EMS achieves very good results that lie within a few percent of the global optimal results. Compared with rule-based strategy, the SDP strategy can lead to ICE operation near optimal work zone. The average efficiency of ICE and EM are both improved evidently.Although overcome the limitation of DP approach, SDP approach will still suffer from"curse of dimensionality"in EMS design. That is, the computation and memory needed by value iteration and policy iteration will increase exponentially with the number of states. This will limit its application in engineering. To deal with this problem we adopt NDP to design EMS. Instead of solving the value function by iteration algorithms, NDP adopt neural network to approximate it, which decreases the computation evidently. Simulation results show that NDP EMS can get suboptimal results, which made NDP has distinct advantage in EMS design compared with DP or SDP.As the major key techniques, high performance VCU design and energy management strategy plays an important role in the intellectual property of HEV. The significance of this study lies in improving the domestic research and development of HEV and promoting the industrialization of HEV with self-owned intellectual property rights.