Study On Energy Management Optimization Control Strategy Of Parallel Hybrid Electric Bus

Under the background of growing global energy and environmental problems, hybrid electric vehicle (HEV) has gotten extensive attention as an advanced car which can improve fuel economy and reduce emissions of the car. And this emerging technology also promotes the development of energy management strategy applicable to all types of vehicle at the same time. Of course, excellent energy management control strategy can realize the optimal allocation of the energy between the system components in order to obtain the best performance vehicle under the premise of meeting the vehicle dynamic performance indexes. And related work is done in this paper regarding the parallel hybrid electric vehicle as the research object, the main research content is as follows:First of all, the hybrid simulation platform is constructed based on the ADVISOR software. Match the powertrain parameters of key parts in dynamic power drive system in this paper. And then complete the model construction of the key components of the drive train system and the vehicle based on detailed analysis of vehicle dynamic model, the engine model, the motor model and the mathematical battery model applying the combination method of test and theoretical modeling, providing a good platform for the subsequent control strategy design and the of the vehicle performance simulation analysis.Secondly, starting from the instantaneous optimization algorithm of the vehicle energy management strategy, the instantaneous optimal torque distribution method based on equivalent consumption minimization strategy is proposed in this paper. With the introduction of key system parameters of battery charging and discharging equivalent factor, calculate the equivalent fuel consumption of battery power, and build the based on the instantaneous optimization objective function combining with the actual engine fuel consumption. Simulation results show that the proposed control algorithm can be implemented effectively in the optimal energy distribution of the engine and motor, and maintain the balance of battery SOC at the same time, provides a good theoretical basis and experimental conditions for the design of the adaptive control strategy based on driving cycle identification.Then, aiming at the problem of poor adaptability of hybrid electric bus driving cycle caused by serious inconsistencies between the typical driving cycle and the actual road conditions, a kind of adaptive control strategy based on the driving cycle recognition is designed in this paper. First of all, construct the typical working condition in line with the local actual driving road characteristics based on the independently researched and developt data acquisition and monitoring system in the group; Then carry on the on-line driving cycle identification using the fuzzy recognition algorithm, call and update the optimal control parameters in real time corresponding to the current vehicle driving modes for the real-time optimization of engine and motor power allocation. Simulation test results show that the control strategy improves the driving cycle adaptation, reduces the online real-time calculation, and can give full play to the advantages of adaptive control strategy, which has a broad application prospect.Finally, the global optimization control strategy based on dynamic programming algorithm is put forward to study the global optimization performance of the parallel hybrid electric bus in the text, and its simulation results are turned out to be the best theoretical fuel economy and the optimal control sequence of output power for the hybrid system. By comparing the analysis of simulation experiment on the fuel economy of energy management strategy on the driving cycle of UDDS, NEDC, and Dalian, the energy saving potential of the presented energy distribution control method is analyzed. The simulation results show that the instantaneous optimal control strategy based on ECMS and adaptive energy management strategy based on the driving cycle recognition proposed in this article can both improve the vehicle’s fuel economy effectively, having certain fuel-efficient potential.