Research On Uncertainty Energy Management Strategy For Hybrid Electric Vehicle

Hybrid electric vehicle technology is an effective way to solve the current energy shortage and environmental pollution problems.With the assistance of energy management strategies,it is a very important topic to fully explore the fuel economy of hybrid electric vehicles.Therefore,energy management strategies are of great significance in the simulation and design of hybrid electric vehicles.Previous studies are based on deterministic system parameter models,without considering the uncertainty of system parameters in actual working conditions,such as rolling resistance coefficients,etc.To this end,this paper introduces the uncertainty analysis method into the energy management strategy research by modeling the uncertainty of the hybrid electric vehicle system and the uncertainty propagation.Proposing the uncertain energy management strategy based on real-time optimization and the uncertain energy management strategy based on global optimization to improve the fuel economy and system robustness of hybrid electric vehicles.The specific research work is as follows:(1)Completed hybrid electric bus system modeling and uncertainty propagation analysis,which can quickly and effectively obtain the uncertainty of vehicle demand power.First,a fuel cell hybrid electric bus is taken as the research object,and its simulation model for energy management is established.Secondly,it analyzes the source of uncertainty in the passenger car system and completes its uncertainty modeling.Finally,the uncertainty propagation method based on the point estimation and the maximum entropy principle is used to quickly obtain the uncertainty of the demand power at each time under a given working condition,and its accuracy and efficiency are verified by the Monte Carlo method.(2)Developed an uncertain energy management strategy based on real-time optimization to further explore the fuel economy of hybrid electric vehicles.After implementing the power follow-up energy management strategy for hybrid electric buses,the strategy based on the Equivalent Consumption Minimization Strategy(ECMS)is studied and its application in hybrid electric vehicles is realized.Through the Monte Carlo simulation method,the uncertainty demand power sample generation,simulation and ECMS solution are performed at each control time,and the solution results are statistically analyzed to obtain the final energy distribution results.The simulation results show that the uncertain energy management strategy based on realtime optimization has better fuel economy than the power follow strategy.(3)Developed an uncertain energy management strategy based on global optimization to improve the practical application ability of energy management strategies.First realized the application of dynamic programming in the energy management of hybrid electric vehicles.Then introduce the demand power uncertainty propagation result.On the one hand,combining the optimal energy allocation results obtained by dynamic programming and the uncertainty propagation results,formulating a rule-based uncertainty allocation method provides an effective solution when the actual power demand of the vehicle deviates from the theoretical power demand in the actual driving process,and improve the practical application ability of energy management strategies.On the other hand,in theoretical research,Monte Carlo simulation is used to generate multiple sets of random simulation working conditions that meet the uncertainty demand power probability distribution,and dynamic programming is used to solve the global optimal energy distribution of each random simulation working condition,and the results conduct statistical analysis.The simulation results show that its fuel economy is slightly higher than the uncertain energy management strategy based on real-time optimization and the power follow strategy.