Adaptive Energy Management Strategy For Fuel Cell Hybrid Bus

Fuel cell is a clean and efficient energy source with great development potential,the vehicle economy and battery life are the key factors restricting its commercial development.The response speed of the output power of the fuel cell is relatively slow,so it is usually required to cooperate with the power battery to meet the rapid response of the vehicle’s power demand,that is,the vehicle is driven by the fuel cell-power battery hybrid.One of the key technologies of fuel cell hybrid electric vehicle is to formulate reasonable energy management strategies,which can improve the working efficiency of fuel cell,improve the economy of vehicle,and increase the service life of fuel cell.In this paper,based on the national key research and development project "Commercial-oriented fuel cell bus vehicle integration and demonstration operation",this paper starts from the principal analysis,through the method of system modeling and simulation test,the fuel cell bus from the specific parts to the vehicle system model building and integration.To the model building and integration of the vehicle system;and propose a vehicle energy management strategy for the built vehicle system,distribute multiple energy sources of the vehicle,and verify the rationality and prominence of the control strategy.First of all,based on the experimental data and the working environment and principles of fuel cell buses,this paper builds models of key parts such as the vehicle dynamics model,motor energy consumption model,fuel cell efficiency model,and power battery model in the MATLAB/SIMULINK environment.Through simulation analysis,the energy consumption performance of the fuel cell bus system under different operating conditions can be obtained,and as a result,the energy management control strategy of the whole vehicle can be further designed and analyzed.Then,according to the actual working conditions of the fuel cell bus,the route can be approximated as a given working condition,and under the given working condition,two energy management strategies combining rules and optimization algorithm are proposed,and the control rules are improved by the optimization algorithm.At present,most of the researches on fuel cell energy management strategies are aimed at economy,and there is a lack of energy management strategies that consider the life of fuel cells.In this paper,the fuzzy control strategy and genetic algorithm are combined with each other,which not only uses the excellent characteristics of fuzzy control not relying on precise mathematical models,but also combines the optimization ability of genetic algorithm.At the same time,sequential quadratic programming algorithm is used to optimize the strategy based on simple rules,and good results are also obtained.Finally,in order to better simulate the actual situation,clustering analysis algorithm was used to select four types of typical operating conditions to represent different routes,an adaptive fuel cell bus energy management strategy based on SCG-BP neural network working condition recognition was adopted.The simulation results show that the strategy can show good adaptability and the vehicle performance while the consumption is reduced,it also reduces the number of substantial load changes of the fuel cell output power,showing good adaptability and economy.