| Fuel cell is an ideal energy source for electric vehicles with high efficiency and no pollution.However,because of its slow dynamic response and soft power characteristics,it is necessary to combine it with new energy storage devices such as battery or supercapacitor to form a composite energy storage fuel cell system.At present,the most promising hybrid energy storage fuel cell system is a three-energy source system with fuel cell,battery and supercapacitor.This hybrid system maximizes the advantages of each component,but at the same time,it will increase the difficulty of system control.In addition,the short energy source life and high system production cost are the main reasons to prevent its commercialization.In this paper,the three-energy source system is taken as the research object.Considering the vehicle energy consumption and the energy source life,the parameter matching analysis and optimization of the three energy sources system and the energy management strategy research are carried out.Specific research contents are as follows:(1)The configuration scheme of the three-energy source system is determined,and the characteristics of fuel cell,battery,supercapacitor and other components are analyzed.A Matlab/Simulink simulation model of the three energy sources system including the fuel cell and lithium battery life attenuation model is established.(2)Considering vehicle energy consumption and energy source life,dynamic programming(DP)strategy is used to analyze the influence of different parameter configurations and control strategies on vehicle comprehensive operating cost under different cycles.Genetic algorithm is used to optimize the parameter matching of fuel cell system with composite energy storage.The optimal parameter configuration of the three energy sources system under the DP strategy is obtained with the objective of minimizing the comprehensive operating cost of vehicles under the comprehensive cycle.(3)The influence of the power supply sequence on the vehicle energy consumption economy and energy source life is explored when formulating the rule strategy for the three-energy source system.Based on the analysis of the power sequence provided by energy sources under different accelerations,an adaptive rule strategy based on vehicle state recognition is proposed.Based on the sensitivity analysis,the influence of many control parameters in the adaptive rule strategy on the comprehensive operating cost of the vehicle is analyzed,and the key control parameters are optimized by using genetic algorithm.The feasibility and effectiveness of the adaptive rule strategy and sensitivity analysis are verified by comparing the simulation results before and after optimization.(4)In order to improve the utilization rate of the ultracapacitor and prolong the fuel cell and battery life,a multi-objective hierarchical energy management strategy is designed based on the analysis of the law of DP strategy.In the upper strategy,the generalized regression neural network is used to learn the rules of the output power of the ultracapacitor and the demand power under the DP strategy,and the ultracapacitor output power is obtained according to the offline learning results.In the lower level strategy,the power of fuel cell and battery is allocated by using ECMS strategy,and the equivalent factor is calculated according to the optimal control parameters of each component under DP strategy in several cycles.The effectiveness of this strategy is verified by simulation results.In order to further improve the performance of the hierarchical energy management strategy,the hierarchical energy management strategy is optimized based on the results of vehicle speed prediction.The simulation results show that the optimized hierarchical energy management strategy has improved in terms of vehicle comprehensive economy. |
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