Optimal Design And Energy Management Of Power System For Full-power Fuel Cell Vehicle

Full-power fuel cell vehicle has become a research hotspot with its advantages of excellent energy and environmental protection performance,good market prospect and strong support of national policies.The existing research on parameter matching of fuel cell vehicle is mainly focused on the energy hybrid fuel cell vehicle and power hybrid fuel cell vehicle,but less on full-power fuel cell vehicle.In addition,the fuel cell has a higher energy conversion efficiency because it does not have the restriction of the Carnot cycle,which in turn makes the vehicle obtain better economy.However,how to further improve the vehicle economy by optimizing the powertrain design and energy management strategy is still an urgent problem in the process of independent research and development.In view of the above analysis,the full-power fuel cell vehicle is taken as the research object of this paper,and the optimization design and energy management of its power system are studied.First of all,based on the research of dynamic design index and existing matching theory,a parameter matching method for the power system of full-power fuel cell vehicle is proposed,and the rationality of the method is verified by the forward matching of typical full-power fuel cell vehicle Toyota Mirai.At the same time,with the aid of Advisor simulation software,the rationality of the parameters obtained by the matching is further verified.The proposed matching method develops the matching theory of full-power fuel cell vehicle well,and has certain reference significance for the integrated design of full-power fuel cell vehicle power system.Secondly,based on the requirement of economic index,the energy-saving analysis and optimization design method of full-power fuel cell vehicle power system are given.Based on the proposed theoretical hydrogen consumption model,the effects of fuel cell efficiency,drive motor efficiency,rolling resistance coefficient,curb weight,regenerative braking ratio on vehicle economy are analyzed quantitatively,and according to the obtained quantitative analysis results,the optimization matching method of the key component parameters of the power system is given under the premise of meeting certain economic indicator.In addition,based on the proposed ergodic weight coefficient dynamic programming method,the advantages and disadvantages of the current energy management strategy are measured.The influence degree of energy management strategy on economy and the essence of optimizing energy management strategy are determined.The optimization design and dynamic planning analysis based on the economic index reveal the effective ways to improve the economy from the two aspects of parameter matching and energy management,which has certain guiding significance for the parameter matching of power system and the formulation of energy management strategy.Thirdly,based on the characteristics of full-power fuel cell vehicle,the advantages and disadvantages of existing energy management strategies are analyzed and the power follow strategy is selected.At the same time,according to the shortcomings of power follow strategy,a power follow control strategy based on Fuzzy correction is proposed.In addition,in view of the difficulty and the poor adaptability to working conditions in calibrating the key control parameters in the control strategy,a learning vector quantization neural network is used to identify the working conditions,and the adaptive online adjustment of the key control parameters is carried out based on the results of the working conditions identification.For the characteristic parameters used in working condition recognition,it is obtained through the proposed difference degree that is based on the K-means clustering algorithm.For the key control parameters to be adjusted online,it is obtained by using multi-island genetic algorithm for offline optimization under different kinds of working conditions.In order to verify the correctness,validity and real-time of the developed model and energy management strategy,offline simulation and hardware in the loop test are carried out respectively.Firstly,the simulation results of Simulink self-built model and advisor model are compared to verify the correctness of the developed vehicle model,driver model and power follow control strategy model.Then,fuzzy control,condition identification and optimization are added to the power following control strategy to improve the fuel economy,and the effectiveness of the improved method is proved by offline simulation.Finally,the real controller and real-time simulator are used to build the hardware in the loop test platform and carry out the hardware in the loop test for the developed strategy to verify the real-time performance.