| Fuel cell vehicles(FCV)have received extensive attention due to their high energy conversion efficiency,low noise,and clean emissions.However,in the current complex working conditions of fuel cells,frequent start-stops and variable load phenomena often occur.The catalyst and carbon carrier inside the fuel cell will accelerate decay under the influence of these unfavorable working conditions,which indirectly affects the durability of the fuel cell.Aiming at the problem of fuel cell life accelerating attenuation due to frequent start and stop and variable load,this paper combines fuzzy control theory with moving maximum and moving average algorithms,and proposes a hybrid energy management strategy with the goal of reducing frequent start-stops and substantial load changes of fuel cells.The specific work is as follows:(1)The different power system architectures of fuel cell logistics vehicles are compared,and the fuel cell and power battery structure was selected.According to the performance requirements of a certain 4×2 fuel cell logistics vehicle,the parameters of power system components such as hydrogen fuel cells were matched,and its model was selected.The vehicle’s dynamic performance parameters were verified,and the results showed that the matched fuel cell logistics vehicle can reach a maximum speed of about 103km/h,which is greater than the indicator’s 90km/h;when the fuel cell logistics vehicle speed is within 24km/h,its gradeability is greater than 20%,which meets the requirement of a maximum gradeability of 20% at a full load of 20km/h;the 50km/h acceleration time of the fuel cell logistics vehicle is 7.27 s,and meet the vehicle performance requirements from 10 s to 50km/h.(2)According to the vehicle parameters of the fuel cell logistics vehicle,the vehicle model of the fuel cell logistics vehicle is built;according to the working principle of the power system components of the fuel cell logistics vehicle,the power system model is built.Based on the fuzzy control principle,moving maximum and moving average algorithms,a hybrid energy management strategy model for fuel cell logistics vehicles is built.(3)The fuel cell output power of the hybrid energy management strategy,state machine strategy and power follower strategy were compared under the urban cycle driving schedule(Urban Dynamometer Driving Schedule,UDDS).The results show that the hybrid energy management strategy improves the efficiency of the fuel cell.Effectively reduce the switching and frequent load changes of the fuel cell,and reduce the time that the fuel cell is in unfavorable working conditions;compares the state machine strategy,power follow strategy,fuzzy control strategy and hybrid energy management strategy Smoothness,the results show that the smoothness of the state machine strategy,power follow strategy,fuzzy control strategy and hybrid energy management strategy are 117.9,92.6,48 and 22.This proves that the hybrid energy management strategy can greatly reduce the degree of load change of the fuel cell output power;the equivalent hydrogen consumption per 100 kilometers of hybrid energy management strategy,state machine strategy and power follow strategy are compared in different working conditions.The results show that: Compared with the state machine strategy and the power following strategy,the economics of the hybrid energy management strategy proposed in this paper are increased by 13.33% and 9.25%.(4)The Raspberry Pi was selected as the hybrid energy management strategy controller,and the hybrid energy management strategy was coded and embedded in the controller;UDP was selected as the data transmission protocol between the controller and the computer,cosimulated the controller and Simulink,and compared their fuel cell and power battery demand power curves in 200 s of UDDS operating conditions.The results showed that the results of the controller simulation and Simulink simulation are consistent,which proves that the hybrid energy management strategy has certain practical value. |
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