Journal of Jilin University(Engineering and Technology Edition) ›› 2020, Vol. 50 ›› Issue (1): 36-43.doi: 10.13229/j.cnki.jdxbgxb20180966

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Energy management strategy of fuel cell bus based on Pontryagin′s minimum principle

Zhe WANG1,2(),Yi XIE1,2,Peng-fei ZANG1,2,Yao WANG1,2   

  1. 1. School of Automotive Studies, Tongji University, Shanghai 201804, China
    2. Clean Energy Automotive Engineering Center, Tongji University, Shanghai 201804, China
  • Received:2018-09-21 Online:2020-01-01 Published:2020-02-06

Abstract:

An energy management strategy for fuel cell bus is designed based on the Pontryagin’s minimum principle, in which the fuel cell power is set as the control variable, minimal fuel consumption is taken as the objective function, and the durability of fuel cell is considered as the constraint. An on-line energy management strategy is designed with improving the Pontryagin’s minimum principle in order to adapting to different operating conditions. A fuel cell bus simulation model is built. The simulation results show that the energy management strategy can adapt to different operating conditions well, and it is better than the traditional on/off energy management strategy in terms of fuel economy and fuel cell durability.

Key words: vehicle engineering, fuel cell bus, on-line energy management strategy, Pontryagin′s minimum principle, fuel economy, durability of fuel cell

CLC Number: 

  • U461.8

Fig.1

Powertrain system structure of fuel cell bus"

Fig.2

Power?efficiency curve of fuel cell"

Fig.3

Rint equivalent circuit"

Fig.4

Solution process of Pontryagin’s minimum principle"

Fig.5

Relationship betweenλ(0) and |?SOC|"

Fig.6

Fuel cell bus forward simulation model"

Table 1

Parameters of powertrain system"

参数数值参数数值
整车整备质量/kg14 000主减速比7.72
燃料电池额定功率/kW60风阻系数0.65
燃料电池怠速功率/kW3.3迎风面积/m27.00
电机峰值功率/kW220车轮半径/m0.478
电机最高转速/(r·min-1)3 700滚阻系数0.015
电机最大转矩/(N·m)2 100电池容量/(A?h)120
电池峰值功率/kW187.2电池电压/V520

Fig.7

Simulation results of China City"

Fig.8

Simulation results of Shanghai City"

Fig.9

Simulation results of Nuremberg bus"

Table 2

Simulation results of China City"

统计结果开关模式极小值原理离线最优策略
|?SOC|0.0050.0040.000 5
大幅变载时间/s7.160.660.79
燃料电池功率变化率最大值/(kW?s-1)285.495.005.08
怠速时间/s372.580.90.9
启停次数500
燃料电池平均工作效率/%44.4653.0553.05
动力电池平均工作效率/%97.7798.3298.28

Table 3

Simulation results of Shanghai City"

统计结果开关模式极小值原理离线最优策略
|?SOC|0.0030.0080.000 7
大幅变载时间/s5.192.512.83
燃料电池功率变化率最大值/(kW?s-1)285.495.805.80
怠速时间/s289.010.90.9
启停次数300
燃料电池平均工作效率/%45.1652.7452.95
动力电池平均工作效率/%97.6198.1098.10

Table 4

Simulation results of Nuremberg bus"

统计结果开关模式极小值原理离线最优策略
|?SOC|0.00050.00030.00002
大幅变载时间/s4.4127.3722.16
燃料电池功率变化率最大值/(kW?s-1)285.495.805.80
怠速时间/s348.740.90.9
启停次数200
燃料电池平均工作效率/%43.4352.9753.03
动力电池平均工作效率/%97.1197.5297.54

Fig.10

Correction of terminal SOC value"

Fig.11

Fuel economy under different strategies"

1 衣宝廉, 侯明. 车用燃料电池耐久性的解决策略[J]. 汽车安全与节能学报, 2011, 2(2): 91-100.
Yi Bao-lian, Hou Ming. Solutions for the durability of fuel cells in vehicle applications[J]. Journal of Automotive Safety and Energy, 2011, 2(2): 91-100.
2 张来云. 增程式燃料电池汽车动力系统匹配及能量管理策略研究[D]. 上海:华东理工大学机械与动力工程学院, 2016.
Zhang Lai-yun. The power system matching and energy management strategy research of fuel cell range extender electric vehicle[D]. Shanghai: College of Mechanical and Power Engineering,East China University of Science and Technology, 2016.
3 谢星, 周苏, 王廷宏, 等. 基于Cruise/Simulink的车用燃料电池/蓄电池混合动力的能量管理策略仿真[J]. 汽车工程, 2010, 32(5): 373-378.
Xie Xing, Zhou Su, Wang Ting-hong, et, al. A Simulation on energy management strategy for the power system of a fuel cell/battery HEV based on Cruise/Simulink[J]. Automotive Engineering, 2010, 32(5): 373-378.
4 李熙, 谢勇波, 宋超,等. 基于T-S模糊控制的燃料电池客车能量管理策略及仿真分析[J]. 客车技术与研究, 2017, 39(4): 5-8, 39.
Li Xi, Xie Yong-bo, Song Chao, et al. Management strategy and simulation analysis on fuel cell bus energy based on T-S fuzzy control[J]. Bus & Coach Technology and Research, 2017, 39(4): 5-8, 39.
5 Ahn H S, Lee N S. Power distribution control law for FCHEV-a fuzzy logic-based approach[C]∥International Conference on Control and Automation, Budapest, Hungary, 2005.
6 徐陈锋. 基于自适应模糊策略的燃料电池车混合动力系统控制[D]. 杭州:浙江大学控制科学与工程学院, 2017.Xu Chen-feng. Adaptive fuzzy control for power management of fuel-cell-battery hybrid vehicles[D]. Hangzhou:College of Control Science and Engineering, Zhejiang University, 2017.
7 Fletcher T, Thring R, Watkinson M. An energy management strategy to concurrently optimise fuel consumption & PEM fuel cell lifetime in a hybrid vehicle[J]. International Journal of Hydrogen Energy, 2016, 41(46): 21503-21515.
8 张炳力, 代康伟, 赵韩, 等. 基于随机动态规划的燃料电池城市客车能量管理策略优化[J]. 系统仿真学报, 2008, 20(17): 4664-4667.
Zhang Bing-li, Dai Kang-wei, Zhao Han, et al. Optimized energy management strategy for fuel cell city bus based on stochastic dynamic programming[J]. Journal of System Simulation, 2008, 20(17): 4664-4667.
9 Zheng C H, Xu G Q, Park Y I, et al. Prolonging fuel cell stack lifetime based on Pontryagin's minimum principle in fuel cell hybrid vehicles and its economic influence evaluation[J]. Journal of Power Sources, 2014, 248: 533-544.
10 Chen H, Pei P, Song M. Lifetime prediction and the economic lifetime of proton exchange membrane fuel cells[J]. Applied Energy, 2015, 142: 154-163.
11 Pei P, Chang Q, Tang T. A quick evaluating method for automotive fuel cell lifetime[J]. International Journal of Hydrogen Energy, 2008, 33(14): 3829-3836.
12 Pei P, Yuan X, Li P, et al. Lifetime evaluating and the effects of operation conditions on automotive fuel cells[J]. Chinese Journal of Mechanical Engineering, 2010, 23(1): 66-71.
13 Pei P, Chen H. Main factors affecting the lifetime of proton exchange membrane fuel cells in vehicle applications: a review[J]. Applied Energy, 2014, 125: 60-75.
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