Humidity control of automobile high-power proton exchange membrane fuel cell stack under variable loading currents

doi:10.3969/j.issn.1674-8484.2025.01.013

Abstract

Abstract:

To address excessive humidity overshoot in high-power proton exchange membrane fuel cells (PEMFCs) under variable load currents, a fuzzy active disturbance rejection control (ADRC) algorithm was employed for both the cathode and anode flow field humidity regulation. Based on the internal water vapor change mechanism within the battery stack, a humidity model for a 150 kW rated power PEMFC stack was developed and validated. Subsequently, the limitations of the proportional-integral-derivative (PID) control algorithm were analyzed. Finally, using the mass flow rate of the humidifier as the control variable, ADRC and fuzzy ADRC algorithms were applied to regulate the humidity of the cathode and anode flow fields. The results show that, for an absolute current step amplitude of 50 A, the humidity overshoot in the cathode flow field decreases by 15.5% and 16.3%, respectively, while in the anode flow field both of them decrease by 70.3%, compared to PID control. For an absolute current step amplitude of 100 A, the humidity overshoot in the cathode flow field was reduced by 45.0% and 47.5%, and in the anode flow field by 92.3% and 92.4%, respectively. This study reveals the mechanism underlying humidity changes in high-power battery stacks and proposes a method to maintain water stability, thereby effectively mitigating issues of “water flooding” and “film drying” in battery stacks.

Key words: proton exchange membrane fuel cell (PEMFC), humidity control, proportional-integral-derivative (PID), fuzzy active disturbance rejection control (ADRC)

CLC Number:

TM911.4

LAN Zijian, DAI Xiaofang, LIU Qingshan, CHEN Yisong, FU Pei. Humidity control of automobile high-power proton exchange membrane fuel cell stack under variable loading currents[J]. Journal of Automotive Safety and Energy, 2025, 16(1): 127-135.

Figures/Tables 12

References 27

[1]	邵志刚, 衣宝廉. 氢能与燃料电池发展现状及展望[J]. 中国科学院院刊, 2019, 34(4): 469-477.
	SHAO Zhigang, YI Baolian. Development status and prospect of hydrogen energy and fuel cells[J]. *Bull Chin Acad Sc*, 2019, 34(4): 469-477. (in Chinese)
[2]	谢雨岑. 基于深度学习的燃料电池性能衰退预测研究[D]. 成都: 电子科技大学, 2021.
	XIE Yucen. Research on performance decline prediction of fuel cell based on deep learning[D]. Chengdu: University of Electronic Science and Technology of China, 2021. (in Chinese)
[3]	WU Di, PENG Chao, YIN Cong, et al. Review of system integration and control of proton exchange membrane fuel cells[J]. *Electrochem Energ Re*, 2020, 3(3): 466-505.
[4]	ZHU Yun, ZOU Jianxiao, LI Shuai, et al. An adaptive sliding mode observer based near-optimal OER tracking control approach for PEMFC under dynamic operation condition[J]. *Int’l J Hydro Ener*, 2022, 47(2): 1157-1171.
[5]	Damour C, Benne M, Grondin-perez B, et al. A novel non-linear model-based control strategy to improve PEMFC water management-The flatness-based approach[J]. *Int’l J Hydro Ener*, 2015, 40(5): 2371-2376.
[6]	Van Nguyen T, Knobbe M W. A liquid water management strategy for PEM fuel cell stacks[J]. J Power Sources, 2003, 114(1): 70-79.
[7]	Rosanas-boeta N, Ocampo-martinez C, Kunusch C. On the anode pressure and humidity regulation in PEM fuel cells: A nonlinear predictive control approach[J]. *IFAC-PapersOnLin*, 2015, 48(23): 434-439.
[8]	Barzegari M M, Dardel M, Alizadeh E, et al. Reduced-order model of cascade-type PEM fuel cell stack with integrated humidifiers and water separators[J]. *Energ, 2016, 113*: 683-692.
[9]	FU Hao, SHEN Jiong, SUN Li, et al. Fuel cell humidity modeling and control using cathode internal water content[J]. *Int’l J Hydro Ener*, 2021, 46(15): 9905-9917.
[10]	SONG Yanpo, WANG Xiangwei. AI-based proton exchange membrane fuel cell inlet relative humidity control[J]. *IEEE Acces*, 2021, 9: 158496-158507.
[11]	徐彩前. 质子交换膜燃料电池建模与湿度优化控制[D]. 成都: 电子科技大学, 2022.
	XU Caiqian. PEM fuel cell modeling and humidity optimizing control[D]. Chengdu: University of Electronic Science and Technology of China, 2022. (in Chinese)
[12]	CHEN Xi, WANG Chunxi, XU Jianghai, et al. Membrane humidity control of proton exchange membrane fuel cell system using fractional-order PID strategy[J]. *Appl Ener, 2023, 343*: 121182.
[13]	CHI Xuncheng, CHEN Fengxiang, JIAO Jieran. Model-based observer for vehicle proton exchange membrane fuel cell humidity based on adaptive sliding mode estimation technique[J]. *Int’l J Hydro Ener*, 2024, 52: 750-766.
[14]	CHEN Xi, XU Jianghai, LIU Qian, et al. Active disturbance rejection control strategy applied to cathode humidity control in PEMFC system[J]. *Energ Conver Mana, 2020, 224*: 113389.
[15]	CHEN Xi, XU Jianghai, FANG Ye, et al. Temperature and humidity management of PEM fuel cell power system using multi-input and multi-output fuzzy method[J]. *Appl Therm Eng, 2022, 203*: 117865.
[16]	Tümer B, Yildiz D Ş, Arkun Y. Water and thermal management in PEM fuel cells using feasible humidity plots and model predictive controllers[J]. *Comput Chem Eng, 2025, 192*: 108905.
[17]	刘岩. 燃料电池系统电效率影响因素分析及其水热管理[D]. 长春: 吉林大学, 2020.
	LIU Yan. Analysis of factors influencing the power efficiency of fuel cell system and its hydrothermal management[D]. Changchun: Jilin University, 2020. (in Chinese)
[18]	WANG Zhen, WEI Dong, YE Hongji. Method for diagnosing state of hydrothermal management of fuel cell stack based on frequency secant angle[J]. *CIESC* , 2018, 69(10): 4371-4377.
[19]	FANG Ming, WAN Xinming, ZOU Jianxiao. Development of a fuel cell humidification system and dynamic control of humidity[J]. *Int’l J Energ Re*, 2022, 46(15): 22421-22438.
[20]	Pukrushpan J T, Peng H, Stefanopoulou A G. Control-oriented modeling and analysis for automotive fuel cell systems[J]. J Dyna Syst, Measure, Contr, 2004, 126(1): 14-25.
[21]	LI Qi, CHEN Weirong, LIU Zhixiang, et al. Development of energy management system based on a power sharing strategy for a fuel cell-battery-supercapacitor hybrid tramway[J]. *J Power Source, 2015, 279*: 267-280.
[22]	PENG Fei, REN Linjie, ZHAO Yuanzhe, et al. Hybrid dynamic modeling-based membrane hydration analysis for the commercial high-power integrated PEMFC systems considering water transport equivalent[J]. *Energ Conver Mana, 2020, 205*: 112385.
[23]	Saponaro G Z, Stefanizzi M, Franchini E, et al. Modeling and design of a PEM fuel cell system for ferry applications[R]. SAE Tech Paper, 2023-24-0145.
[24]	Tuset J K. Modelling and validation of a fuel cell electric bus[D]. Oslo: University of Oslo, 2021.
[25]	王恺. 车载质子交换膜燃料电池建模与进气系统控制研究[D]. 长春: 吉林大学, 2020.
	WANG Kai. Research on modeling of vehicle proton exchange membrane fuel cell and control of intake system[D]. Changchun: Jilin University, 2020. (in Chinese)
[26]	韩京清. 从PID技术到“自抗扰控制”技术[J]. 控制工程, 2002(3): 13-18.
	HAN Jingqing. From PID technique to active disturbances rejection control technique[J]. *Contr Engi Chi*, 2002(3): 13-18. (in Chinese)
[27]	张磊, 鲁凯, 高春侠, 等. 基于变增益自抗扰技术的机器人轨迹跟踪控制方法[J]. 电子学报, 2022, 50(1): 89-97. doi: 10.12263/DZXB.20200100
	ZHANG Lei, LU Kai, GAO Chunxia, et al. Path tracking control method of robot based on time-varying gain[J]. *Acta Elect Sin*, 2022, 50(1): 89-97. (in Chinese)

变量	电流密度 (A·cm^-2)	电迁移水流量 (10^-6mol·cm^-2·s^-1)	比值 10^-5
文献[25]	0.357	4.68	1.31
本文	0.36/0.40/0.46	4.73/5.26/6.58	1.31

变量	电流密度 (A·cm^-2)	电迁移水流量 (10^-6mol·cm^-2·s^-1)	比值 10^-5
文献[25]	0.357	4.68	1.31
本文	0.36/0.40/0.46	4.73/5.26/6.58	1.31

流场湿度	湿度PID参数拟合程度/ %	PID参数符号	数值
阴极	88	流场湿度比例常数，K_p,ca	2.727
		流场湿度积分常数，K_i,ca	3.629
		流场湿度微分常数，K_d,ca	0.418 3
阳极	92	流场湿度比例常数，K_p,an	2.963
		流场湿度积分常数，K_i,an	32
		流场湿度微分常数，K_d,an	0

流场湿度	湿度PID参数拟合程度/ %	PID参数符号	数值
阴极	88	流场湿度比例常数，K_p,ca	2.727
		流场湿度积分常数，K_i,ca	3.629
		流场湿度微分常数，K_d,ca	0.418 3
阳极	92	流场湿度比例常数，K_p,an	2.963
		流场湿度积分常数，K_i,an	32
		流场湿度微分常数，K_d,an	0

1阶非线性因子，α₁	0.5
2阶非线性因子，α₂	0.25
1阶比例系数，β₀₁	80
2阶比例系数，β₀₂	5
过滤因子，δ	0.05