车用大功率质子交换膜燃料电池堆变负载电流下湿度控制

doi:10.3969/j.issn.1674-8484.2025.01.013

摘要/Abstract

摘要：

为解决大功率质子交换膜燃料电池（PEMFC）变负载电流下湿度超调大的问题，该文对电池堆阴极流场湿度和阳极流场湿度均使用模糊自抗扰控制（ADRC）算法。根据水蒸气在电池堆内部的变化机理，建立了额定功率为 150 kW 的电池堆湿度模型并验证其准确性；随后分析比例-积分-微分（PID）算法的缺陷；最后以加湿器水质量流量为控制变量，对阴极流场湿度和阳极流场湿度均采用ADRC和模糊ADRC算法进行研究。结果表明：电流阶跃绝对幅度为50 A时，相比于PID，ADRC 和模糊ADRC控制下的阴极流场湿度超调量分别减小15.5%和16.3%，阳极流场湿度超调量均减小70.3%；电流阶跃绝对幅度为100 A时，ADRC和模糊ADRC控制下的阴极流场湿度超调量分别减小45.0%和47.5%，阳极流场湿度超调量分别减小92.3%和92.4%。本研究揭示了大功率电池组湿度变化的机理，提出了保持水稳定性的方法，从而有效缓解电池组“水淹”和“膜干”问题。

关键词: 质子交换膜燃料电池（PEMFC）, 湿度控制, 比例-积分-微分（PID）, 模糊自抗扰控制（ADRC）

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)

中图分类号:

TM911.4

兰子剑, 代晓芳, 刘青山, 陈轶嵩, 付佩. 车用大功率质子交换膜燃料电池堆变负载电流下湿度控制[J]. 汽车安全与节能学报, 2025, 16(1): 127-135.

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.

图/表 12

参考文献 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