PEM电解制氢热管理建模及解耦控制设计与优化

doi:10.11949/0438-1157.20250937

摘要/Abstract

摘要：

质子交换膜（PEM）电解制氢具有效率高、响应快、电流密度高、可调范围广的优点，是适应可再生能源波动制氢的重要技术。温度控制是直接影响PEM电解制氢耐久性、输出性能及可靠运行的关键因素。为实现电解制氢温度和温差的快速精确控制，建立了面向控制的PEM电解制氢系统时滞数学模型并进行线性化和频域模型转化，针对电解槽温度和温差控制强耦合、动态响应慢的问题，提出了基于前馈解耦的自适应模糊PID优化控制策略，并基于100kW电解制氢装置完成了系统模型验证和控制策略仿真对比分析。结果表明，所提控制策略在波动工况下能使电解制氢温度和温差保持稳定，温度/温差调节时间分别加快65.75s与66.5s，并且具备较强的抗干扰能力，最大偏差在±0.5℃内。

关键词: 制氢, 模型, 控制, 前馈控制, 模糊控制

Abstract:

Proton Exchange Membrane (PEM) electrolysis for hydrogen production, recognized for its high efficiency, rapid response, elevated current density, and wide adjustable range, has emerged as a pivotal technology adapting to the fluctuations of renewable energy. Temperature control is a critical factor directly influencing core component durability, operational states, and system performance. To achieve rapid and precise control of electrolytic stack temperature and temperature difference, this study establishes a control-oriented time-delay mathematical model for PEM electrolysis systems, subsequently linearized and converted into frequency-domain representations. Addressing challenges including strong coupling between temperature and temperature difference control, significant fluctuations, and sluggish dynamic response, an adaptive fuzzy PID optimization control strategy based on feed-forward decoupling is proposed. System model validation and comparative simulation analysis of control strategies have been completed utilizing 100kW PEM electrolysis facility. The results demonstrate that the proposed control strategy can effectively maintain stable hydrogen production temperature and temperature difference under fluctuating operating conditions. Specifically, the temperature and temperature difference adjustment times are reduced by 65.75 s and 66.5 s, respectively, while exhibiting strong anti-interference capability, with a maximum deviation confined within ±0.5°C.

Key words: hydrogen production, model, control, feed-forward control, fuzzy control

中图分类号:

TQ 028.8

梁丹曦, 俎焱敏, 宋洁, 柯绍杰, 徐桂芝, 侯坤, 梁立晓, 赵子泰, 张永生. PEM电解制氢热管理建模及解耦控制设计与优化[J]. 化工学报, DOI: 10.11949/0438-1157.20250937.

Danxi LIANG, Yanmin ZU, Jie Song, Shaojie KE, Guizhi XU, Kun HOU, Lixiao LIANG, Zitai ZHAO, Yongsheng ZHANG. Thermal management modeling and decoupling control design and optimization for PEM electrolytic hydrogen production system[J]. CIESC Journal, DOI: 10.11949/0438-1157.20250937.

图/表 16

图1 电解制氢系统水热回路结构示意图

Fig.1 Schematic diagram of the water and thermal circuit structure of the electrolytic hydrogen production system

图2 电解制氢系统水热回路能量流图

Fig.2 Energy flow diagram of the water and thermal circuit of the electrolytic hydrogen production system

图3 双变量前馈补偿解耦控制结构

Fig.3 Dual variable feedforward compensation decoupling control structure

图4 前馈解耦-模糊PID控制结构

Fig.4 Feedforward decoupling fuzzy PID control structure

图5 模糊控制器原理

Fig.5 Principle of Fuzzy Controller

图6 模糊PID控制隶属度函数曲线

Fig.6 Fuzzy PID control membership function curve

图7 模糊控制输入输出映射关系

Fig.7 Fuzzy control input-output mapping relationship

图8 PEM 电解制氢 Simulink 仿真模型及实验装置

Fig.8 Simulink simulation model and experimental system for PEM electrolysis hydrogen production

图9 实验值与模型仿真值对比

Fig.9 Comparison between experimental values and model simulation values

图10 不同控制策略电解槽温度和温差的变化

Fig.10 Changes in temperature and temperature difference of electrolytic cells under different control strategies

图11 不同控制策略电解槽入口温度变化放大: (a)400s；(b)800s；(c)1200s；(d)1600s

Fig.11 Amplification of inlet temperature changes in electrolytic cells with different control strategies: (a)400s；(b)800s；(c)1200s；(d)1600s

图12 不同控制策略电解槽温差变化放大: (a)400s；(b)800s；(c)1200s；(d)1600s

Fig.12 Amplification of temperature difference changes in electrolytic cells with different control strategies: (a)400s；(b)800s；(c)1200s；(d)1600s

图13 不同控制策略温度温差ISE值

Fig.13 ISE value of temperature difference under different control strategies

表1 电解制氢系统在波动工况下温度和温差动态响应指标

Table 1 Dynamic response indicators of temperature and temperature difference in electrolytic hydrogen production system under fluctuating operating conditions

目标		指标	控制策略	升载一 t=400s	降载一 t=800s	降载二 t=1200s	升载二 t=1600s
入口温度	60℃	超调量（℃）	PID	0.206	-0.163	-0.252	0.085
			前馈解耦	0.147	-0.112	-0.173	0.06
			前馈+模糊PID	0.061	-0.043	-0.069	0.023
		调节时间（s）	PID	122	118	129	101
			前馈解耦	99	96	105	53
			前馈+模糊PID	52	51	58	46
温差	5℃	超调量（℃）	PID	0.266	-0.215	-0.34	0.113
			前馈解耦	0.185	-0.149	-0.235	0.078
			前馈+模糊PID	0.089	-0.072	-0.109	0.036
		调节时间（s）	PID	168	155	181	157
			前馈解耦	142	136	164	119
			前馈+模糊PID	107	92	120	76

图14 不同比热容波动工况下前馈解耦-模糊PID控制

Fig.14 Feedforward decoupling fuzzy PID control under different specific heat capacity fluctuation conditions

图15 典型调峰工况下温度温差动态响应

Fig.15 Dynamic response of temperature and temperature difference under typical peak shaving conditions

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