针对质子交换膜电解槽（PEMEC）温度动态建模及控制问题,建立50 kW PEMEC电压模型,模型误差小于2.95%,在此基础上,建立电解槽热管理模型与效率模型;其次,结合变论域思想设计变论域模糊PID控制器,用于调节电解槽对外能量交换,使之工作在既定温度;最后,基于硬件在环实时仿真平台在负载扰动和参数变化的不同测试工况下进行验证,相较于传统PID和模糊PID控制,变论域模糊PID控制调节时间至少缩短10.3%,最大温度偏差最少降低7.1%,结果表明变论域模糊PID控制器不仅具有更快的动态响应速度,还具有更强的鲁棒性。
Abstract
To address the issue of temperature dynamic modeling and control for proton exchange membrane electrolyzer cell （PEMEC）,a 50 kW PEMEC voltage model is developed with a modeling error of less than 2.95%. Based on this model, thermal management and efficiency models of the electrolyzer are further established. Furthermore, based on the concept of variable universe, a variable universe fuzzy PID controller was designed to regulate the external energy exchange of the electrolyzer cell, ensuring its operation at the target temperature. Finally, verification was conducted on a hardware-in-the-loop real-time simulation platform under various test conditions including load disturbances and parameter variations. Compared to traditional PID control and fuzzy PID control, the variable domain fuzzy PID control demonstrated a reduction in adjustment time of at least 10.3% and a minimum reduction of 7.1% in the maximum temperature deviation. These results indicate that the variable domain fuzzy PID controller not only offers faster dynamic response but also demonstrates greater robustness.
关键词
制氢 /
电解槽 /
建模 /
硬件在环 /
温度控制
Key words
hydrogen production /
electrolytic cells /
modeling /
hardware-in-the-loop simulation /
temperature control
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 魏泓屹, 卓振宇, 张宁, 等. 中国电力系统碳达峰·碳中和转型路径优化与影响因素分析[J]. 电力系统自动化, 2022, 46(19): 1-12.
WEI H Y, ZHUO Z Y, ZHANG N, et al.Transition path optimization and influencing factor analysis of carbon emission peak and carbon neutrality for power system of China[J]. Automation of electric power systems, 2022, 46(19): 1-12.
[2] 林涛, 赵丹阳, 严寒. 风电消纳下多型号制氢机组阵列优化调度研究[J]. 太阳能学报, 2022, 43(11): 466-473.
LIN T, ZHAO D Y, YAN H.Research on optimal scheduling of multi-model hydrogen generator array under wind power consumption[J]. Acta energiae solaris sinica, 2022, 43(11): 466-473.
[3] 马晓锋, 张舒涵, 何勇, 等. PEM电解水制氢技术的研究现状与应用展望[J]. 太阳能学报, 2022, 43(6): 420-427.
MA X F, ZHANG S H, HE Y, et al.Research status and application prospect of PEM electrolysis water technology for hydrogen production[J]. Acta energiae solaris sinica, 2022, 43(6): 420-427.
[4] TRINKE P, BENSMANN B, HANKE-RAUSCHENBACH R.Current density effect on hydrogen permeation in PEM water electrolyzers[J]. International journal of hydrogen energy, 2017, 42(21): 14355-14366.
[5] KELLER R, RAULS E, HEHEMANN M, et al.An adaptive model-based feedforward temperature control of a 100 kW PEM electrolyzer[J]. Control engineering practice, 2022, 120: 104992.
[6] QI R M, LI J R, LIN J, et al.Design of the PID temperature controller for an alkaline electrolysis system with time delays[J]. International journal of hydrogen energy, 2023, 48(50): 19008-19021.
[7] ZHAO D Q, HE Q J, YU J, et al.A data-driven digital-twin model and control of high temperature proton exchange membrane electrolyzer cells[J]. International journal of hydrogen energy, 2022, 47(14): 8687-8699.
[8] 金红超, 何锋, 胡耀宗. 基于变论域模糊理论的PEMFC热管理系统控制研究[J]. 电子测量技术, 2022, 45(14): 23-28.
JIN H C, HE F, HU Y Z.Thermal management system control of PEMFC based on variable universe fuzzy theory[J]. Electronic measurement technology, 2022, 45(14): 23-28.
[9] MARANGIO F, PAGANI M, SANTARELLI M, et al.Concept of a high pressure PEM electrolyser prototype[J]. International journal of hydrogen energy, 2011, 36(13): 7807-7815.
[10] HUANG P.Humidity standard of compressed hydrogen for fuel cell technology[J]. ECS transactions, 2008, 12(1): 479.
[11] DIÉGUEZ P M, URSÚA A, SANCHIS P, et al. Thermal performance of a commercial alkaline water electrolyzer: experimental study and mathematical modeling[J]. International journal of hydrogen energy, 2008, 33(24): 7338-7354.
[12] HERNÁNDEZ-GÓMEZ Á, RAMIREZ V, GUILBERT D. Investigation of PEM electrolyzer modeling: electrical domain, efficiency, and specific energy consumption[J]. International journal of hydrogen energy, 2020, 45(29): 14625-14639.
[13] YODWONG B, GUILBERT D, PHATTANASAK M, et al.Faraday’s efficiency modeling of a proton exchange membrane electrolyzer based on experimental data[J]. Energies, 2020, 13(18): 4792.
[14] SCHEEPERS F, STÄHLER M, STÄHLER A, et al. Temperature optimization for improving polymer electrolyte membrane-water electrolysis system efficiency[J]. Applied energy, 2021, 283: 116270.
[15] 张少康. 基于模糊自整定PID的脱硝控制系统研究与应用[D]. 北京: 华北电力大学, 2018.
ZHANG S K.Research and application of NOx reduction control system based on fuzzy self-tuning PID[D]. Beijing: North China Electric Power University, 2018.
[16] 谢雨岑, 邹见效, 彭超. 基于变论域模糊增量理论的质子交换膜燃料电池温度控制[J]. 控制理论与应用, 2019, 36(3): 428-435.
XIE Y C, ZOU J X, PENG C.Temperature control of PEMFC system based on variable universe fuzzy incremental theory[J]. Control theory & applications, 2019, 36(3): 428-435.
[17] ABDIN Z, WEBB C J, GRAY E M.Modelling and simulation of a proton exchange membrane (PEM) electrolyser cell[J]. International journal of hydrogen energy, 2015, 40(39): 13243-13257.
[18] OJONG E T, KWAN J T H, NOURI-KHORASANI A, et al. Development of an experimentally validated semi-empirical fully-coupled performance model of a PEM electrolysis cell with a 3-D structured porous transport layer[J]. International journal of hydrogen energy, 2017, 42(41): 25831-25847.
基金
国家重点研发计划（2020YFB1506802）; 国家资助博士后研究人员计划（GZC20232011）
PDF(2265 KB)
