Hydrogen fuel cell stack on-line intelligent monitoring system based on FDC

doi:10.19799/j.cnki.2095-4239.2024.0037

Abstract

Abstract:

In hydrogen fuel cell vehicles, the Fuel Cell DC-DC converter (FDC) is a key interface between the hydrogen fuel cell stack(hydrogen stack) and the inverter, and the stability of its output DC bus voltage is a key link to ensure the normal operation of loads such as the motor. So, a new type of sliding mode predictive control is proposes in this article. Firstly, the topology of FDC is improved and a predictive model based on sliding mode surface is established. Then, a sliding mode surface value function is designed to improve the tracking accuracy of FDC; On this basis, in order to achieve online intelligent monitoring of the hydrogen reactor, the variable step linear interpolation lookup table method is further adopted to accurately estimate the impedance of the hydrogen reactor online. Firstly, the FDC is digitally controlled to generate small sinusoidal harmonics with variable frequency, and the multi frequency impedance value of the hydrogen reactor is estimated based on the input voltage and current sampling of the FDC; Then, the variable step linear interpolation lookup table method is used to compare the estimated impedance value with the design standard value, evaluate the current state of the hydrogen reactor, and achieve online intelligent monitoring of the hydrogen reactor. Finally, simulation and experimental verification will be conducted. The results show: ①When the experimental reference current is set to 100 A, The system current overshoot and response time under traditional PI control are 20 A and 15ms, respectively. In contrast, the system current overshoot and response time under sliding mode predictive control are 1.5 A and 2.5 ms, respectively; ②The tracking accuracy of FDC for self generated harmonics can be controlled within 2%; ③The variable step linear interpolation lookup algorithm can achieve accurate estimation of fuel cell impedance. Verify the effectiveness of the algorithm.

Key words: hydrogen fuel electric reactor, DC-DC converter, equivalent impedance, sliding mode predictive control, variable step linear table lookup method

CLC Number:

TK 91

Siyan LIU, Genxiang ZHONG, Qing GE. Hydrogen fuel cell stack on-line intelligent monitoring system based on FDC[J]. Energy Storage Science and Technology, 2024, 13(6): 2030-2038.

Figures/Tables 13

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References 18

1	WANG W, LI J Z. A tripartite evolutionary game model for the hydrogen fuel cell vehicle industry development under government regulation in China[J]. Fuel, 2023, 348: 128223.
2	MUBAROK H, SANTOSO T H. Monitoring of hydrogen fuel cell modeling with boost converter[J]. Journal of Physics: Conference Series, 2021, 1844(1): 012018.
3	CHU T K, XIE M, HAO J, et al. Degradation analysis of the core components of metal plate proton exchange membrane fuel cell stack under dynamic load cycles[J]. International Journal of Hydrogen Energy, 2022, 47(11): 7432-7442.
4	杨文, 李奇, 刘强, 等. 基于安全运行区域约束的PEMFC发电系统效率优化控制方法[J]. 中国电机工程学报, 2022, 42(15): 5576-5587.
	YANG W, LI Q, LIU Q, et al. Efficiency optimization control method of PEMFC power generation system based on safe operating area constraints[J]. Proceedings of the CSEE, 2022, 42(15): 5576-5587.
5	BRAZ B A, OLIVEIRA V B, PINTO A M F R. Experimental studies of the effect of cathode diffusion layer properties on a passive direct methanol fuel cell power output[J]. International Journal of Hydrogen Energy, 2019, 44(35): 19334-19343.
6	LYU Z W, LI H Y, HAN M F, et al. Performance degradation analysis of solid oxide fuel cells using dynamic electrochemical impedance spectroscopy[J]. Journal of Power Sources, 2022, 538: 231569.
7	顾荣鑫, 朱东, 杨彦博, 等. 质子交换膜燃料电池低温停机研究综述[J]. 汽车技术, 2022(6): 1-13.
	GU R X, ZHU D, YANG Y B, et al. Review on the research of the cold stop for proton exchange membrane fuel cells[J]. Automobile Technology, 2022(6): 1-13.
8	MA T C, KANG J J, LIN W K, et al. Highly integrated online multi-channel electrochemical impedance spectroscopy measurement device for fuel cell stack[J]. Energies, 2022, 15(9): 3414.
9	金致含, 苏建徽, 施永, 等. 基于二进制序列的燃料电池宽频带EIS测试[J]. 太阳能学报, 2022, 43(7): 1-8.
	JIN Z H, SU J H, SHI Y, et al. Broadband eis test of fuel cell based on binary sequences[J]. Acta Energiae Solaris Sinica, 2022, 43(7): 1-8.
10	PETRONE G, SPAGNUOLO G, ZAMBONI W, et al. An improved mathematical method for the identification of fuel cell impedance parameters based on the interval arithmetic[J]. Mathematics and Computers in Simulation, 2021, 183: 78-96.
11	PETRONE G, ZAMBONI W, SPAGNUOLO G, et al. EIS method for the on-board evaluation of the fuel cell impedance[C]//2018 IEEE 4th International Forum on Research and Technology for Society and Industry (RTSI). Palermo, Italy. IEEE, 2018: 1-6.
12	YAO Q, LU D D C, LEI G. Accurate online battery impedance measurement method with low output voltage ripples on power converters[J]. Energies, 2021, 14(4): 1064.
13	吉冈良, 恒石亘启, 铃木悠平. 燃料电池系统: 日本, 111211345B[P]. 2023-02-17.
	JI G L, HENG S G,LING M Y P,Fuel cell system: Japan, 111211345B[P]. 2023-02-17.
14	吕沁阳, 滕腾, 张宝迪, 等. 增程式燃料电池车经济性与耐久性优化控制策略[J]. 哈尔滨工业大学学报, 2021, 53(7): 126-133.
	LÜ Q Y, TENG T, ZHANG B D, et al. Optimal control strategy for economy and durability of extended range fuel cell vehicle[J]. Journal of Harbin Institute of Technology, 2021, 53(7): 126-133.
15	刘偲艳, 胡毕华. 氢燃料汽车双向DC-DC变换器改进模型预测控制[J]. 储能科学与技术, 2021, 10(6): 2046-2052.
	LIU S Y, HU B H. Model predictive control for bidirectional DC-DC converter of hydrogen fuel vehicles[J]. Energy Storage Science and Technology, 2021, 10(6): 2046-2052.
16	郭磊磊, 郑铭哲, 李琰琰, 等. 三相LCL并网逆变器无参数滑模预测控制策略[J]. 电力系统保护与控制, 2022, 50(18): 72-82.
	GUO L L, ZHENG M Z, LI Y Y, et al. Nonparametric sliding mode predictive control strategy for a three-phase LCL grid-connected inverter[J]. Power System Protection and Control, 2022, 50(18): 72-82.
17	王勇, 高海燕. Buck型DC-DC变换器的滑模预测控制方法[J]. 厦门理工学院学报, 2022, 30(3): 18-23.
	WANG Y, GAO H Y. A sliding mode predictive control for buck DC-DC converter[J]. Journal of Xiamen University of Technology, 2022, 30(3): 18-23.
18	苏泳, 陈艳峰. 基于非线性扰动观测的储能双向DC-DC变换器非奇异终端滑模控制策略[J]. 储能科学与技术, 2024, 13(5): 1523-1531.
	SU Yong, CHEN Yanfeng.Nonsingular terminal sliding mode control strategy of bidirectional DC-DC converter in energy storage system based on the nonlinear disturbance observer[J]. Energy Storage Science and Technology, 2024, 13(5): 1523-1531.

控制器参数	数值
直流输入侧电压u_in/ V	60~350
输出侧电压u_o/ V	550
直流母线电容C_in、C_o/ F	2×10^-3
采样频率f_s / kHz	50
电感L / uH	200

阻抗	10 Hz	100 Hz	200 Hz	500 Hz	800 Hz	1100 Hz
实测R/mΩ	155.6	152.3	145.7	132.5	123.1	111.7
实测jX/mΩ	-3.1	-5.8	-7.1	-6.3	-4.9	-1.8
实测θ/deg	-1.14	-2.18	-2.79	-2.72	-2.27	-0.92
实测Z/mΩ	155.6	152.4	145.9	132.6	123.2	111.7

[1]	Yong SU, Yanfeng CHEN. Nonsingular terminal sliding mode control strategy of bidirectional DC-DC converter in energy storage system based on the nonlinear disturbance observer [J]. Energy Storage Science and Technology, 2024, 13(5): 1523-1531.
[2]	Jingchao SHEN, Jian HU, Jingliang HU, Ticao JIAO, Xiaomei QI, Yunpeng WANG, Di YU, Shangqi LIU. Parameter adaptive backstepping control of bidirectional DC-DC converter for DC microgrid energy storage device [J]. Energy Storage Science and Technology, 2022, 11(5): 1512-1522.
[3]	Siyan LIU, Bihua HU. Model predictive control for bidirectional DC-DC converter of hydrogen fuel vehicles [J]. Energy Storage Science and Technology, 2021, 10(6): 2046-2052.