PARAMETER IDENTIFICATION OF PROTON EXCHANGE MEMBRANE FUEL CELLS MODEL BASED ON IMPROVED CHICKEN SWARM OPTIMIZATION ALGORITHM

Yang Yulun; Ling Ming

doi:10.19912/j.0254-0096.tynxb.2021-1138

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Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (2) : 269-278. DOI: 10.19912/j.0254-0096.tynxb.2021-1138

PARAMETER IDENTIFICATION OF PROTON EXCHANGE MEMBRANE FUEL CELLS MODEL BASED ON IMPROVED CHICKEN SWARM OPTIMIZATION ALGORITHM

Yang Yulun, Ling Ming

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Abstract

Most of the current intelligent algorithms are prone to local optimum when solving the parameter identification problem of proton exchange membrane fuel cells model, which results in low parameter identification accuracy and poor model generalization ability.To solve this problem, a parameter identification method of proton exchange membrane fuel cell based on improved chicken swarm optimization algorithm is proposed in this paper. Firstly, the Tent mapping strategy is introduced to initialize the population, as well as enhance the ergodicity and uniformity of the population. Secondly, the adaptive inertia weight based on individual feeding speed is designed to improve the optimization efficiency of individual hens,which tries to balance the exploitation and exploration ability of the algorithm. In addition, the long and short jump characteristics of Levy flight strategy is used to randomly update the position of chicken,so as to enhance the algorithm's global search ability. Finally, the superiority of the algorithm is verified through the test functions of four groups,and the algorithm is applied to the parameter identification of H-12 stack. According to the results,it indicates that the algorithm has higher parameter identification accuracy and stronger generalization ability in contrast with whale optimization algorithm,flower pollination algorithm and so on.

Key words

proton exchange membrane fuel cells / models / identification / chicken swarm optimization algorithm / Levy flight strategy

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Yang Yulun, Ling Ming. PARAMETER IDENTIFICATION OF PROTON EXCHANGE MEMBRANE FUEL CELLS MODEL BASED ON IMPROVED CHICKEN SWARM OPTIMIZATION ALGORITHM[J]. Acta Energiae Solaris Sinica. 2023, 44(2): 269-278 https://doi.org/10.19912/j.0254-0096.tynxb.2021-1138

References

[1] AGWA A M, LFERGANY A A, SARHAN G M.Steady-state modeling of fuel cells based on atom search optimizer[J]. Energies, 2019, 12(10): 1-14.
[2] GUO Y Y, DAI X D, JERMSITTIPARSERT K, et al.An optimal configuration for a battery and PEM fuel cell-based hybrid energy system using developed Krill herd optimization algorithm for locomotive application[J]. Energy reports, 2020, 6: 885-894.
[3] 张新丰, 罗明慧, 姚川棋, 等. 大功率车用质子交换膜燃料电池发动机性能测试实验室设计[J]. 同济大学学报(自然科学版), 2017, 45(S1): 132-137.
ZHANG X F, LUO M H, YAO C Q, et al.Design of proton exchange membrane fuel cell engine performance test laboratory for high power vehicle[J]. Journal of Tongji University (natural science edition), 2017, 45(S1): 132-137.
[4] 付洋, 戴朝华, 张玉瑾, 等. 便携式燃料电池电源系统的设计与控制研究[J], 太阳能学报, 2020, 41(1): 311-317.
FU Y, DAI C H, ZHANG Y J, et al.Design and control of portable fuel cell power supply system[J]. Acta energiae solaris sinica, 2020, 41(1): 311-317.
[5] 徐靖, 赵霞, 罗映红. 氢燃料电池并入微电网的改进虚拟同步机控制[J]. 电力系统保护与控制, 2020, 48(22): 165-172.
XU J, ZHAO X, LUO Y H.Improved virtual synchronizer control for hydrogen fuel cell converting into microgrid[J]. Power system protection and control, 2020, 48(22): 165-172.
[6] 柯超, 甘屹, 王胜佳, 等. 基于温度效应的空冷型质子交换膜燃料电池动态建模[J]. 太阳能学报, 2021, 42(8): 488-495.
KE C, GAN Y, WANG S J, et al.Dynamic modeling of air-cooled proton exchange membrane fuel cell based on temperature effect[J]. Acta energiae solaris sinica, 2021, 42(8): 488-495.
[7] GUHA A, PATRA A.Online estimation of the electrochemical impedance spectrum and remaining useful life of lithium-ion batteries[J]. IEEE transactions on instrumentation and measurement, 2018, 67(8): 1836-1849.
[8] 胡捷, 苏建徽, 杜燕, 等. 基于最小二乘法的PEMFC电堆模型参数辨识[J]. 太阳能学报, 2021, 42(6): 1-4.
HU J, SU J H, DU Y, et al.Parameter identification of PEMFC reactor model based on least squares method[J]. Acta energiae solaris sinica, 2021, 42(6): 1-4.
[9] GEEM Z W, NOH J S.Parameter estimation for a proton exchange membrane fuel cell model using GRG technique[J]. Fuel cells, 2016, 16(5): 640-645.
[10] REN Y, CAO G Y, ZHU X J.Particle swarm optimization based predictive control of proton exchange membrane fuel cell (PEMFC)[J]. Journal of Zhejiang University-science A, 2006, 7(3): 458-462.
[11] ABDI H, MESSAOUDENCE N A, KOLSI L, et al.Modeling and optimization of a proton exchange membrane fuel cell using particle swarm algorithm with constriction coefficient[J]. Journal of thermal analysis and calorimetry, 2020, 144(5): 1-11.
[12] 徐斌. 基于改进差分进化算法的质子交换膜燃料电池模型参数优化识别[J]. 化工学报, 2021, 72(3): 1512-1520.
XU B.Optimization and identification of model parameters of proton exchange membrane fuel cell based on improved differential evolution algorithm[J]. CIESC journal, 2021, 72(03): 1512-1520.
[13] ABDEL-BASSET M, MOHAMED R, ELHOSENY M, et al.An efficient heap-based optimization algorithm for parameters identification of proton exchange membrane fuel cells model: analysis and case studies[J]. International journal of hydrogen energy, 2021, 46(21): 11908-11925.
[14] 皇甫宜耿, 石麒, 李玉忍. 质子交换膜燃料电池系统建模仿真与控制[J]. 西北工业大学学报, 2015, 33(4): 682-687.
HUANGFU Y G, SHI Q, LI Y R.Modeling, simulation and control of proton exchange membrane fuel cell system[J]. Journal of Northwestern Polytechnical University, 2015, 33(4): 682-687.
[15] 高志, 蔡慧, 卫东, 等. 水冷型PEMFC输出特性建模与仿真分析[J]. 太阳能学报, 2019, 40(5): 1472-1480.
GAO Z, CAI H, WEI D, et al.Modeling and simulation analysis of output characteristics of water-cooled PEMFC[J]. Acta energiae solaris sinica, 2019, 40(05): 1472-1480.
[16] MENG X B, LIU Y, GAO X Z, et al.A new bio-inspired algorithm: chicken swarm optimization[C]//International Conference in Swarm Intelligence. Springer International Publishing, Hefei, China, 2014.
[17] 顾艳春, 鲁海燕, 向蕾, 等. 自适应动态学习鸡群优化算法[J]. 计算机工程与应用, 2020, 56(20): 36-45.
GU Y C, LU H Y, XIANG L, et al.Adaptive dynamic learning algorithm for chicken swarm optimization[J]. Computer engineering and applications, 2020, 56(20): 36-45.
[18] 张严, 秦亮曦. 基于Levy飞行策略的改进樽海鞘群算法[J]. 计算机科学, 2020, 47(7): 154-160.
ZHANG Y, QIN L X.Improved salps swarm algorithm based on Levy flight strategy[J]. Computer science, 2020, 47(7): 154-160.
[19] AHMAD S, SULAIMAN M, KUMAM P, et al.A novel population initialization strategy for accelerating Levy flights based multi-verse optimizer[J]. Journal of Intelligent & fuzzy systems, 2020, 39(1): 1-17.