Optimization of proton-exchange membrane fuel cells model by developed design of horse optimizer

ABSTRACT

The present research suggests a new method for optimum parameters identification of the unknown parameters of the proton-exchange membrane fuel cells (PEMFCs). The technique is defined by proposing an improved bio-inspired technique, which is developed Horse Optimization Algorithm which is used for optimum model identification of PEMFCs. The target here is to provide higher confirmation of the empirical outputted data points and the model outputted voltage. It is done by minimizing the mean square error of the two output values. To specify the efficiency of the proposed technique, this has been executed to a 250 W PEM fuel cell stack model from the literature and the achievements have been put in comparison with several latest techniques to indicate the efficiency of the method technique. Simulation results showed that the proposed technique with 1.2512 MSE delivers the maximum confirmation against the comparative techniques that have been utilized as an effective method for the PEMFC model identification.

KEYWORDS:

• Pemfcs
• model identification
• optimization
• mean square error
• output voltage
• developed horse optimization algorithm

Acknowledgements

This work was supported by Natural Science Foundation of the Higher Education Institutions of Jiangsu Province（No.22KJD460005）

This work was supported by Scientific Research Foundation of Nanjing Institute of Technology(No.YKJ201994).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Yijun Xu

Yijun Xu was born in Nanjing, Jiangsu Province in 1990, obtained his PhD degree in Mechanical engineering from Politecnico di Torino, Italy. Now he is working in Nanjing Institute of Technology. His research activity is mainly related to automotive field, including vehicle chassis electrification, energy saving and emission reduction technology and fuel cells. Furthermore, he has been involved, as a project leader in several projects and collaborations with industrial companies.

Xuan Zhang

Xuan Zhang was born in Nanjing, Jiangsu Province in 1989, obtained his Master degree in Electronics and communication engineering from Nanjing University of Posts and Telecommunications. Now he is working in Zhongbei College, Nanjing Normal University. His research activity is mainly related to signal processing and control.

Yuxing Bai

Yuxing Bai was born in Zhenjiang, Jiangsu Province in 1987, obtained his PhD degree in Jiangsu University. Now he is working in School of automotive and rail transit, Nanjing Institute of Technology. His research activity is mainly related to fluid mechanics, including CFD simulations, pump design and optimization.

Xin Li

Xin Li graduated from Nanjing University of Aeronautics and Astronautics, obtained his PhD degree in vehicle operation engineering. Now he is currently working in School of automotive and rail transit, Nanjing Institute of Technology. His research activity is mainly related to friction and wear condition monitoring of mechanical system and fault diagnosis.

Navid Razmjooy

Navid Razmjooy is a Postdoc researcher at the industrial college of the Ankara Yıldırım Beyazıt Üniversitesi. He is also a part-time assistant professor at the Islamic Azad University, Ardabil, Iran. His main areas of research are the Renewable Energies, Machine Vision, Soft Computing, Data Mining, Evolutionary Algorithms, Interval Analysis, and System Control. Navid Razmjooy studied his Ph.D. in the field of Electrical Engineering (Control and Automation) from Tafresh University, Iran (2018). He is a senior member of IEEE/USA and YRC in IAU/Iran.