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In the quest for sustainable and efficient energy solutions, hydrogen fuel cells emerge as a beacon of hope, offering a promising pathway towards a greener future. Accurate Identification of the ungiven parameters of proton exchange membrane fuel cell (PEMFC) mathematical models is indispensable for designing, managing, and simulating the practical PEMFC. In order to identify the parameters of PEMFC punctually, this paper presents a modified version of the slime mould algorithm (MSMA). In order to increase capability of the MSMA in the exploitation phase, both locally and globally, the sine-cosine technique has been utilized to boost the search capabilities. To assess the performance of MSMA, MSMA is first utilized to address ten well-known benchmark functions. The obtained results confirm that MSMA outperforms SMA on all benchmark functions. Then, MSMA is employed to solve the optimization problem of different mechanical design problems and also the MSMA provides superior performance over the standard SMA. Finally, the MSMA is used to identify the unknown parameters of four typical PEMFCs: 250W PEMFC, BCS 500W PEMFC, AVISTA SR-12 model, and the Temasek 1 kW PEMFC model. Experimental results boost the supremacy of MSMA in the PEMFC parameters extraction by comparing it with the original SMA and well-known potent optimization techniques. Furthermore, MATLAB/Simulink is employed for advanced dynamic PEMFC modeling, facilitating a comprehensive assessment of fuel cell parameters. The validation of this dynamic PEMFC model, using MSMA-optimized parameters, establishes its practical utility in system analysis and real-world fuel cell operation, marking a significant advancement in PEMFC technology management and simulation. [ABSTRACT FROM AUTHOR]

• Mathematical model used to simulate the electrochemical characteristics of fuel cell. • A set of unidentified parameters must be properly estimated. • The Bonobo Optimizer and the modified Quasi Oppositional BO are proposed. • The findings obtained are compared to those acquired using other current optimization approaches. The accuracy of the mathematical model used to simulate the electrochemical characteristics of fuel cell (FC) stacks has a significant impact on the quality of the electrochemical simulation. Due to the lack of manufacturers' information, a set of unidentified parameters must be properly estimated for establishing an accurate representation of proton exchange membrane FCs (PEMFCs). In this research, the Bonobo Optimizer (BO) and the modified Quasi Oppositional BO (QOBO) are applied for determining unknown design parameters of various typical PEMFCs. The obtained results in the form of polarization curves are compared with the corresponding experimental ones to validate the appropriateness and adequacy of the used algorithms. The findings obtained using the original BO and modified QOBO algorithms are compared to those acquired using other current optimization approaches, revealing that the QOBO algorithm outperformed the conventional BO algorithm in solving the optimization problem. Further, a statistical analysis is carried out that guaranteed the robustness and reliability of the developed QOBO. [ABSTRACT FROM AUTHOR]

• Proton exchange membrane fuel cells. • An improved Salp Swarm Algorithm (SSA) is proposed to enhance the conventional SSA. • The proposed ISSA has been utilized for identifying the unknown parameter values. • The Sum of Squared Errors (SSE) is adopted as the objective function. • Statistical analysis of proposed ISSA compared with the conventional SSA is carried out. Recently, Proton Exchange Membrane Fuel Cells (PEMFCs) become one of the most promising friendly renewable energy sources. Therefore, developing a mathematical model for the PEMFC is an urgent necessity for simulation and evaluation of the processes occurring inside the fuel cell (FC) stack. In this paper, a precis model, which can stimulate the electrical and electrochemical phenomenon of the PEMFC is introduced. Improved salp swarm algorithm (ISSA) is proposed to enhance the performance of the conventional SSA and avoid getting stuck on local optimum. The proposed ISSA has been utilized for identifying the unknown parameter values of PEMFC stack models. The proposed ISSA is validated on four different FC stacks and a comparison between the computed and measured results has been accomplished. The Sum of Squared Errors (SSE) between experimental and estimated voltages is adopted as the objective function which has to be minimized. For validating the goodness of the ISSA, the generated values of the unknown parameters and the value of SSE using the ISSA-based PEMFC model are compared with the corresponding ones obtained by other optimization techniques. Furthermore, statistical analysis of proposed ISSA compared with the conventional SSA is carried out for all the PEMFC stacks involved in this work. The simulation results under various conditions of operation and the statistical results proved the stability and reliability of ISSA in comparison with recently utilized algorithms. [ABSTRACT FROM AUTHOR]