Energy Conversion and Management 301 (2024) 118014 Available online 26 December 2023 0196-8904/© 2023 Elsevier Ltd. All rights reserved. Performance evaluation of a novel self-tuning particle swarm optimization algorithm-based maximum power point tracker for porton exchange membrane fuel cells under different operating conditions Ahmed Refaat a, * , Ahmed Elbaz a , Abd-Elwahab Khalifa a , Mohamed Mohamed Elsakka b , Ahmed Kalas a , Medhat Hegazy Elfar a a Electrical Engineering Department, Faculty of Engineering, Port Said University, Port Said, Egypt b Mechanical Power Engineering Department, Faculty of Engineering, Port Said University, Port Said, Egypt A R T I C L E INFO Keywords: Fuel Cell (FC) Metaheuristic Optimization Algorithms Self-Tuning PSO (ST-PSO) Algorithm PEMFC System MPPT Techniques ABSTRACT The power generated by a proton exchange membrane fuel cell (PEMFC) is heavily impacted by the change in membrane water content (MWC) and cell temperature. Since PEMFC stacks exhibit nonlinear characteristics, it is crucial to employ a controller that can accurately track the maximum power point (MPP) and extract the most efficient power from the fuel cell (FC) stack. This article introduces a novel MPP tracking technique, based on a self-tuning particle swarm optimization (ST-PSO) algorithm, to maximize power output from PEMFC under different operational conditions. The performance of the ST-PSO algorithm is evaluated through numerical simulations and compared to four well-known metaheuristic algorithms. The results indicate that the proposed ST-PSO-based MPPT technique surpasses the other metaheuristic methods in terms of extracting the maximum power, achieving fast-tracking, and minimizing power fluctuations in various operating conditions. It attained an MPPT efficiency, consistently exceeding 99.602 % and 99.545 %, while also achieving rapid tracking times of no more than 0.366 s and 0.297 s for the two tested scenarios. Moreover, the ST-PSO controller exhibits robustness and consistent tracking of the MPP. Experimental validation of the ST-PSO controller confirms its robustness and superiority over the other tested algorithm, achieving the highest MPPT efficiency of approximately 98.94 % with a rapid tracking time of 2.0 s. Additionally, it demonstrates the lowest power fluctuations of about 2.26 %, providing a stable power output. 1. Introduction The reliance on natural gas, oil, and coal within global economies is gradually decreasing due to their detrimental effect on the environment and the rapid exhaustion of fossil fuel reserves. To effectively mitigate the adverse impacts stemming from the use of fossil fuels, a pivotal shift towards the widespread utilization of renewable energy sources is imperative. This transition not only addresses the environmental degradation caused by fossil fuels but also paves the way for a more resilient and sustainable energy future [1–3]. Many sources of renew- able energy are subject to limitations based on geographical and climatic factors. For instance, solar energy is reliant on the presence of sunlight and cannot be efficiently utilized in areas with overcast skies. Similarly, wind energy is contingent on consistent wind patterns and therefore may not be available in all locations. The utilization of tidal and wave energy requires proximity to bodies of water, making it inaccessible in many regions [4]. Recently, Fuel Cells (FCs) have garnered significant global interest due to their low emissions and high efficiencies. FCs can be systematically classified into six primary types, which include molten carbonate cells, proton exchange membrane cells (PEMFCs), direct methanol cells, phosphoric acid cells, solid oxide cells, and alkaline cells [5,6]. PEMFCs, in particular, have widespread uses due to their remarkable characteristics, including low operating temperatures, high power densities, fast start-up, and ease of scalability, rendering them a promising alternative for the next generation of power sources for distributed generation systems and electric propulsion applications [7,8]. The performance of PEMFCs is impacted by operating conditions like operating temperature, gas pressure, membrane water contents (MWC), etc. When gas pressures are adjusted at a defined level, a nonlinear * Corresponding author. E-mail address: Ahmed_refaat_1984@eng.psu.edu.eg (A. Refaat). Contents lists available at ScienceDirect Energy Conversion and Management journal homepage: www.elsevier.com/locate/enconman https://doi.org/10.1016/j.enconman.2023.118014 Received 13 September 2023; Received in revised form 9 December 2023; Accepted 18 December 2023