MULTI-OBJECTIVE OPTIMIZATION OF PROTON EXCHANGE MEMBRANE FUEL CELL SYSTEMS USING FUZZY LOGIC CONTROLLER: A REVIEW
Proton Exchange Membrane Fuel Cell, being non-linear in nature, possess great control problems to linear controllers such as particle swarm optimization, especially when variable operating conditions are desired. Optimizing PEMFC performance requires balancing multiple conflicting objectives, including efficiency, cost, durability, power output, and operational stability. This paper reviews multi-objective optimization techniques for the purpose of integrating Fuzzy Logic Controller in the multi-objective optimization of PEMFC systems to overcoming the inherent challenges of PEMFC technology (complex, nonlinear, and multi-variable nature). Multi-objective optimization (MOO) techniques are employed to address these challenges, with fuzzy logic-based controller (FLC) emerging as a powerful approach due to its ability to handle uncertainty and nonlinear system dynamics. Fuzzy Logic Based-Particle Swarm Optimization (FL-PSO) offers a powerful approach for optimizing PEMFC systems by dynamically adjusting operating parameters for higher efficiency, longer durability, and lower costs. Its ability to handle uncertainty and multi-objective trade-offs makes it a promising tool for the next generation of fuel cell technology.
Authors : Zirata, K.B., Thuku, I.T., Ibrahim, V.M. and Patrick, D.O.
Category : Open Access Volume (Issue) : 10(2) Date Uploaded : 10th April 2025