Combination whale optimization algorithm and fuzzy logic for optimal design battery charging LiFePO₄

Abstract

This research proposes an optimized charging strategy for lithium iron phosphate (LiFePO₄) batteries by integrating the whale optimization algorithm (WOA) with a fuzzy logic controller (FLC) for adaptive constant current-constant voltage charging. The method addresses the limitations of conventional CC-CV charging, which uses fixed parameters and has limited adaptability to changing operating conditions. WOA automatically optimizes the FLC scaling factors to improve control performance and system responsiveness. The WOA-fuzzy and WOA-PI models were trained using 226 samples of initial current and voltage data. The system was evaluated in PSIM by comparing fuzzy, PI, WOA-PI, and WOA-fuzzy controllers. Open-loop simulation produced an average voltage error of 1.29%, confirming the need for closed-loop control. Under SOC conditions ranging from 30% to 97%, all controllers maintained the charging voltage near 73 V and the charging current around 10 A. The average voltage errors were 0.6635% for PI, 0.6684% for fuzzy, 0.6618% for WOA-PI, and 0.6601% for WOA-fuzzy. Hardware testing confirmed these results, with average errors of 0.14% for WOA-fuzzy and 0.31% for WOA-PI. Overall, WOA-fuzzy provides stable charging, faster convergence, and improved charging performance.