Intelligent Battery Management in a Hybrid Photovoltaic Using Fuzzy Logic System
Year: 2025
Type: article
Abstract: LiFePO4 batteries need a battery management system (BMS) to improve performance, extend their lifespan, and maintain safety by utilizing advanced monitoring, control, and optimization techniques. This paper presents the design, development, and implementation of an intelligent battery management system (i-BMS) that integrates the real-time monitoring and control of batteries. The system was extensively tested using multiple datasets, and the results show that the system was able to maintain battery temperature within the set range, balance the cell voltages, and distribute energy according to load prioritization. It uses a fuzzy logic system approach to effectively manage farm energy requirements. Additionally, the proposed method embedded a three-level load prioritization algorithm woven into the fuzzy rule set to allocate energy dynamically among essential, regular, and non-essential loads.
Source: Technologies
Institutions: De La Salle University, Liverpool Hope University
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,930
Funder: De La Salle University
OpenAlex ID: W4410766884
