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ELMANSOURI, Fatima ezzahra (Moulay ismail university), Hafid, Oubouaddi (ENSAM meknes), OUANNOU, ABDELMALEK (Moulay Ismail University,ENSAM), Mosaad, Mohamed (SMIEEE Yanbu Industrial Collage, Royal commission of Jubail and ), barbara, sara (University moulay ismail, ensam), Brouri, Adil (ENSAM, Moulay Ismail University,)

Fuzzy Logic Control for PV-Powered Lithium-Ion Battery Management

Scheduled for presentation during the Regular Session "Photovoltaic systems control " (FriS1T1), Friday, July 12, 2024, 09:20−09:40, Salle des conférences

12th IFAC Symposium on Control of Power & Energy Systems, July 10-12, 2024, Rabat, Morocco

This information is tentative and subject to change. Compiled on January 2, 2025

Keywords Energy Storage Systems and Technologies, Operation and Control of Renewable Energy Systems

Abstract

Nowadays, battery storage systems play a crucial role in both fixed and mobile applications. Lithium-ion batteries, in particular, emerge as a promising solution owing to their impressive power and energy density. Battery lifespan depends on charging and draining cycles. Overcharging can increase internal stress, heat, and battery part damage, limiting its lifespan. Discharging a battery too quickly or excessively might damage it and shorten its lifespan. Therefore, an intelligent management control system is an essential solution. This paper presents a fuzzy logic control for a PV-powered battery management system to control the charging and discharging processes of the battery, to prevent overcharging and guarantee an extended battery life span. This controller demonstrates a fast response time and a high level of accuracy. Furthermore, to improve the system performance and achieve cost-effectiveness, the power extracted from the PV system is maximized through an Incremental Conductance (INC) based Maximum Power Point Tracking (MPPT) approach. This approach presents superior tracking precision and demonstrates greater tracking accuracy when compared to alternative methods such as Perturb and Observe (P&O). The overall system and the control strategies are tested and validated in MATLAB/Simulink environment, and the simulation results affirm the effectiveness and robustness of the system.

 

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