Active Charge Balancing Strategy Using the State of Charge Estimation Technique for a PV-Battery Hybrid System

Charging a group of series-connected batteries of a PV-battery hybrid system exhibits an imbalance issue. Such imbalance has severe consequences on the battery activation function and the maintenance cost of the entire system. Therefore, this paper proposes an active battery balancing technique for...

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Bibliographic Details
Published in:Energies (Basel) Vol. 13; no. 13; p. 3434
Main Authors: Ohirul Qays, Md, Buswig, Yonis, Hossain, Md Liton, Abu-Siada, Ahmed
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.07.2020
Subjects:
active battery balancing
Algorithms
backpropagation neural network
DC/DC Buck-boost converter
Fuzzy logic
Neural networks
Parameter identification
PV-battery integrated system
Simulation
Software
Solar energy
state of charge estimation
Temperature effects
ISSN:1996-1073, 1996-1073
Online Access:Get full text
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Summary:Charging a group of series-connected batteries of a PV-battery hybrid system exhibits an imbalance issue. Such imbalance has severe consequences on the battery activation function and the maintenance cost of the entire system. Therefore, this paper proposes an active battery balancing technique for a PV-battery integrated system to improve its performance and lifespan. Battery state of charge (SOC) estimation based on the backpropagation neural network (BPNN) technique is utilized to check the charge condition of the storage system. The developed battery management system (BMS) receives the SOC estimation of the individual batteries and issues control signal to the DC/DC Buck-boost converter to balance the charge status of the connected group of batteries. Simulation and experimental results using MATLAB-ATMega2560 interfacing system reveal the effectiveness of the proposed approach.
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ISSN:1996-1073
1996-1073
DOI:10.3390/en13133434