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

Author

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  • Md Ohirul Qays

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Malaysia Sarawak, Kota Samarahan 94300, Sarawak, Malaysia)

  • Yonis Buswig

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Malaysia Sarawak, Kota Samarahan 94300, Sarawak, Malaysia)

  • Md Liton Hossain

    (School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth 6102, Australia)

  • Ahmed Abu-Siada

    (School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth 6102, Australia)

Abstract

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.

Suggested Citation

  • Md Ohirul Qays & Yonis Buswig & Md Liton Hossain & Ahmed Abu-Siada, 2020. "Active Charge Balancing Strategy Using the State of Charge Estimation Technique for a PV-Battery Hybrid System," Energies, MDPI, vol. 13(13), pages 1-16, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:13:p:3434-:d:379773
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    References listed on IDEAS

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