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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| Vydáno v: | Energies (Basel) Ročník 13; číslo 13; s. 3434 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Basel
MDPI AG
01.07.2020
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| ISSN: | 1996-1073, 1996-1073 |
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| 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. |
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| AbstractList | 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. |
| Author | Hossain, Md Liton Buswig, Yonis Ohirul Qays, Md Abu-Siada, Ahmed |
| Author_xml | – sequence: 1 givenname: Md surname: Ohirul Qays fullname: Ohirul Qays, Md – sequence: 2 givenname: Yonis surname: Buswig fullname: Buswig, Yonis – sequence: 3 givenname: Md Liton orcidid: 0000-0002-2094-3036 surname: Hossain fullname: Hossain, Md Liton – sequence: 4 givenname: Ahmed surname: Abu-Siada fullname: Abu-Siada, Ahmed |
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| SubjectTerms | 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 |
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| Title | Active Charge Balancing Strategy Using the State of Charge Estimation Technique for a PV-Battery Hybrid System |
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