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...
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| 主要な著者: | , , , |
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| フォーマット: | E-Article |
| 言語: | English |
| 出版事項: |
Multidisciplinary Digital Publishing Institute
2020
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| 主題: | |
| オンライン･アクセス: | http://ir.unimas.my/id/eprint/30572/1/Active%20Charge%20Balancing%20Strategy%20Using%20the%20State%20ofCharge%20Estimation%20Technique%20for%20a%20PV-BatteryHybrid%20System.pdf http://ir.unimas.my/id/eprint/30572/ https://www.mdpi.com/1996-1073/13/13/3434 https://doi.org/10.3390/en13133434 |
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| 要約: | : 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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