Active cell balancing control strategy for parallel connected LiFePO4 batteries
While several recent studies have focused on eliminating the imbalance of energy stored in series-connected battery cells, not much attention has been given to balance the energy stored in parallel-connected battery cells. As such, this paper aims at presenting a new balancing approach for parallel...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
China electric power research institute
2020
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/31841/1/Active%20cell%20-%20Copy.pdf http://ir.unimas.my/id/eprint/31841/ https://ieeexplore.ieee.org/abstract/document/9171672 |
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| Institution: | Universiti Malaysia Sarawak |
| Language: | English |
| Summary: | While several recent studies have focused on eliminating the imbalance of energy stored in series-connected battery cells, not much attention has been given to balance the energy stored in parallel-connected battery cells. As such, this paper aims at presenting a new balancing approach for parallel LiFePO 4 battery cells. In this regards, Backpropagation Neural Network (BPNN) based technique is employed to develop a Battery Management System (BMS) that can assess the charging status of all cells and control its operation through DC/DC Buck-Boost converter. Simulation results reveal the effectiveness of the proposed approach in balancing the energy stored in parallel-connected battery cells in which the state of charge (SoC) estimation error is found to be only 1.15%. |
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