TY - GEN
T1 - Intelligent Cell Balancing Control for Lithium-Ion Battery Packs
AU - Sorouri, Hoda
AU - Oshnoei, Arman
AU - Teodorescu, Remus
PY - 2024
Y1 - 2024
N2 - This study introduces a balancing control strategy that employs an Artificial Neural Network (ANN) to ensure State of Charge (SOC) balance across lithium-ion (Li-ion) battery packs, consistent with the framework of smart battery packs. The model targets a battery pack consisting of cells with diverse characteristics, reflecting real-world heterogeneous conditions. A fundamental aspect of this approach is the ability to bypass individual cells optimally. This key feature stops current flow to and from the cell, allowing it to rest and cool off while avoiding charging or discharging cycles. The implementation of ANN enables adaptive and dynamic management of SOC, which is essential for optimizing performance and extending the lifespan of battery packs. The results demonstrate the effectiveness of the proposed ANN-based balancing strategy in SOC balancing, demonstrating its potential as a critical solution in enhancing battery management systems for electric vehicles.
AB - This study introduces a balancing control strategy that employs an Artificial Neural Network (ANN) to ensure State of Charge (SOC) balance across lithium-ion (Li-ion) battery packs, consistent with the framework of smart battery packs. The model targets a battery pack consisting of cells with diverse characteristics, reflecting real-world heterogeneous conditions. A fundamental aspect of this approach is the ability to bypass individual cells optimally. This key feature stops current flow to and from the cell, allowing it to rest and cool off while avoiding charging or discharging cycles. The implementation of ANN enables adaptive and dynamic management of SOC, which is essential for optimizing performance and extending the lifespan of battery packs. The results demonstrate the effectiveness of the proposed ANN-based balancing strategy in SOC balancing, demonstrating its potential as a critical solution in enhancing battery management systems for electric vehicles.
KW - The authors shall provide up to 4 keywords or phrases (in alphabetical order and separated by commas) to help identify the major topics of the paper
UR - http://www.scopus.com/inward/record.url?scp=85199068064&partnerID=8YFLogxK
U2 - 10.1109/IPEMC-ECCEAsia60879.2024.10567978
DO - 10.1109/IPEMC-ECCEAsia60879.2024.10567978
M3 - Article in proceeding
SP - 3997
EP - 4001
BT - 2024 IEEE 10th International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia
ER -