TY - GEN
T1 - Development and Evaluation of an Experimental Platform for State-of-Charge Balancing Control of Lithium-Ion Battery Systems
AU - Wang, Jiaao
AU - Carson, M. Chase
AU - Qian, Yangyang
AU - Lin, Zongli
AU - Shamash, Yacov A.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Numerous battery management system (BMS) algorithms aimed at achieving state-of-charge (SOC) balancing have been proposed. This paper reports on the development and evaluation of an experimental platform for testing BMS algorithms. The platform we developed allows for simple parameter or physical quantity expression tweaks, making it easier to assess the performances of different various BMS algorithms. The hardware of the platform comprises a DSP chip (TMS320F28335), a custom-designed buck converter, various battery packs, and load resistors. By simulating circuit operations and analyzing battery output under load, an SOC versus open-circuit voltage graph is produced for estimation of the SOC. Employing cascaded PI controllers for the buck converter, the platform demonstrates its capability in power control and battery balance management through tests on a single battery system and on multiple battery systems. A BMS algorithm is selected for platform evaluation, affirming its effectiveness in maintaining SOC balancing among heterogeneous battery units.
AB - Numerous battery management system (BMS) algorithms aimed at achieving state-of-charge (SOC) balancing have been proposed. This paper reports on the development and evaluation of an experimental platform for testing BMS algorithms. The platform we developed allows for simple parameter or physical quantity expression tweaks, making it easier to assess the performances of different various BMS algorithms. The hardware of the platform comprises a DSP chip (TMS320F28335), a custom-designed buck converter, various battery packs, and load resistors. By simulating circuit operations and analyzing battery output under load, an SOC versus open-circuit voltage graph is produced for estimation of the SOC. Employing cascaded PI controllers for the buck converter, the platform demonstrates its capability in power control and battery balance management through tests on a single battery system and on multiple battery systems. A BMS algorithm is selected for platform evaluation, affirming its effectiveness in maintaining SOC balancing among heterogeneous battery units.
KW - Battery systems
KW - experimental platform
KW - SOC balancing
KW - SOC estimation
UR - https://www.scopus.com/pages/publications/85203241036
U2 - 10.1109/AIM55361.2024.10637146
DO - 10.1109/AIM55361.2024.10637146
M3 - Conference contribution
AN - SCOPUS:85203241036
T3 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
SP - 1488
EP - 1493
BT - 2024 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2024
Y2 - 15 July 2024 through 19 July 2024
ER -