TY - GEN
T1 - Multi-pattern active cell balancing architecture and equalization strategy for battery packs
AU - Narayanaswamy, Swaminathan
AU - Park, Sangyoung
AU - Steinhorst, Sebastian
AU - Chakraborty, Samarjit
N1 - Publisher Copyright:
© 2018 ACM.
PY - 2018/7/23
Y1 - 2018/7/23
N2 - Active cell balancing is the process of improving the usable capacity of a series-connected Lithium-Ion (Li-Ion) battery pack by redistributing the charge levels of individual cells. Depending upon the State-of-Charge (SoC) distribution of the individual cells in the pack, an appropriate charge transfer pattern (cell-to-cell, cell-tomodule, module-to-cell or module-to-module) has to be selected for improving the usable energy of the battery pack. However, existing active cell balancing circuits are only capable of performing limited number of charge transfer patterns and, therefore, have a reduced energy efficiency for different types of SoC distribution. In this paper, we propose a modular, multi-pattern active cell balancing architecture that is capable of performing multiple types of charge transfer patterns (cell-to-cell, cell-to-module, module-tocell and module-to-module) with a reduced number of hardware components and control signals compared to existing solutions. We derive a closed-form, analytical model of our proposed balancing architecture with which we profile the efficiency of the individual charge transfer patterns enabled by our architecture. Using the profiling analysis, we propose a hybrid charge equalization strategy that automatically selects the most energy-efficient charge transfer pattern depending upon the SoC distribution of the battery pack and the characteristics of our proposed balancing architecture. Case studies show that our proposed balancing architecture and hybrid charge equalization strategy provide up to a maximum of 46.83% improvement in energy efficiency compared to existing solutions.
AB - Active cell balancing is the process of improving the usable capacity of a series-connected Lithium-Ion (Li-Ion) battery pack by redistributing the charge levels of individual cells. Depending upon the State-of-Charge (SoC) distribution of the individual cells in the pack, an appropriate charge transfer pattern (cell-to-cell, cell-tomodule, module-to-cell or module-to-module) has to be selected for improving the usable energy of the battery pack. However, existing active cell balancing circuits are only capable of performing limited number of charge transfer patterns and, therefore, have a reduced energy efficiency for different types of SoC distribution. In this paper, we propose a modular, multi-pattern active cell balancing architecture that is capable of performing multiple types of charge transfer patterns (cell-to-cell, cell-to-module, module-tocell and module-to-module) with a reduced number of hardware components and control signals compared to existing solutions. We derive a closed-form, analytical model of our proposed balancing architecture with which we profile the efficiency of the individual charge transfer patterns enabled by our architecture. Using the profiling analysis, we propose a hybrid charge equalization strategy that automatically selects the most energy-efficient charge transfer pattern depending upon the SoC distribution of the battery pack and the characteristics of our proposed balancing architecture. Case studies show that our proposed balancing architecture and hybrid charge equalization strategy provide up to a maximum of 46.83% improvement in energy efficiency compared to existing solutions.
KW - Active cell balancing
KW - Batteries
KW - Equalization algorithms
UR - http://www.scopus.com/inward/record.url?scp=85051469943&partnerID=8YFLogxK
U2 - 10.1145/3218603.3218607
DO - 10.1145/3218603.3218607
M3 - Conference contribution
AN - SCOPUS:85051469943
SN - 9781450357043
T3 - Proceedings of the International Symposium on Low Power Electronics and Design
BT - ISLPED 2018 - Proceedings of the 2018 International Symposium on Low Power Electronics and Design
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd IEEE/ACM International Symposium on Low Power Electronics and Design, ISLPED 2018
Y2 - 23 July 2018 through 25 July 2018
ER -