State-of-charge estimation based on microcontroller-implemented sigma-point Kalman filter in a modular cell balancing system for Lithium-Ion battery packs

Fan Zhang; M. Muneeb Ur Rehman; Hongjie Wang; Yoash Levron; Gregory Plett; Regan Zane; Dragan Maksimović

doi:10.1109/COMPEL.2015.7236525

State-of-charge estimation based on microcontroller-implemented sigma-point Kalman filter in a modular cell balancing system for Lithium-Ion battery packs

Fan Zhang, M. Muneeb Ur Rehman, Hongjie Wang, Yoash Levron, Gregory Plett, Regan Zane, Dragan Maksimović

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Cell balancing in large battery packs requires accurate state of charge (SOC) estimation for individual cells. This paper presents a low complexity sigma-point Kalman filter to estimate the state-of-charge (SOC) of Lithium-Ion battery cells. The proposed sigma-point Kalman filter is of 1^st order, and can be easily implemented on a simple microcontroller around a dc-dc converter in a modular cell balancing system. The approach is verified experimentally on a battery pack containing twenty-one balancing converters and twenty-one 25 Ah Lithium-Ion cells under high-current (up to 100A) cycling.

Original language	English
Title of host publication	2015 IEEE 16th Workshop on Control and Modeling for Power Electronics, COMPEL 2015
ISBN (Electronic)	9781467368476
DOIs	https://doi.org/10.1109/COMPEL.2015.7236525
State	Published - 1 Sep 2015
Event	16th IEEE Workshop on Control and Modeling for Power Electronics, COMPEL 2015 - Vancouver, Canada Duration: 12 Jul 2015 → 15 Jul 2015

Publication series

Name	2015 IEEE 16th Workshop on Control and Modeling for Power Electronics, COMPEL 2015

Conference

Conference	16th IEEE Workshop on Control and Modeling for Power Electronics, COMPEL 2015
Country/Territory	Canada
City	Vancouver
Period	12/07/15 → 15/07/15

Keywords

BMS
Kalman filter
SOC
battery management
cell balancing

ASJC Scopus subject areas

Energy Engineering and Power Technology
Control and Systems Engineering
Modeling and Simulation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/COMPEL.2015.7236525

Cite this

Zhang, F., Ur Rehman, M. M., Wang, H., Levron, Y., Plett, G., Zane, R., & Maksimović, D. (2015). State-of-charge estimation based on microcontroller-implemented sigma-point Kalman filter in a modular cell balancing system for Lithium-Ion battery packs. In 2015 IEEE 16th Workshop on Control and Modeling for Power Electronics, COMPEL 2015 Article 7236525 (2015 IEEE 16th Workshop on Control and Modeling for Power Electronics, COMPEL 2015). https://doi.org/10.1109/COMPEL.2015.7236525

Zhang, Fan ; Ur Rehman, M. Muneeb ; Wang, Hongjie et al. / State-of-charge estimation based on microcontroller-implemented sigma-point Kalman filter in a modular cell balancing system for Lithium-Ion battery packs. 2015 IEEE 16th Workshop on Control and Modeling for Power Electronics, COMPEL 2015. 2015. (2015 IEEE 16th Workshop on Control and Modeling for Power Electronics, COMPEL 2015).

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title = "State-of-charge estimation based on microcontroller-implemented sigma-point Kalman filter in a modular cell balancing system for Lithium-Ion battery packs",

abstract = "Cell balancing in large battery packs requires accurate state of charge (SOC) estimation for individual cells. This paper presents a low complexity sigma-point Kalman filter to estimate the state-of-charge (SOC) of Lithium-Ion battery cells. The proposed sigma-point Kalman filter is of 1st order, and can be easily implemented on a simple microcontroller around a dc-dc converter in a modular cell balancing system. The approach is verified experimentally on a battery pack containing twenty-one balancing converters and twenty-one 25 Ah Lithium-Ion cells under high-current (up to 100A) cycling.",

keywords = "BMS, Kalman filter, SOC, battery management, cell balancing",

author = "Fan Zhang and {Ur Rehman}, {M. Muneeb} and Hongjie Wang and Yoash Levron and Gregory Plett and Regan Zane and Dragan Maksimovi{\'c}",

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Zhang, F, Ur Rehman, MM, Wang, H, Levron, Y, Plett, G, Zane, R & Maksimović, D 2015, State-of-charge estimation based on microcontroller-implemented sigma-point Kalman filter in a modular cell balancing system for Lithium-Ion battery packs. in 2015 IEEE 16th Workshop on Control and Modeling for Power Electronics, COMPEL 2015., 7236525, 2015 IEEE 16th Workshop on Control and Modeling for Power Electronics, COMPEL 2015, 16th IEEE Workshop on Control and Modeling for Power Electronics, COMPEL 2015, Vancouver, Canada, 12/07/15. https://doi.org/10.1109/COMPEL.2015.7236525

State-of-charge estimation based on microcontroller-implemented sigma-point Kalman filter in a modular cell balancing system for Lithium-Ion battery packs. / Zhang, Fan; Ur Rehman, M. Muneeb; Wang, Hongjie et al.
2015 IEEE 16th Workshop on Control and Modeling for Power Electronics, COMPEL 2015. 2015. 7236525 (2015 IEEE 16th Workshop on Control and Modeling for Power Electronics, COMPEL 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Cell balancing in large battery packs requires accurate state of charge (SOC) estimation for individual cells. This paper presents a low complexity sigma-point Kalman filter to estimate the state-of-charge (SOC) of Lithium-Ion battery cells. The proposed sigma-point Kalman filter is of 1st order, and can be easily implemented on a simple microcontroller around a dc-dc converter in a modular cell balancing system. The approach is verified experimentally on a battery pack containing twenty-one balancing converters and twenty-one 25 Ah Lithium-Ion cells under high-current (up to 100A) cycling.

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Zhang F, Ur Rehman MM, Wang H, Levron Y, Plett G, Zane R et al. State-of-charge estimation based on microcontroller-implemented sigma-point Kalman filter in a modular cell balancing system for Lithium-Ion battery packs. In 2015 IEEE 16th Workshop on Control and Modeling for Power Electronics, COMPEL 2015. 2015. 7236525. (2015 IEEE 16th Workshop on Control and Modeling for Power Electronics, COMPEL 2015). doi: 10.1109/COMPEL.2015.7236525

State-of-charge estimation based on microcontroller-implemented sigma-point Kalman filter in a modular cell balancing system for Lithium-Ion battery packs

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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