Condition Monitoring and Effective Capacity Improvement for Lithium Polymer Batteries

Thanh Hai Nguyen; Khalifa Al Hosani

doi:10.1109/IECON.2019.8926740

Condition Monitoring and Effective Capacity Improvement for Lithium Polymer Batteries

Thanh Hai Nguyen
, Khalifa Al Hosani

Electrical Engineering

Higher Colleges of Technology

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

2 Scopus citations

Abstract

This paper proposes a model-based identification method for online monitoring of a state of charge (SOC) and state of health (SOH) of lithium polymer (Li-Po) batteries, which allows a runtime prediction and improves a useful capacity of the aged battery by an internal voltage compensation. For this, the internal resistance of the battery model is frequently updated with the latest estimated data. The algorithm utilizes the measured input current and the battery terminal voltage, where the Sigma-point Kalman filter (SKF) is utilized as an estimation tool. As a result, this scheme offers robustness and high accuracy for estimation under varying operating conditions of the battery. The feasibility of the proposed scheme is validated by the simulation and experimental results. It is shown that the estimation error for the SOC is about 4%.

Original language	British English
Title of host publication	Proceedings
Subtitle of host publication	IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE Computer Society
Pages	2330-2336
Number of pages	7
ISBN (Electronic)	9781728148786
DOIs	https://doi.org/10.1109/IECON.2019.8926740
State	Published - Oct 2019
Event	45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 - Lisbon, Portugal Duration: 14 Oct 2019 → 17 Oct 2019

Publication series

Name	IECON Proceedings (Industrial Electronics Conference)
Volume	2019-October

Conference

Conference	45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019
Country/Territory	Portugal
City	Lisbon
Period	14/10/19 → 17/10/19

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Condition monitoring
lithium polymer batteries
Sigma-point Kalman filter
SOC
SOH

Access to Document

10.1109/IECON.2019.8926740

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Nguyen, T. H., & Al Hosani, K. (2019). Condition Monitoring and Effective Capacity Improvement for Lithium Polymer Batteries. In Proceedings: IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society (pp. 2330-2336). Article 8926740 (IECON Proceedings (Industrial Electronics Conference); Vol. 2019-October). IEEE Computer Society. https://doi.org/10.1109/IECON.2019.8926740

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title = "Condition Monitoring and Effective Capacity Improvement for Lithium Polymer Batteries",

abstract = "This paper proposes a model-based identification method for online monitoring of a state of charge (SOC) and state of health (SOH) of lithium polymer (Li-Po) batteries, which allows a runtime prediction and improves a useful capacity of the aged battery by an internal voltage compensation. For this, the internal resistance of the battery model is frequently updated with the latest estimated data. The algorithm utilizes the measured input current and the battery terminal voltage, where the Sigma-point Kalman filter (SKF) is utilized as an estimation tool. As a result, this scheme offers robustness and high accuracy for estimation under varying operating conditions of the battery. The feasibility of the proposed scheme is validated by the simulation and experimental results. It is shown that the estimation error for the SOC is about 4\%.",

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Nguyen, TH & Al Hosani, K 2019, Condition Monitoring and Effective Capacity Improvement for Lithium Polymer Batteries. in Proceedings: IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society., 8926740, IECON Proceedings (Industrial Electronics Conference), vol. 2019-October, IEEE Computer Society, pp. 2330-2336, 45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019, Lisbon, Portugal, 14/10/19. https://doi.org/10.1109/IECON.2019.8926740

Condition Monitoring and Effective Capacity Improvement for Lithium Polymer Batteries. / Nguyen, Thanh Hai; Al Hosani, Khalifa.
Proceedings: IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society. IEEE Computer Society, 2019. p. 2330-2336 8926740 (IECON Proceedings (Industrial Electronics Conference); Vol. 2019-October).

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

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AB - This paper proposes a model-based identification method for online monitoring of a state of charge (SOC) and state of health (SOH) of lithium polymer (Li-Po) batteries, which allows a runtime prediction and improves a useful capacity of the aged battery by an internal voltage compensation. For this, the internal resistance of the battery model is frequently updated with the latest estimated data. The algorithm utilizes the measured input current and the battery terminal voltage, where the Sigma-point Kalman filter (SKF) is utilized as an estimation tool. As a result, this scheme offers robustness and high accuracy for estimation under varying operating conditions of the battery. The feasibility of the proposed scheme is validated by the simulation and experimental results. It is shown that the estimation error for the SOC is about 4%.

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KW - Sigma-point Kalman filter

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KW - SOH

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ER -

Condition Monitoring and Effective Capacity Improvement for Lithium Polymer Batteries

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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