A comprehensive model for battery State of Charge prediction

Bart Homan, Gerardus Johannes Maria Smit, Richard Pieter van Leeuwen, Marnix Ten Kortenaar (Contributor)

Research output: Contribution to conferencePaperAcademicpeer-review

3 Citations (Scopus)
336 Downloads (Pure)

Abstract

In this paper the relatively simple model for State of Charge prediction, based on energy conservation, introduced in [1] is improved and verified. The model as introduced in [1] is verified for Pb-acid, Li-ion and Seasalt batteries. The model is further improved to accommodate the rate capacity effect and the capacity recovery effect, the improvements are verified with lead-acid batteries. For further verification the model is applied on a realistic situation and compared to measurements on the behavior of a real battery in that situation. Furthermore the results are compared to results of the well-established KiBaM model. Predictions on the SoC over time done using the proposed model closely follow the SoC over time calculated from measured data.
The resulting improved model is both simple and effective, making it specially useful as part of smart control, and energy usage simulations.
Original languageEnglish
Pages1-6
Number of pages6
DOIs
Publication statusPublished - 20 Jul 2017
Event12th IEEE PES PowerTech Conference: Towards and Beyond Sustainable Energy Systems - University of Manchester, Manchester, United Kingdom
Duration: 18 Jun 201722 Jul 2017
Conference number: 12
http://ieee-powertech.org/

Conference

Conference12th IEEE PES PowerTech Conference
Abbreviated titlePowerTech 2017
CountryUnited Kingdom
CityManchester
Period18/06/1722/07/17
Internet address

Fingerprint

Lead acid batteries
Energy conservation
Recovery
Acids
Ions
System-on-chip

Keywords

  • Storage
  • Predictive model
  • Smart grid
  • Energy management

Cite this

Homan, B., Smit, G. J. M., van Leeuwen, R. P., & Ten Kortenaar, M. (2017). A comprehensive model for battery State of Charge prediction. 1-6. Paper presented at 12th IEEE PES PowerTech Conference, Manchester, United Kingdom. https://doi.org/10.1109/PTC.2017.7980943
Homan, Bart ; Smit, Gerardus Johannes Maria ; van Leeuwen, Richard Pieter ; Ten Kortenaar, Marnix. / A comprehensive model for battery State of Charge prediction. Paper presented at 12th IEEE PES PowerTech Conference, Manchester, United Kingdom.6 p.
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abstract = "In this paper the relatively simple model for State of Charge prediction, based on energy conservation, introduced in [1] is improved and verified. The model as introduced in [1] is verified for Pb-acid, Li-ion and Seasalt batteries. The model is further improved to accommodate the rate capacity effect and the capacity recovery effect, the improvements are verified with lead-acid batteries. For further verification the model is applied on a realistic situation and compared to measurements on the behavior of a real battery in that situation. Furthermore the results are compared to results of the well-established KiBaM model. Predictions on the SoC over time done using the proposed model closely follow the SoC over time calculated from measured data.The resulting improved model is both simple and effective, making it specially useful as part of smart control, and energy usage simulations.",
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Homan, B, Smit, GJM, van Leeuwen, RP & Ten Kortenaar, M 2017, 'A comprehensive model for battery State of Charge prediction' Paper presented at 12th IEEE PES PowerTech Conference, Manchester, United Kingdom, 18/06/17 - 22/07/17, pp. 1-6. https://doi.org/10.1109/PTC.2017.7980943

A comprehensive model for battery State of Charge prediction. / Homan, Bart ; Smit, Gerardus Johannes Maria; van Leeuwen, Richard Pieter; Ten Kortenaar, Marnix (Contributor).

2017. 1-6 Paper presented at 12th IEEE PES PowerTech Conference, Manchester, United Kingdom.

Research output: Contribution to conferencePaperAcademicpeer-review

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AU - Smit, Gerardus Johannes Maria

AU - van Leeuwen, Richard Pieter

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N2 - In this paper the relatively simple model for State of Charge prediction, based on energy conservation, introduced in [1] is improved and verified. The model as introduced in [1] is verified for Pb-acid, Li-ion and Seasalt batteries. The model is further improved to accommodate the rate capacity effect and the capacity recovery effect, the improvements are verified with lead-acid batteries. For further verification the model is applied on a realistic situation and compared to measurements on the behavior of a real battery in that situation. Furthermore the results are compared to results of the well-established KiBaM model. Predictions on the SoC over time done using the proposed model closely follow the SoC over time calculated from measured data.The resulting improved model is both simple and effective, making it specially useful as part of smart control, and energy usage simulations.

AB - In this paper the relatively simple model for State of Charge prediction, based on energy conservation, introduced in [1] is improved and verified. The model as introduced in [1] is verified for Pb-acid, Li-ion and Seasalt batteries. The model is further improved to accommodate the rate capacity effect and the capacity recovery effect, the improvements are verified with lead-acid batteries. For further verification the model is applied on a realistic situation and compared to measurements on the behavior of a real battery in that situation. Furthermore the results are compared to results of the well-established KiBaM model. Predictions on the SoC over time done using the proposed model closely follow the SoC over time calculated from measured data.The resulting improved model is both simple and effective, making it specially useful as part of smart control, and energy usage simulations.

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Homan B, Smit GJM, van Leeuwen RP, Ten Kortenaar M. A comprehensive model for battery State of Charge prediction. 2017. Paper presented at 12th IEEE PES PowerTech Conference, Manchester, United Kingdom. https://doi.org/10.1109/PTC.2017.7980943