Can an identifiability-optimizing test protocol improve the robustness of subsequent health-conscious lithium-ion battery control? an illustrative case study

Ji Liu, Michael Rothenberger, Sergio Mendoza, Partha Mishra, Yun Sik Jung, Hosam K. Fathy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

This paper examines the degree to which optimizing a lithium-ion battery's cycling for parameter identifiability can improve the robustness of subsequent health-conscious, model-based battery control. The paper builds on two established bodies of literature showing that (i) battery trajectory optimization for identifiability can improve parameter estimation accuracy significantly, and (ii) model-based battery control can improve performance significantly without compromising longevity. To the best of the authors' knowledge, the connection between these two distinct bodies of literature has never been examined before. We highlight the importance of this connection through an illustrative case study. Specifically, we (i) optimize the experimental cycling of commercial lithium-ion battery cells for identifiability. We then (ii) use the optimized cycles for experimental parameter identification, and (iii) use the resulting parameter values for pseudospectral battery charge trajectory optimization. Finally, we (iv) examine the robustness of the resulting solution to battery parameter identification uncertainties generated using Fisher information analysis. The results of this case study are quite compelling: the likelihood of accidental damage via lithium plating diminishes considerably when battery parameters are estimated from an identifiability-optimizing cycle prior to the use of these parameters in health-conscious control.

Original languageEnglish (US)
Title of host publication2016 American Control Conference, ACC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6320-6325
Number of pages6
ISBN (Electronic)9781467386821
DOIs
StatePublished - Jul 28 2016
Event2016 American Control Conference, ACC 2016 - Boston, United States
Duration: Jul 6 2016Jul 8 2016

Publication series

NameProceedings of the American Control Conference
Volume2016-July
ISSN (Print)0743-1619

Other

Other2016 American Control Conference, ACC 2016
CountryUnited States
CityBoston
Period7/6/167/8/16

Fingerprint

Health
Identification (control systems)
Trajectories
Information analysis
Robustness (control systems)
Plating
Parameter estimation
Lithium
Lithium-ion batteries
Uncertainty

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Liu, J., Rothenberger, M., Mendoza, S., Mishra, P., Jung, Y. S., & Fathy, H. K. (2016). Can an identifiability-optimizing test protocol improve the robustness of subsequent health-conscious lithium-ion battery control? an illustrative case study. In 2016 American Control Conference, ACC 2016 (pp. 6320-6325). [7526663] (Proceedings of the American Control Conference; Vol. 2016-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2016.7526663
Liu, Ji ; Rothenberger, Michael ; Mendoza, Sergio ; Mishra, Partha ; Jung, Yun Sik ; Fathy, Hosam K. / Can an identifiability-optimizing test protocol improve the robustness of subsequent health-conscious lithium-ion battery control? an illustrative case study. 2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 6320-6325 (Proceedings of the American Control Conference).
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abstract = "This paper examines the degree to which optimizing a lithium-ion battery's cycling for parameter identifiability can improve the robustness of subsequent health-conscious, model-based battery control. The paper builds on two established bodies of literature showing that (i) battery trajectory optimization for identifiability can improve parameter estimation accuracy significantly, and (ii) model-based battery control can improve performance significantly without compromising longevity. To the best of the authors' knowledge, the connection between these two distinct bodies of literature has never been examined before. We highlight the importance of this connection through an illustrative case study. Specifically, we (i) optimize the experimental cycling of commercial lithium-ion battery cells for identifiability. We then (ii) use the optimized cycles for experimental parameter identification, and (iii) use the resulting parameter values for pseudospectral battery charge trajectory optimization. Finally, we (iv) examine the robustness of the resulting solution to battery parameter identification uncertainties generated using Fisher information analysis. The results of this case study are quite compelling: the likelihood of accidental damage via lithium plating diminishes considerably when battery parameters are estimated from an identifiability-optimizing cycle prior to the use of these parameters in health-conscious control.",
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Liu, J, Rothenberger, M, Mendoza, S, Mishra, P, Jung, YS & Fathy, HK 2016, Can an identifiability-optimizing test protocol improve the robustness of subsequent health-conscious lithium-ion battery control? an illustrative case study. in 2016 American Control Conference, ACC 2016., 7526663, Proceedings of the American Control Conference, vol. 2016-July, Institute of Electrical and Electronics Engineers Inc., pp. 6320-6325, 2016 American Control Conference, ACC 2016, Boston, United States, 7/6/16. https://doi.org/10.1109/ACC.2016.7526663

Can an identifiability-optimizing test protocol improve the robustness of subsequent health-conscious lithium-ion battery control? an illustrative case study. / Liu, Ji; Rothenberger, Michael; Mendoza, Sergio; Mishra, Partha; Jung, Yun Sik; Fathy, Hosam K.

2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 6320-6325 7526663 (Proceedings of the American Control Conference; Vol. 2016-July).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Liu J, Rothenberger M, Mendoza S, Mishra P, Jung YS, Fathy HK. Can an identifiability-optimizing test protocol improve the robustness of subsequent health-conscious lithium-ion battery control? an illustrative case study. In 2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 6320-6325. 7526663. (Proceedings of the American Control Conference). https://doi.org/10.1109/ACC.2016.7526663