Battery management systems may rely on mathematical models to provide higher performance than standard charging protocols. Electrochemical models allow us to capture the phenomena occurring inside a lithium-ion cell and therefore, could be the best model choice. However, to be of practical value, they require reliable model parameters. Uncertainty quantification and optimal experimental design concepts are essential tools for identifying systems and estimating parameters precisely. Approximation errors in uncertainty quantification result in sub-optimal experimental designs and consequently, less-informative data, and higher parameter unreliability. In this work, we propose a highly efficient design of experiment method based on global parameter sensitivities. This novel concept is applied to the single-particle model with electrolyte and thermal dynamics (SPMeT), a well-known electrochemical model for lithium-ion cells. The proposed method avoids the simplifying assumption of output-parameter linearization (i.e., local parameter sensitivities) used in conventional Fisher information matrix-based experimental design strategies. Thus, the optimized current input profile results in experimental data of higher information content and in turn, in more precise parameter estimates.

Pozzi, A., Xie, X., Raimondo, D. M., Schenkendorf, R., Global sensitivity methods for design of experiments in lithium-ion battery context, Contributed paper, in IFAC-PapersOnLine, (Germania, 12-17 July 2020), Elsevier B.V., RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS 2020:<<IFAC-PAPERSONLINE>>,53 7248-7255. 10.1016/j.ifacol.2020.12.558 [http://hdl.handle.net/10807/193663]

Global sensitivity methods for design of experiments in lithium-ion battery context

Pozzi, A.
Primo
;
2020

Abstract

Battery management systems may rely on mathematical models to provide higher performance than standard charging protocols. Electrochemical models allow us to capture the phenomena occurring inside a lithium-ion cell and therefore, could be the best model choice. However, to be of practical value, they require reliable model parameters. Uncertainty quantification and optimal experimental design concepts are essential tools for identifying systems and estimating parameters precisely. Approximation errors in uncertainty quantification result in sub-optimal experimental designs and consequently, less-informative data, and higher parameter unreliability. In this work, we propose a highly efficient design of experiment method based on global parameter sensitivities. This novel concept is applied to the single-particle model with electrolyte and thermal dynamics (SPMeT), a well-known electrochemical model for lithium-ion cells. The proposed method avoids the simplifying assumption of output-parameter linearization (i.e., local parameter sensitivities) used in conventional Fisher information matrix-based experimental design strategies. Thus, the optimized current input profile results in experimental data of higher information content and in turn, in more precise parameter estimates.
Inglese
IFAC-PapersOnLine
21st IFAC World Congress 2020
Germania
Contributed paper
12-lug-2020
17-lug-2020
Elsevier B.V.
Pozzi, A., Xie, X., Raimondo, D. M., Schenkendorf, R., Global sensitivity methods for design of experiments in lithium-ion battery context, Contributed paper, in IFAC-PapersOnLine, (Germania, 12-17 July 2020), Elsevier B.V., RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS 2020:<<IFAC-PAPERSONLINE>>,53 7248-7255. 10.1016/j.ifacol.2020.12.558 [http://hdl.handle.net/10807/193663]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/193663
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