Predicting Lithium-ion Battery Resistance Degradation using a Log-Linear Model

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Resumé

The resistance is one of the parameters that describes the performance of Lithium-ion (Li-ion) batteries, as it offers information about the battery efficiency and its power capability. However, similar to other performance parameters of Li-ion batteries, the resistance is dependent on the operating
conditions and increases while the battery is aging. Traditionally, to capture these dependencies, Li-ion cells are aged at different conditions using synthetic mission profiles and periodically the aging tests are stopped in order to measure the resistance at standard conditions. Most of the times, even though accurate information about the resistance behavior is obtained, they do not reflect the behavior from real-life applications. Thus, in this work we propose a method for extracting, modelling, and predicting the resistance directly from the battery dynamic mission profile. While the extraction mainly relied on data manipulation and bookkeeping, the modelling and subsequent prediction of the resistance used a log-linear model.
OriginalsprogEngelsk
TitelProceedings of 2019 IEEE Energy Conversion Congress and Exposition (ECCE)
Antal sider8
ForlagIEEE Press
Publikationsdatosep. 2019
Sider1136-1143
DOI
StatusUdgivet - sep. 2019
Begivenhed2019 IEEE Energy Conversion Congress and Exposition (ECCE) - Baltimore, USA
Varighed: 29 sep. 20193 okt. 2019

Konference

Konference2019 IEEE Energy Conversion Congress and Exposition (ECCE)
LandUSA
By Baltimore
Periode29/09/201903/10/2019

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Aging of materials
Degradation
Lithium
Ions
Lithium-ion batteries

Citer dette

Vilsen, S. B., Kær, S. K., & Stroe, D-I. (2019). Predicting Lithium-ion Battery Resistance Degradation using a Log-Linear Model. I Proceedings of 2019 IEEE Energy Conversion Congress and Exposition (ECCE) (s. 1136-1143). IEEE Press. https://doi.org/10.1109/ECCE.2019.8912770
Vilsen, Søren Byg ; Kær, Søren Knudsen ; Stroe, Daniel-Ioan. / Predicting Lithium-ion Battery Resistance Degradation using a Log-Linear Model. Proceedings of 2019 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE Press, 2019. s. 1136-1143
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abstract = "The resistance is one of the parameters that describes the performance of Lithium-ion (Li-ion) batteries, as it offers information about the battery efficiency and its power capability. However, similar to other performance parameters of Li-ion batteries, the resistance is dependent on the operatingconditions and increases while the battery is aging. Traditionally, to capture these dependencies, Li-ion cells are aged at different conditions using synthetic mission profiles and periodically the aging tests are stopped in order to measure the resistance at standard conditions. Most of the times, even though accurate information about the resistance behavior is obtained, they do not reflect the behavior from real-life applications. Thus, in this work we propose a method for extracting, modelling, and predicting the resistance directly from the battery dynamic mission profile. While the extraction mainly relied on data manipulation and bookkeeping, the modelling and subsequent prediction of the resistance used a log-linear model.",
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Vilsen, SB, Kær, SK & Stroe, D-I 2019, Predicting Lithium-ion Battery Resistance Degradation using a Log-Linear Model. i Proceedings of 2019 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE Press, s. 1136-1143, 2019 IEEE Energy Conversion Congress and Exposition (ECCE), Baltimore, USA, 29/09/2019. https://doi.org/10.1109/ECCE.2019.8912770

Predicting Lithium-ion Battery Resistance Degradation using a Log-Linear Model. / Vilsen, Søren Byg; Kær, Søren Knudsen; Stroe, Daniel-Ioan.

Proceedings of 2019 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE Press, 2019. s. 1136-1143.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

TY - GEN

T1 - Predicting Lithium-ion Battery Resistance Degradation using a Log-Linear Model

AU - Vilsen, Søren Byg

AU - Kær, Søren Knudsen

AU - Stroe, Daniel-Ioan

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N2 - The resistance is one of the parameters that describes the performance of Lithium-ion (Li-ion) batteries, as it offers information about the battery efficiency and its power capability. However, similar to other performance parameters of Li-ion batteries, the resistance is dependent on the operatingconditions and increases while the battery is aging. Traditionally, to capture these dependencies, Li-ion cells are aged at different conditions using synthetic mission profiles and periodically the aging tests are stopped in order to measure the resistance at standard conditions. Most of the times, even though accurate information about the resistance behavior is obtained, they do not reflect the behavior from real-life applications. Thus, in this work we propose a method for extracting, modelling, and predicting the resistance directly from the battery dynamic mission profile. While the extraction mainly relied on data manipulation and bookkeeping, the modelling and subsequent prediction of the resistance used a log-linear model.

AB - The resistance is one of the parameters that describes the performance of Lithium-ion (Li-ion) batteries, as it offers information about the battery efficiency and its power capability. However, similar to other performance parameters of Li-ion batteries, the resistance is dependent on the operatingconditions and increases while the battery is aging. Traditionally, to capture these dependencies, Li-ion cells are aged at different conditions using synthetic mission profiles and periodically the aging tests are stopped in order to measure the resistance at standard conditions. Most of the times, even though accurate information about the resistance behavior is obtained, they do not reflect the behavior from real-life applications. Thus, in this work we propose a method for extracting, modelling, and predicting the resistance directly from the battery dynamic mission profile. While the extraction mainly relied on data manipulation and bookkeeping, the modelling and subsequent prediction of the resistance used a log-linear model.

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Vilsen SB, Kær SK, Stroe D-I. Predicting Lithium-ion Battery Resistance Degradation using a Log-Linear Model. I Proceedings of 2019 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE Press. 2019. s. 1136-1143 https://doi.org/10.1109/ECCE.2019.8912770