EPE Association: EPE 2023 - DS2o: Batteries: Management Systems (BMS), Monitoring and Life-Time Prediction

EPE 2023 - DS2o: Batteries: Management Systems (BMS), Monitoring and Life-Time Prediction
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2023 ECCE Europe - Conference > EPE 2023 - Topic 08: Electric Vehicle Propulsion Systems and their Energy Storage > EPE 2023 - DS2o: Batteries: Management Systems (BMS), Monitoring and Life-Time Prediction

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   Analysis of potential lifetime extension through dynamic battery reconfiguration
By Albert SKEGRO, Changfu ZOU, Torsten WIK [View]
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Abstract: Growing demands for electrification result in increasingly larger battery packs. Due to factors such as cell position in the pack and variations in the manufacturing process, the packs exhibit variations in the performance of their constituent cells. Moreover, due to the fixed cell configuration, the weakest cell renders the pack highly susceptible to these variations. Reconfigurable battery pack systems, which have increased control flexibility due to additional power electronics, present a promising solution for these issues. Nevertheless, to what extent they can prolong the battery lifetime has not been investigated.This simulation study analyzes the potential of dynamic reconfiguration for extending battery lifetime w.r.t. several parameters. Results indicate that the lifetime extension is larger for series than for parallel configurations. For the latter, the dominant factor is equivalent full cycles spread at the end of life, but resistance increase with age and the number of cells in parallel are also influential. Finally, for the former, the number of series-connected elements amplifies these effects.

   Experimental Study on DC Pulse Discharge Preheating of Lithium Ion Batteries at low temperature over a wide frequency range
By Chengwei LUO [View]
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Abstract: The severe degradation of Lithium-ion batteries (LIBs) performance at low temperatures needs to be recovered by preheating, while pulsed preheating is often considered as a good internal preheating method. In this paper, a heating experimental platform for Li-ion power batteries under pulse excitation is built, and the electrochemical impedance spectrum (EIS) and the convective heat transfer coefficient h of experimental 18650 Li-ion batteries are tested to carry out pulse excitation temperature rise experiments in the frequency range of 1Hz~80kHz. The experiments show that the temperature rise rate of lithium-ion battery decreases with increasing frequency in the range of 1Hz-6kHz, and becomes faster with increasing frequency in the range of 6kHz-80kHz, which verifies the validity of the temperature rise model of lithium-ion battery.

   Features extraction for battery SOH estimation from battery pulsed charging operation
By Siyu JIN, Xinming YU, Xin SUI, Wendi GUO, Maitane BERECIBAR, Daniel-Ioan STROE [View]
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Abstract: Pulse charging is recognized as a charging technique for maximizing the life of lithium-ion batteries. In this paper, 10 features are extracted from the battery PC operations for battery state of health prediction. By permuting, combining and comparing features, the prediction performance is improved when using two features as input.

   Lithium-ion Battery SOH Estimation with Varying Amount of Battery Operation Data
By Xingjun LI, Dan YU, Søren Byg VILSEN, Daniel-Ioan STROE [View]
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Abstract: This work estimates SOH of lithium-ion batteries, aged by a forklift driving profile, based on multiple linear regression and compares the estimation accuracy at three levels. Unlike previous research, this work uses dynamic and field data rather than public datasets. The influence of data size and the position to extract features on the SOH estimation accuracy was researched. It is found that extracting features from smaller voltage segments contains more information. The estimation accuracy can be improved by 24.5\% MAPE after the Box-Cox transformation

EPE 2023 - DS2o: Batteries: Management Systems (BMS), Monitoring and Life-Time Prediction
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2023 ECCE Europe - Conference > EPE 2023 - Topic 08: Electric Vehicle Propulsion Systems and their Energy Storage > EPE 2023 - DS2o: Batteries: Management Systems (BMS), Monitoring and Life-Time Prediction
	[return to parent folder]

	Analysis of potential lifetime extension through dynamic battery reconfiguration By Albert SKEGRO, Changfu ZOU, Torsten WIK	[View] [Download]
Abstract: Growing demands for electrification result in increasingly larger battery packs. Due to factors such as cell position in the pack and variations in the manufacturing process, the packs exhibit variations in the performance of their constituent cells. Moreover, due to the fixed cell configuration, the weakest cell renders the pack highly susceptible to these variations. Reconfigurable battery pack systems, which have increased control flexibility due to additional power electronics, present a promising solution for these issues. Nevertheless, to what extent they can prolong the battery lifetime has not been investigated.This simulation study analyzes the potential of dynamic reconfiguration for extending battery lifetime w.r.t. several parameters. Results indicate that the lifetime extension is larger for series than for parallel configurations. For the latter, the dominant factor is equivalent full cycles spread at the end of life, but resistance increase with age and the number of cells in parallel are also influential. Finally, for the former, the number of series-connected elements amplifies these effects.

	Experimental Study on DC Pulse Discharge Preheating of Lithium Ion Batteries at low temperature over a wide frequency range By Chengwei LUO	[View] [Download]
Abstract: The severe degradation of Lithium-ion batteries (LIBs) performance at low temperatures needs to be recovered by preheating, while pulsed preheating is often considered as a good internal preheating method. In this paper, a heating experimental platform for Li-ion power batteries under pulse excitation is built, and the electrochemical impedance spectrum (EIS) and the convective heat transfer coefficient h of experimental 18650 Li-ion batteries are tested to carry out pulse excitation temperature rise experiments in the frequency range of 1Hz~80kHz. The experiments show that the temperature rise rate of lithium-ion battery decreases with increasing frequency in the range of 1Hz-6kHz, and becomes faster with increasing frequency in the range of 6kHz-80kHz, which verifies the validity of the temperature rise model of lithium-ion battery.

	Features extraction for battery SOH estimation from battery pulsed charging operation By Siyu JIN, Xinming YU, Xin SUI, Wendi GUO, Maitane BERECIBAR, Daniel-Ioan STROE	[View] [Download]
Abstract: Pulse charging is recognized as a charging technique for maximizing the life of lithium-ion batteries. In this paper, 10 features are extracted from the battery PC operations for battery state of health prediction. By permuting, combining and comparing features, the prediction performance is improved when using two features as input.

	Lithium-ion Battery SOH Estimation with Varying Amount of Battery Operation Data By Xingjun LI, Dan YU, Søren Byg VILSEN, Daniel-Ioan STROE	[View] [Download]
Abstract: This work estimates SOH of lithium-ion batteries, aged by a forklift driving profile, based on multiple linear regression and compares the estimation accuracy at three levels. Unlike previous research, this work uses dynamic and field data rather than public datasets. The influence of data size and the position to extract features on the SOH estimation accuracy was researched. It is found that extracting features from smaller voltage segments contains more information. The estimation accuracy can be improved by 24.5\% MAPE after the Box-Cox transformation