Comparison of Model-Based and Sensor-Based Detection of Thermal Runaway in Li-Ion Battery Modules for Automotive Application

Klink, Jacob; Hebenbrock, André; Grabow, Jens; Orazov, Nury; Nylén, Ulf; Benger, Ralf; Beck, Hans-Peter

doi:10.3390/batteries8040034

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Comparison of Model-Based and Sensor-Based Detection of Thermal Runaway in Li-Ion Battery Modules for Automotive Application

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Research Center Energy Storage Technologies, Clausthal University of Technology, Am Stollen 19A, 38640 Goslar, Germany

Battery Performance & Cell Development, Scania CV AB, 151 87 Södertälje, Sweden

Institute of Electrical Power Engineering and Electrical Energy Engineering, Clausthal University of Technology, Leibnizstraße 28, 38678 Clausthal-Zellerfeld, Germany

Author to whom correspondence should be addressed.

Academic Editors: Binghe Liu, Lubing Wang, Yuqi Huang, Yongjun Pan and Carlos Ziebert

Batteries 2022, 8(4), 34; https://doi.org/10.3390/batteries8040034

Received: 1 March 2022 / Revised: 4 April 2022 / Accepted: 7 April 2022 / Published: 12 April 2022

(This article belongs to the Topic Safety of Lithium-ion Batteries)

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Abstract

In recent years, research on lithium–ion (Li-ion) battery safety and fault detection has become an important topic, providing a broad range of methods for evaluating the cell state based on voltage and temperature measurements. However, other measurement quantities and close-to-application test setups have only been sparsely considered, and there has been no comparison in between methods. In this work, the feasibility of a multi-sensor setup for the detection of Thermal Runaway failure of automotive-size Li-ion battery modules have been investigated in comparison to a model-based approach. For experimental validation, Thermal Runaway tests were conducted in a close-to-application configuration of module and battery case—triggered by external heating with two different heating rates. By two repetitions of each experiment, a high accordance of characteristics and results has been achieved and the signal feasibility for fault detection has been discussed. The model-based method, that had previously been published, recognised the thermal fault in the fastest way—significantly prior to the required 5 min pre-warning time. This requirement was also achieved with smoke and gas sensors in most test runs. Additional criteria for evaluating detection approaches besides detection time have been discussed to provide a good starting point for choosing a suitable approach that is dependent on application defined requirements, e.g., acceptable complexity. View Full-Text

Keywords: lithium-ion battery module; fault detection; thermal runaway; thermal fault; external heating; battery safety

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MDPI and ACS Style

Klink, J.; Hebenbrock, A.; Grabow, J.; Orazov, N.; Nylén, U.; Benger, R.; Beck, H.-P. Comparison of Model-Based and Sensor-Based Detection of Thermal Runaway in Li-Ion Battery Modules for Automotive Application. Batteries 2022, 8, 34. https://doi.org/10.3390/batteries8040034

AMA Style

Klink J, Hebenbrock A, Grabow J, Orazov N, Nylén U, Benger R, Beck H-P. Comparison of Model-Based and Sensor-Based Detection of Thermal Runaway in Li-Ion Battery Modules for Automotive Application. Batteries. 2022; 8(4):34. https://doi.org/10.3390/batteries8040034

Chicago/Turabian Style

Klink, Jacob, André Hebenbrock, Jens Grabow, Nury Orazov, Ulf Nylén, Ralf Benger, and Hans-Peter Beck. 2022. "Comparison of Model-Based and Sensor-Based Detection of Thermal Runaway in Li-Ion Battery Modules for Automotive Application" Batteries 8, no. 4: 34. https://doi.org/10.3390/batteries8040034

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Comparison of Model-Based and Sensor-Based Detection of Thermal Runaway in Li-Ion Battery Modules for Automotive Application

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