Comparison of Model-Based and Sensor-Based Detection of Thermal Runaway in Li-Ion Battery Modules for Automotive Application. Klink, J., Hebenbrock, A., Grabow, J., Orazov, N., Nylén, U., Benger, R., & Beck, H. Batteries, 8(4):34, April, 2022. ![Comparison of Model-Based and Sensor-Based Detection of Thermal Runaway in Li-Ion Battery Modules for Automotive Application [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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.
@article{klink_comparison_2022,
title = {Comparison of {Model}-{Based} and {Sensor}-{Based} {Detection} of {Thermal} {Runaway} in {Li}-{Ion} {Battery} {Modules} for {Automotive} {Application}},
volume = {8},
copyright = {https://creativecommons.org/licenses/by/4.0/},
issn = {2313-0105},
url = {https://www.mdpi.com/2313-0105/8/4/34},
doi = {10.3390/batteries8040034},
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.},
language = {en},
number = {4},
urldate = {2025-05-16},
journal = {Batteries},
author = {Klink, Jacob and Hebenbrock, André and Grabow, Jens and Orazov, Nury and Nylén, Ulf and Benger, Ralf and Beck, Hans-Peter},
month = apr,
year = {2022},
pages = {34},
}
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