Non-intrusive auto-detecting and adaptive hybrid scheme for multiscale heat transfer: Thermal runaway in a battery pack

Accurately capturing and simulating multiscale systems is a formidable challenge, as both spatial and temporal scales can span many orders of magnitude. Rigorous upscaling methods not only ensure efficient computation, but also guarantee that errors remain within a priori prescribed limits. This provides a balance between computational costs and accuracy. However, the most significant difficulties arise when the conditions under which upscaled models can be applied cease to hold. To address this, we develop an automatic-detecting and adaptive, nonintrusive two-sided hybrid method for multiscale heat transfer and apply it to thermal runaway in a battery pack. To allow adaptive hybrid simulations, two kernels are developed to dynamically map the values between the fine-scale and the upscaled subdomains in a single simulation. The accuracy of the developed hybrid method is demonstrated through conducting a series of thermal runaway test cases in a battery pack. Our results show that the maximum spatial errors consistently remain below the threshold bounded by upscaling errors. • An auto-detecting, adaptive hybrid method is developed for battery thermal runaway. • Adaptation criteria are based on the applicability of the upscaled equations. • Upscaling and downscaling kernels are developed for mapping between subdomains. • The accuracy of the hybrid method has been verified against fine-scale simulations. • Errors of the hybrid method are bounded by the theoretical upscaling error.

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Publication Details

Journal
International Journal of Heat and Mass Transfer
Published
2025-04-20
DOI
https://doi.org/10.1016/j.ijheatmasstransfer.2025.127003
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Non-intrusive auto-detecting and adaptive hybrid scheme for multiscale heat transfer: Thermal runaway in a battery pack

Ilenia Battiato, Yinuo Yao
International Journal of Heat and Mass Transfer
Advanced Battery Technologies Research
article

Non-intrusive auto-detecting and adaptive hybrid scheme for multiscale heat transfer: Thermal runaway in a battery pack

Ilenia Battiato, Yinuo Yao
article en

Abstract

Accurately capturing and simulating multiscale systems is a formidable challenge, as both spatial and temporal scales can span many orders of magnitude. Rigorous upscaling methods not only ensure efficient computation, but also guarantee that errors remain within a priori prescribed limits. This provides a balance between computational costs and accuracy. However, the most significant difficulties arise when the conditions under which upscaled models can be applied cease to hold. To address this, we develop an automatic-detecting and adaptive, nonintrusive two-sided hybrid method for multiscale heat transfer and apply it to thermal runaway in a battery pack. To allow adaptive hybrid simulations, two kernels are developed to dynamically map the values between the fine-scale and the upscaled subdomains in a single simulation. The accuracy of the developed hybrid method is demonstrated through conducting a series of thermal runaway test cases in a battery pack. Our results show that the maximum spatial errors consistently remain below the threshold bounded by upscaling errors. • An auto-detecting, adaptive hybrid method is developed for battery thermal runaway. • Adaptation criteria are based on the applicability of the upscaled equations. • Upscaling and downscaling kernels are developed for mapping between subdomains. • The accuracy of the hybrid method has been verified against fine-scale simulations. • Errors of the hybrid method are bounded by the theoretical upscaling error.

International Journal of Heat and Mass TransferVol. 247
Defense Advanced Research Projects Agency, Defense Sciences Office, DARPA
Affordable and clean energy
Openalex Percentile: Top 93%
Advanced Battery Technologies Research
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