Thermal performance prediction of the battery surface via dynamic mode decomposition
The heat dissipation from the battery surface significantly affects battery performance and lifetime. This study proposes a new and an alternative method to predict the thermal performance of the battery operation according to the surface temperature gradients and heat & exergy losses by using a...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/155511 |
| _version_ | 1826126879726239744 |
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| author | Kanbur, Baris Burak Kumtepeli, Volkan Duan, Fei |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Kanbur, Baris Burak Kumtepeli, Volkan Duan, Fei |
| author_sort | Kanbur, Baris Burak |
| collection | NTU |
| description | The heat dissipation from the battery surface significantly affects battery performance and lifetime. This study proposes a new and an alternative method to predict the thermal performance of the battery operation according to the surface temperature gradients and heat & exergy losses by using a data-driven dynamic mode decomposition method, which is new for thermal flows. To predict the thermal gradients, a 10 min long experiment is performed via an infrared thermographic camera for a commercial Li-polymer battery of a smartphone. The camera collects the thermal images on the battery surface along 1 min as the data training period at first; then, the proposed method predicts the surface temperature gradients for the rest of the experimental period, 5 min. The temperature gradients on the battery surface are well predicted with less than 1% error whereas the heat dissipation and the exergy loss are predicted with the maximum error values of 2.75% and 5.30%, respectively. According to the error probability distribution plots, the vast majority of the occurred error is less than ±5%. The results prove the fast prediction ability of the proposed technique and show promising outcomes for further improvement studies. |
| first_indexed | 2024-10-01T06:59:35Z |
| format | Journal Article |
| id | ntu-10356/155511 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:59:35Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1555112022-03-03T07:54:49Z Thermal performance prediction of the battery surface via dynamic mode decomposition Kanbur, Baris Burak Kumtepeli, Volkan Duan, Fei School of Mechanical and Aerospace Engineering Interdisciplinary Graduate School (IGS) Energy Research Institute @ NTU (ERI@N) Engineering::Mechanical engineering Battery Thermal Management Exergy Analysis The heat dissipation from the battery surface significantly affects battery performance and lifetime. This study proposes a new and an alternative method to predict the thermal performance of the battery operation according to the surface temperature gradients and heat & exergy losses by using a data-driven dynamic mode decomposition method, which is new for thermal flows. To predict the thermal gradients, a 10 min long experiment is performed via an infrared thermographic camera for a commercial Li-polymer battery of a smartphone. The camera collects the thermal images on the battery surface along 1 min as the data training period at first; then, the proposed method predicts the surface temperature gradients for the rest of the experimental period, 5 min. The temperature gradients on the battery surface are well predicted with less than 1% error whereas the heat dissipation and the exergy loss are predicted with the maximum error values of 2.75% and 5.30%, respectively. According to the error probability distribution plots, the vast majority of the occurred error is less than ±5%. The results prove the fast prediction ability of the proposed technique and show promising outcomes for further improvement studies. 2022-03-03T07:54:48Z 2022-03-03T07:54:48Z 2020 Journal Article Kanbur, B. B., Kumtepeli, V. & Duan, F. (2020). Thermal performance prediction of the battery surface via dynamic mode decomposition. Energy, 201, 117642-. https://dx.doi.org/10.1016/j.energy.2020.117642 0360-5442 https://hdl.handle.net/10356/155511 10.1016/j.energy.2020.117642 2-s2.0-85084089184 201 117642 en Energy © 2020 Elsevier Ltd. All rights reserved. |
| spellingShingle | Engineering::Mechanical engineering Battery Thermal Management Exergy Analysis Kanbur, Baris Burak Kumtepeli, Volkan Duan, Fei Thermal performance prediction of the battery surface via dynamic mode decomposition |
| title | Thermal performance prediction of the battery surface via dynamic mode decomposition |
| title_full | Thermal performance prediction of the battery surface via dynamic mode decomposition |
| title_fullStr | Thermal performance prediction of the battery surface via dynamic mode decomposition |
| title_full_unstemmed | Thermal performance prediction of the battery surface via dynamic mode decomposition |
| title_short | Thermal performance prediction of the battery surface via dynamic mode decomposition |
| title_sort | thermal performance prediction of the battery surface via dynamic mode decomposition |
| topic | Engineering::Mechanical engineering Battery Thermal Management Exergy Analysis |
| url | https://hdl.handle.net/10356/155511 |
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