A Comprehensive Comparison of the Phase Change Material-Based Internal and External Cooling Systems
Bibliographic record
Abstract
Being employed in a wide range of energy storage applications, such as solar energy storage systems and electric vehicles (EVs), lithium-ion batteries (LIBs) have become an important link in the chain of clean energy harvest and delivery and have played a crucial role in low-carbon energy transitions. Thermal management is critical for maintaining the efficiency, safety, and longevity of LIBs due to the exothermic behavior and high temperature sensitivity of LIBs. A desirable thermal management system should be able to help sustain a desired operating temperature range and a small temperature gradient within batteries. The heat accumulation effect in the center of cylindrical LIBs has been observed and experimentally studied by Shah et al. [1] and Zhang et al. [2]. The insufficient cooling at the battery center can cause temperature nonuniformity and lead to performance degradation of batteries in long-term operation. We have previously reported a phase change material (PCM)-based internal cooling system for alleviating the heat accumulation in 18650-type LIBs [3, 4]. In this presentation, the internal cooling system will be thoroughly compared with an external PCM-based cooling system in terms of their weight and volume added to the entire battery systems, their cooling effectiveness for single batteries of different sizes and radial thermal conductivities, and the necessity of increasing the thermal conductivity of PCM through adding additives. References: [1] K. Shah, C. Mckee, D. Chalise, and A. Jain, Energy , 113 , 852-860 (2016). [2] G. Zhang, L. Cao, S. Ge, C. Y. Wang, C. E., Shaffer, and C. D. Rahn, J. Electrochem. Soc. , 161 , 1499-1507 (2014). [3] R. Zhao, J. Gu, and J. Liu, Int. J. Energy. Res. , 42 , 2728-2740 (2018). [4] R. Zhao, J. Gu, and J. Liu, Energy , 135 , 811-822 (2017). Figure Caption: Figure 1. Comparison of the measured and simulated temperature profiles of the a) internally and b) externally cooled single cell, where T 1 , T 2 , and T 3 are the temperatures measured at the battery center, battery surface, and plastic case surface, respectively. The tests were performed in a wind tunnel under natural convection with a convective heat transfer coefficient of 20 W m -2 K -1 . Figure 1
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".