A Distributed Analytical Electro-Thermal Model for Pouch-Type Lithium-Ion Batteries
Bibliographic record
Abstract
An analytic multi-physics model for pouch-type lithium-ion (Li-ion) batteries is presented. Both electrical and thermal processes are considered in the model to resolve their interplay on heat generation and battery thermal behavior. Voltage response of a sample Li-ion battery during galvanostatic discharge processes is measured to obtain a concentration-independent polarization expression. By numerically solving the charge balance equation on positive and negative electrodes in conjugation with the polarization expression, it is shown that the transfer current between the electrodes remains approximately constant, in particular when depth-of-discharge is less than 90%. Based on this observation, the electrochemical performance of the battery is simplified, and by using the method of separation of variables a closed-form electrical model is proposed. Joule heating on each electrode, calculated from the electrical model, is used as a local heat source in a two-dimensional battery thermal model. The distributed thermal model is solved analytically with the method of integral transform. The analytical results are successfully validated through comparisons with experimental and numerical data. It is confirmed that ohmic heating in the electrodes contributes to a relatively small portion (8-18%) of the total heat generation; nonetheless, since this heat is highly localized it results in spatial non-uniformity in temperature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".