Modelling of temperature dependent impedance in lithium ion polymer batteries and impact analysis on electric vehicles
Bibliographic record
Abstract
The objective of this work is to demonstrate a temperature-dependent impedance model for high-power lithium-ion polymer cells used in modern Electric Vehicles (EV). The impedance model is combined with a self-heating thermal model for system simulations, in order to predict the impact of different cell types on the overall EV performance, under real-world urban and highway drive-cycles. Measurements show that the internal resistance is almost doubled when the ambient temperature is lowered from 20° C to 5°C. This has a drastic impact on the EV's ability to satisfy the load current requirements without performance lags, and justifies the importance of the modelling approach. When operating in cold climates, it is observed that the Battery Thermal Management System (BTMS) must strike a balance between EV range and performance, as the stored energy should be optimally distributed between the propulsion and heating systems.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".