Battery heating strategy to enhance fast-charge performance at low temperatures
Bibliographic record
Abstract
• Considerations for BTMS design for fast-charging time reduction in extremely cold conditions. • Evaluation of the impact of fast charging without preheating under cold conditions. • Simulation model with battery and BTMS thermal models for fast charging. • Analysis of heating effects on charging costs, including power consumption during heating. • Suggested optimizing BTMS design by balancing the heater capacity and thermal management strategies. Fast-charge of lithium-ion batteries (LiBs) in battery-powered electric vehicles (BEVs) can be completed within 15 min at 20 °C. However, at subzero temperatures the in-vehicle battery management system (BMS) limits charging speed to ensure battery safety, leading to prolonged charging times and long queues at charging stations. Active battery heating strategies are necessary to overcome this limitation, requiring more heat than conventional systems with a target range of 0–5 °C designed to prevent Li-plating. While improving coolant channel design is important, efficient heat utilization within integrated EV thermal management systems (TMS) is increasing attention. This study assessed heating demands for reducing fast-charge times and the influence of heating capacity on charging performance, including charging times, costs, and battery cell temperatures. An equivalent circuit model and a thermal model of a PTC heater-based battery thermal management systems (BTMS) were developed to simulate heating load scenarios, heating during fast-charge and single-heating. The results showed that heating during fast-charge, even without preheating, significantly reduced charging time. At − 7°C, it decreased from 3 h to 62 min, and at − 20 °C with a larger heater capacity, it remained under 60 min, with additional heating costs remaining negligible at less than $1. However, the impact of higher heater capacities on charging efficiency and temperature imbalances must be carefully evaluated. This study will contribute to the advancement of BTMS designs for enhancing fast-charge performance and provides a foundation for the development of integrated EV TMS for the cabin, powertrain, and battery.
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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 | 0.000 |
| 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 | 0.001 |
| 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".