Enhanced thermal management system for Li-ion batteries using phase change material and liquid cooling under realistic driving cycles
Bibliographic record
Abstract
Designing effective thermal management for electric vehicle batteries is crucial for ensuring safety, reliability, while minimizing weight and operational costs. This study examines a hybrid battery thermal management system (HBTMS), integrating liquid-cooled plates with phase change material (PCM). We evaluate both continuous (CC) and intermittent cooling (IC) strategies across four realistic drive cycles and two rapid discharge-charge cycles, with configurations including natural convection, standalone PCM, serpentine cold plate (SCP) without PCM, and hybrid cold plates in serpentine and zig-zag patterns (ZCP) with PCM. The hybrid ZCP enhances thermal performance over traditional designs by increasing coolant turbulence and PCM mixing, reducing system weight by 52.9 % due to the lower density of PCM. Using IC, which adjusts coolant flow based on PCM melt fraction, hybrid ZCP decreases pumping power by up to 83.9 % and reduces coolant flow duration to 13.9 % of total cycle time. Higher coolant velocities lower battery temperatures but increase pumping power, whereas lower inlet temperatures accelerate cooling and PCM solidification. While CC offers better thermal regulation, IC markedly reduces energy consumption while maintaining adequate thermal performance, demonstrating the hybrid ZCP's efficacy. • Developed an efficient hybrid BTMS combining PCM with liquid-cooled plates. • Evaluated under four realistic drive cycles and cyclic rapid discharge conditions. • Hybrid Zig-zag cold plate outperforms traditional designs in cooling efficiency. • Intermittent cooling (IC) strategy ensures precise thermal control across all cases. • Reduction in weight and pumping power by up to 53 % and 84 %, respectively.
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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 | 0.000 | 0.000 |
| 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".