EnergyStorage
Task 8 / 47
BatteryFastChargingSPMe
Staged fast-charge optimization under a reduced SPMe-T-Aging–style coupled electrochemical, thermal, and aging model, including proxies for plating and fade. It is more physics-heavy than profile-only tasks and scores feasible trajectories against composite objectives for BMS-oriented algorithms.
Model leaderboard
| # | Participant | Score |
|---|---|---|
| 1 | GPT-5.4 | 100.0 |
| 2 | Gemini 3.1 Pro Preview | 40.1 |
| 3 | DeepSeek V3.2 | 37.5 |
| 4 | Qwen3 Coder Next | 14.1 |
| 5 | GLM-5 | 12.3 |
| 6 | Grok 4.20 | 9.1 |
| 7 | SEED 2.0 Pro | 9.0 |
| 8 | Claude Opus 4.6 | 0.0 |
Framework leaderboard
| # | Participant | Score |
|---|---|---|
| 1 | GPT-OSS + ShinkaiEvolve | 100.0 |
| 2 | GPT-OSS + OpenEvolve | 98.5 |
| 3 | GPT-OSS + ABMCTS | 81.1 |
| 4 | Claude Opus 4.6 + OpenEvolve | 36.7 |
| 5 | Claude Opus 4.6 + ABMCTS | 30.6 |
| 6 | Claude Opus 4.6 + ShinkaiEvolve | 0.0 |
Score is the normalized score for this task (0–100, higher is better).