A Comparative Study of SOC Estimation Based on Equivalent Circuit Models
Why this work is in the frame
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Bibliographic record
Abstract
This article presents a comparative study of the state of charge (SOC) estimation using Kalman filter (KF)-based estimators and H-infinity filter. The aim of this research is to obtain the optimal estimator by evaluating the SOC accuracy, robustness, and computation time under varying current noise assumptions. In the KF-based estimators, the extended Kalman filter (EKF), unscented Kalman filter (UKF), and cubature Kalman filter (CKF) are mostly used in the SOC estimation area. The mixed driving cycle profiles are used to test the battery to simulate the complex driving conditions in real electric vehicles (EVs). Also, white noise and bias noise are added into the current data to imitate the inaccurate sensors in EVs. The normal equivalent circuit models (ECMs) and augmented ECMs with varying RC branches are thoroughly compared to acquire the best estimator under varying situations.
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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 | 0.001 | 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 | 0.001 | 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 it