pith:A24RM5J3
System Identification of Lithium-Ion Battery Equivalent Circuit Models Using Ensemble Kalman Inversion
Ensemble Kalman inversion identifies parameters in lithium-ion battery models with accurate results and rapid convergence.
arxiv:2604.10813 v2 · 2026-04-12 · eess.SY · cs.SY
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\pithnumber{A24RM5J3N77MQO5SOWJDPSKMJD}
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Claims
The results demonstrate that the proposed approach achieves accurate parameter estimation with rapid iterative convergence, and it shows strong potential for application to other battery models.
That the local Gaussian approximations in ensemble Kalman inversion remain adequate for the strongly nonlinear and multi-physics battery dynamics, and that the collected data sufficiently excites all relevant parameters without unmodeled disturbances.
Ensemble Kalman inversion achieves accurate parameter estimation with rapid convergence for nonlinear electro-thermal battery models in both simulation and experiments.
Receipt and verification
| First computed | 2026-05-26T02:04:10.535544Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
06b916753b6ffec83bb2759237c94c48e7c87f7550135fccdbe2d9b7ed27a8c4
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/A24RM5J3N77MQO5SOWJDPSKMJD \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 06b916753b6ffec83bb2759237c94c48e7c87f7550135fccdbe2d9b7ed27a8c4
Canonical record JSON
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