Title

Interpretable machine learning for battery health insights: A LIME and SHAP-based study on EIS-derived features

Journal title

Bulletin of the Polish Academy of Sciences Technical Sciences

Yearbook

2025

Volume

73

Issue

5

Authors

Etem, Taha

Affiliation

Etem, Taha : Cankiri Karatekin University, Faculty of Engineering, Computer Engineering, Cankiri, Turkiye

Keywords

lithium-ion batteries ; EIS ; distribution of relaxation times ; SHAP ; LIME

Divisions of PAS

Nauki Techniczne

Coverage

e155033

Date

14.07.2025

Type

Article

Identifier

DOI: 10.24425/bpasts.2025.155033