{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T12:18:45Z","timestamp":1789042725515,"version":"build-2803163510"},"reference-count":29,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T00:00:00Z","timestamp":1788998400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003661","name":"Korea Government","doi-asserted-by":"publisher","award":["P0029836"],"award-info":[{"award-number":["P0029836"]}],"id":[{"id":"10.13039\/501100003661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Batteries"],"abstract":"<jats:p>Accurate battery state estimation is essential for electric-vehicle battery management systems (BMSs), directly improving their safety, durability, and operational reliability. This study proposes an integrated degradation-diagnosis framework that is, to our knowledge, among the first to combine electrochemical impedance spectroscopy (EIS), direct-current internal resistance (DCIR), and state of health (SoH) within a single, quantitative, low-complexity analysis of a hybrid-vehicle NCM811 lithium-ion battery module. Cycling-test data measured at 0, 400, 800, and 1200 cycles were reanalyzed using power-law regression, end-of-life (EOL) extrapolation, and cross-metric correlation analysis; the dataset was then extended to 2000 cycles (six checkpoints in total) to test the reliability of long-term lifetime prediction. Three findings are experimentally demonstrated. First, the ohmic resistance remained essentially constant during cycling, whereas the interfacial resistance increased by +422.7%, identifying interfacial (not bulk) resistance growth as the dominant degradation pathway. Second, power-law models substantially outperformed conventional exponential models for RE, DCIR, and SoH (R2 = 0.998, 0.999, and 0.990, respectively, vs. R2 = 0.870 for the exponential SoH model); extending the dataset from four to six checkpoints narrowed the resulting EOL model-form uncertainty from a 3.5-fold to a 1.6-fold discrepancy (2776 vs. 9831 cycles, narrowing to 3124 vs. 4908 cycles). Third, a strong linear relationship between DCIR and SoH (R2 = 0.956) was obtained, indicating that resistance-only monitoring can approximate SoH without full impedance measurement. Beyond these demonstrated results, the proposed framework offers potential value for SoH estimation, battery condition diagnosis, and state-estimation algorithm development in advanced BMSs; these broader applications have not been experimentally validated in this study and are discussed as directions for future work.<\/jats:p>","DOI":"10.3390\/batteries12090357","type":"journal-article","created":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T11:38:39Z","timestamp":1789040319000},"page":"357","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrated Analysis of EIS, DCIR, and SoH for Degradation Diagnosis and Durability Assessment of NCM811 Lithium-Ion Batteries"],"prefix":"10.3390","volume":"12","author":[{"given":"Hongjong","family":"Lee","sequence":"first","affiliation":[{"name":"Electric Powertrain R&D Division, Korea Automotive Technology Institute, Pungse-ro, Pungse-myeon, Cheonan-si 31214, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Byunghyun","family":"Lee","sequence":"additional","affiliation":[{"name":"Electric Powertrain R&D Division, Korea Automotive Technology Institute, Pungse-ro, Pungse-myeon, Cheonan-si 31214, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kwonse","family":"Kim","sequence":"additional","affiliation":[{"name":"Automotive Engineering Department, Ajou Motor College, Daehak-gil, Jupo-myeon, Boryeong-si 33415, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,10]]},"reference":[{"key":"ref_1","first-page":"104488","article-title":"Batteries and Sustainability: The Relevance of Life Cycle Assessment","volume":"82","author":"Barbosa","year":"2025","journal-title":"Sustain. 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