Battery aging assessment: from critical insights to enhanced diagnosis

Energy & Environmental Science 2026 Open access

Read full text
Authors: Yunhong Che, Joachim Schaeffer, Jinwook Rhyu, Liang Wu, Patrick A. Asinger, Minsu Kim, Jacob Sass, Rolf Findeisen, Martin Z. Bazant, William C. Chueh, Richard D Braatz
DOI: 10.1039/d5ee06439b
Cited by: 2
References: 60

Abstract

Rate-adaptive, mechanistic-aware model converts high C-rate features into low-rate equivalents and corrects aging-induced mismatches via residual learning, enabling rapid, interpretable health diagnostics and early cycle-life prediction.

Fields of Study & Subjects

Advanced Battery Technologies Research Advanced battery technologies research Advanced Battery Materials and Technologies

Publication details

Journal / source
Energy & Environmental Science
Publisher
Royal Society of Chemistry (RSC)
Volume
19
Issue
6
Pages
1954–1968
Publication date
1 January 2026
Language
EN