A phenomenological stress decomposition framework for electro–mechanical state awareness in all-solid-state batteries
Year: 2026
Type: article
Abstract: All-solid-state batteries (ASSBs) exhibit strong electro–mechanical coupling behavior due to stress-dependent solid–solid interfacial contact, making accurate state estimation challenging. To address this issue, an electro–mechanical coupling modeling and joint state estimation framework based on mechanical stress evolution is proposed. A phenomenological mechanical model incorporating mechanical static stress, dynamic diffusion stress, and thermal stress is established and bidirectionally coupled with a second-order RC equivalent circuit model. The proposed stress decomposition framework enables quantitative analysis of the contributions from electrode expansion, diffusion relaxation, and thermal expansion under different operating conditions. Furthermore, a multidimensional parameter mapping among state of charge (SOC), mechanical stress, and temperature is constructed to characterize interfacial contact evolution. Based on the coupled state-space model, an adaptive Strong-Tracking Square-Root cubature kalman filter (ASTSCKF) algorithm is developed for joint online estimation of SOC and mechanical stress. Experimental results under different preload forces, temperatures, constant-power discharge, and dynamic stress test (DST) conditions demonstrate that the proposed method achieves accurate SOC and voltage prediction with high robustness. Stress decomposition results reveal that mechanical static stress dominates the overall stress evolution, while dynamic diffusion stress becomes more significant under pulse-current excitation and thermal stress increases with temperature. The proposed framework provides a physically interpretable approach for electro–mechanical state awareness and intelligent management of ASSBs.
Source: Applied Energy
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,430
Awards: G2849818424, G7410634315
OpenAlex ID: W7218679359
