A multi-stress universal degradation framework for lithium-ion batteries in diverse energy storage scenarios

Battery energy storage systems (BESS) have become essential infrastructure for power grids with high renewable energy penetration, providing critical services including frequency containment reserve (FCR), peak shaving (PS), and photovoltaic (PV) integration. The complex degradation behavior of lithium-ion batteries (LIBs) across diverse operational scenarios necessitates robust models for optimal BESS management. This work presents a universal semi-empirical degradation framework that systematically integrates calendar and cycle aging mechanisms under realistic multi-stress conditions. The proposed model incorporates multiple stress factors such as temperature, C-rate, depth of discharge (DoD), and state of charge (SoC), derived from comprehensive analysis of BESS mission profiles across FCR, PS, and PV applications. Through systematic validation on a battery aging dataset, the proposed framework demonstrates exceptional accuracy with R2 above 0.94. Critical findings reveal that cycle number and DoD emerge as the dominant factors governing battery degradation across these applications. The validated framework provides quantitative insights for optimal BESS deployment strategies, enabling improved lifetime prediction, maintenance scheduling, and economic feasibility assessment. This universal approach addresses fundamental gaps in existing degradation models and offers practical tools for BESS stakeholders to enhance system reliability and economic performance in renewable energy integration applications.