fig10

Figure 10. Conceptual workflow for lifecycle-dependent rebalancing between physics-based and data-driven models in battery digital twins. At the beginning-of-life, the digital twin is physics-dominant because the fresh cell remains close to design assumptions and is supported by relatively clean characterization data. During mid-life, the model becomes a balanced hybrid as degradation modes become more separable, but usage histories diverge. At end-of-life, the twin becomes data-enhanced but physics-constrained because cell-to-cell dispersion, localized ageing, and uncertainty dominate management risk. Throughout the lifecycle, the uncertainty-aware fusion layer updates model weights according to incoming evidence, model residuals, and calibration quality. SOH: State of health; RUL: