Enabling certifiable eVTOL battery systems: model-based structural isolation of concurrent electro-thermal faults

Battery fault diagnosis is a prerequisite for safety certification in electric vertical take-off and landing (eVTOL) aircraft. Unlike ground vehicles, eVTOL systems operate under a zero-failure tolerance regime, where even minor battery anomalies can compromise flight safety. However, existing diagnostic methods exhibit two fundamental limitations: their structural dependence on single-fault assumptions and limited adaptability to high-rate electro-thermal coupling under aviation duty cycles. To address these challenges, this study proposes a structurally decoupled, model-based diagnostic framework for battery modules. A cell-level electro-thermal coupling model is established to capture dynamic electrical–thermal interactions under high discharge rates. Based on structural analysis, four minimal structurally over-constrained subsystems are constructed to generate analytically decoupled residuals. This design enables systematic isolation of seven fault categories, including short circuits, interconnection faults, and multiple sensor failures, while preserving diagnosability under concurrent fault conditions. Kalman filtering enhances state estimation robustness, and an adaptive threshold strategy accommodates varying operational regimes. Under single-fault scenarios, the proposed method achieves a detection rate of 93.88%, enabling complete isolation and parameter estimation of all seven fault types. More critically, under concurrent-fault scenarios in a 10S3P module with 4,323 possible fault-pair combinations, 85.5% are uniquely identified and 98.3% are reduced to fewer than three candidates. These results demonstrate that structural residual design, rather than data-driven pattern recognition, is essential for achieving certifiable multi-fault diagnosability in next-generation eVTOL battery systems. • An EKF-based electro-thermal coupling model is proposed for eVTOL battery modules. • A residual-based multi-fault diagnosis for short circuit, poor connection and sensor faults. • Quantitative fault-severity assessment under 5.8% MAPE. • Concurrent-fault isolation with 85.5% full isolation rate.