Proactive Fault Detection in EV Batteries Via Hybrid Method: Cell-to-Cell Variation Pattern and Physics-Based Model Insights FEV Pvt, Limited

Format:

Book

Conference/Event

Author/Creator:

Jawle, Bharat Sanjay, author.

Selvakumar, Ashwin, author.

Puttoji Rao, Nagaraj Kumar, author.

Conference Name:

WCX SAE World Congress Experience (2026-04-14 : Detroit, Michigan, United States)

Language:

English

Subjects (All):

Battery packs.

Fault detection.

Electric vehicles.

Batteries.

Local Subjects:

Battery packs.

Fault detection.

Electric vehicles.

Batteries.

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2026

Summary:

This study presents a distinct methodology for the early detection of faulty cells in electric vehicle (EV) battery systems, leveraging temporal voltage deviation patterns under real-world charging scenarios alongside outputs from a physics-based model. A comparative longitudinal analysis was conducted on a fleet of twelve EVssix exhibiting stable performance and the other six demonstrating early-stage anomalies characterized by intermittent transitions from drive to neutral mode. These behavioral cues were investigated as precursors to deeper battery degradation. The analysis focused on cell-level voltage dispersion in battery pack during the mid-to-high state-of-charge (SoC) range (approximately 2030% to full charge). Vehicles in healthy condition consistently displayed minimal voltage deviation between BMS-measured cell voltages and physics-based model predictions, whereas those with latent faults showed markedly higher variance, particularly between the highest battery and model-expected cell voltages. Notably, this voltage divergence was often accompanied by a modest yet recurrent thermal rise of 23°C, suggesting early-stage thermal non-uniformity. All vehicles were monitored over extended distances under diverse, real-world driving and environmental conditions, enhancing the robustness and generalizability of the findings. The proposed approach underscores the diagnostic value of tracking voltage deviation trajectories as a non-intrusive, scalable means of forecasting cell-level degradation. This framework could significantly advance predictive maintenance strategies, improving both the reliability and operational lifespan of EV battery packs

Notes:

Vendor supplied data

Access Restriction:

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