Litcius/Paper detail

Data-driven strategy: A robust battery anomaly detection method for short circuit fault based on mixed features and autoencoder

Hongyu Zhao, Chengzhong Zhang, Chenglin Liao, Liye Wang, Weilong Liu, Lifang Wang

2025Applied Energy16 citationsDOI

Topics & Concepts

AutoencoderAnomaly detectionFault (geology)Battery (electricity)Computer scienceFault detection and isolationPattern recognition (psychology)Anomaly (physics)Artificial intelligenceData miningEngineeringDeep learningPhysicsPower (physics)ActuatorGeologyCondensed matter physicsSeismologyQuantum mechanicsAdvanced Battery Technologies ResearchAdvancements in Battery MaterialsFault Detection and Control Systems
Data-driven strategy: A robust battery anomaly detection method for short circuit fault based on mixed features and autoencoder | Litcius