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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
Classification performance of the proposed method is investigated by using the concept of Bhattacharyya distance
📌 3 Key Takeaways
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Objective & Hypothesis:Öz This work proposes a methodology for determining the state-of-health (SOH) of rechargeable batteries.
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Key Findings & Data:A generic electrical circuit model is used as a rechargeable battery model.
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Conclusion & Impact:Classification performance of the proposed method is investigated by using the concept of Bhattacharyya distance
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Anahtar Kelimeler Rechargeable battery · battery state-of-health · quadratic discriminant analysis
Özet
Öz This work proposes a methodology for determining the state-of-health (SOH) of rechargeable batteries. A generic electrical circuit model is used as a rechargeable battery model. Model parameters are identified by an algorithm based on extended Kalman filtering (EKF). Estimated battery parameters are used as classification features in quadratic discriminant analysis. Classification performance of the proposed method is investigated by using the concept of Bhattacharyya distance
Keywords
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Cite This Article
BARLAK, C., ÖZKAZANÇ, Y. (2010). DETERMINATION OF BATTERY STATE-OF-HEALTH VIA STATISTICAL CLASSIFICATION. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, Cilt: 52 - Sayı: 2, 1–9. https://ajindex.com/articles/51193