Journals / Turkish Journal of Electrical Engineering and Computer Science / 2017 / Cilt: 25 - Sayı: 4

A parametric battery state of health estimation method for electric vehicle applications

Pages
2860–2870
Publication Date
2017-08-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The proposed method works successfully in both conditions with maximum error less than 5%.

📌 3 Key Takeaways

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Objective & Hypothesis:Lithium-ion batteries are commonly preferred in electric vehicle applications.
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Key Findings & Data:The relative capacity and state of health of a battery decrease with age.
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Conclusion & Impact:The proposed method works successfully in both conditions with maximum error less than 5%.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Lithium-ion batteries · battery management systems · battery state of health

Abstract

Lithium-ion batteries are commonly preferred in electric vehicle applications. The relative capacity and state of health of a battery decrease with age. Therefore, accurate estimation of these parameters is essential. In this study a parametrical approach for estimation of battery state of health is proposed. A hybrid battery model that has a maximum error less than 3% is used. The relative capacity of the battery is estimated by using performance decrement with age. The method is validated by two different set of experiments. The first set is conducted with batteries that were aged by a controlled process and the second set is conducted with randomly aged batteries. The proposed method works successfully in both conditions with maximum error less than 5%.

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Cite This Article

SARIKURT, T., CEYLAN, M., BALIKÇI, A. (2017). A parametric battery state of health estimation method for electric vehicle applications. Turkish Journal of Electrical Engineering and Computer Science, Cilt: 25 - Sayı: 4, 2860–2870. https://ajindex.com/articles/187358

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