State of Charge Estimation for Lithium-Ion Batteries in Electric and Hybrid Vehicles

Ege Anil Bostan, Volkan Sezer

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

Özet

In recent years, the electric vehicles (EVs) earned reputation due to increasing global warming potential and depletion of fossil fuels. Although EVs became popular, they have still some unsolved challenges such as their range issue. In order to solve their range issue their battery management system (BMS), functioning lithium-ion battery should estimate the state of charge (SOC) correctly to provide safe operation. In this paper, several SOC estimation approaches have been investigated to get accurate SOC. They have been presented and analyzed in terms of the estimation accuracy. For model- based approaches including Extended Kalman Filter (EKF) battery equivalent circuit model has been developed to simulate the dynamic behavior of 51 Ah NMC lithium-ion battery cell. The real world dynamometer measurement data (HPPC WLTP, etc.) have been used to identify and validate the model parameters. According to the results, EKF based estimation provides the best performance comparing to the other approaches.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıELECO 2019 - 11th International Conference on Electrical and Electronics Engineering
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar34-38
Sayfa sayısı5
ISBN (Elektronik)9786050112757
DOI'lar
Yayın durumuYayınlandı - Kas 2019
Etkinlik11th International Conference on Electrical and Electronics Engineering, ELECO 2019 - Bursa, Turkey
Süre: 28 Kas 201930 Kas 2019

Yayın serisi

AdıELECO 2019 - 11th International Conference on Electrical and Electronics Engineering

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???event.eventtypes.event.conference???11th International Conference on Electrical and Electronics Engineering, ELECO 2019
Ülke/BölgeTurkey
ŞehirBursa
Periyot28/11/1930/11/19

Bibliyografik not

Publisher Copyright:
© 2019 Chamber of Turkish Electrical Engineers.

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