Universiti Teknologi Malaysia Institutional Repository

State-of-charge estimation for lithium-ion battery using Busse's adaptive unscented Kalman filter

Yao, L. W. and Aziz, J. A. and Idris, N. R. N. (2016) State-of-charge estimation for lithium-ion battery using Busse's adaptive unscented Kalman filter. In: 2015 IEEE Conference on Energy Conversion, CENCON 2015, 19 - 20 Okt 2015, Johor Bahru, Malaysia.

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

State-of-charge estimation of rechargeable battery is vital to maximize the battery performance and ensure the safe operating condition. This paper presents state-of-charge estimation method for lithium-ion battery using adaptive unscented Kalman Filter. In this aspect, Busse's adaptive rule is implemented to update the process noise covariance of the Kalman filter. Compared with the existing adaptive rules, Busse's rule is relatively simpler and it doesn't require huge memory capacity for storing the voltage residual. The accuracy of the proposed method is verified through experimental studies. A comparison with the unscented Kalman filter algorithms is made to compare the accuracy of each algorithm.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:adaptive unscented Kalman filter, lithium-ion battery, state-of-charge
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:73416
Deposited By: Mohd Zulaihi Zainudin
Deposited On:20 Nov 2017 08:43
Last Modified:20 Nov 2017 08:43

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