Implementation of adaptive neuro-fuzzy inference system in modeling and estimating the state-of-charge of Lithium-Ion batteries

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NASIRI MOHAMMAD; Kazemi Mohammad Hossein

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Paper Information

Journal: THE CSI JOURNAL ON COMPUTING SCIENCE AND INFORMATION TECHNOLOGY Year:2021 | Volume:19 | Issue:1 Page(s): 122-127

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Title

Implementation of adaptive neuro-fuzzy inference system in modeling and estimating the state-of-charge of Lithium-Ion batteries

Author(s)

NASIRI MOHAMMAD | Kazemi Mohammad Hossein | Issue Writer Certificate

Keywords

State

charge

Neuro

fuzzy inference system

Kalman filter

Abstract

In this paper, a nero-fuzzy inference system based on the State-space modeling of Lithium-Ion batteries is used to estimate the State-of-charge (SOC). The battery terminal voltage and current as laboratory sampling data are used for battery modeling. The moving window based on least square error method is applied in different operating windows to identify the parameters of the system and then the identified parameters are uses for training an adaptive Neuro-fuzzy inference system. Then, by exploiting the Kalman filter theory, an algorithm is proposed for State-of-charge estimation. Three kind of practical data are gathered separately from battery terminal voltage and current for training of the nero-fuzzy system, evaluating of trained model, and proposed estimation algorithm. Finally, the estimation results of the proposed algorithm are compared with some existing algorithms that show the effectiveness of the proposed.

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APA: Copy

NASIRI, MOHAMMAD, & Kazemi, Mohammad Hossein. (2021). Implementation of adaptive neuro-fuzzy inference system in modeling and estimating the state-of-charge of Lithium-Ion batteries. THE CSI JOURNAL ON COMPUTING SCIENCE AND INFORMATION TECHNOLOGY, 19(1 ), 122-127. SID. https://sid.ir/paper/986578/en

Vancouver: Copy

NASIRI MOHAMMAD, Kazemi Mohammad Hossein. Implementation of adaptive neuro-fuzzy inference system in modeling and estimating the state-of-charge of Lithium-Ion batteries. THE CSI JOURNAL ON COMPUTING SCIENCE AND INFORMATION TECHNOLOGY[Internet]. 2021;19(1 ):122-127. Available from: https://sid.ir/paper/986578/en

IEEE: Copy

MOHAMMAD NASIRI, and Mohammad Hossein Kazemi, “Implementation of adaptive neuro-fuzzy inference system in modeling and estimating the state-of-charge of Lithium-Ion batteries,” THE CSI JOURNAL ON COMPUTING SCIENCE AND INFORMATION TECHNOLOGY, vol. 19, no. 1 , pp. 122–127, 2021, [Online]. Available: https://sid.ir/paper/986578/en

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