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State of Charge Estimation Function based on Kalman Filter

version 3.1.0 (2.33 MB) by Fauzia Khanum
An EKF_SOC_Estimation function estimates a battery's terminal voltage and state of charge using a second order RC equivalent circuit.

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Updated 29 Jun 2021

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The EKF_SOC_Estimation function estimates a battery's terminal voltage (Vt) and state of charge (SOC) using a second order RC equivalent circuit model. The function can be used either an extended Kalman Filter (EKF) or adaptive-extended Kalman filter (AEKF). Users also have the options of estimating SOC from -20C to 40C. Included is a sample LA92 driving cycle, battery parameters including internal resistance, and SOC-OCV curve for a Turnigy battery cell. To run the sample, simply download all the file and run main.mlx.

Cite As

F. Khanum, E. Louback, F. Duperly, C. Jenkins, P. J. Kollmeyer, and A. Emadi, “A Kalman Filter Based Battery State of Charge Estimation MATLAB Function,” in 2021 IEEE Transportation Electrification Conference & Expo, 2021, pp. 484 - 489.

MATLAB Release Compatibility
Created with R2021a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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