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State Of Charge And Parameter Estimation Of Electric Vehicle Batteries

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Date

May-18

Authors

Bustos, Richard
Siddique, Abu Raihan Mohammad
Cheema, Taranjit
Gadsden, Stephen Andrew
Mahmud, Shohel

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Abstract

Due to rising global environmental issues, electric vehicles (EV) are growing in popularity and will eventually replace vehicles that use internal combustion engines (ICE). EVs draw their power from batteries. Batteries are highly nonlinear storage elements used in a constantly changing environment making them highly dynamic and mathematically complex. In order to approximate the driving range of an EV, the state of charge (SOC) of the battery, which cannot be directly measured, has to be estimated accurately. SOC is highly dependent on the following parameters: internal resistance, temperature, and open circuit voltage. In this paper, two battery equivalent circuit models (ECM) are analyzed in conjunction with a thermal model to track the inner temperature of the battery. The states of the battery are estimated The copyright for the paper content remains with the author.using the popular Kalman filter (KF) and unscented Kalman filter (UKF), and the results are discussed.

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Keywords

Mechatronics, Robots and Control, Advanced Energy Systems, Transportation Systems, Electric vehicles, Equivalent circuit models, Kalman filter, Interactive multiple model, State of charge

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