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- W2754190665 abstract "An accurate power-battery state of charge(SOC) estimation plays an important role in battery electric vehicles(EVs). Affected by random factors such as working conditions and environment, Li-ion power battery has very strong time-varying nonlinearity in the application of EVs, the research on SOC estimation of power battery is of great theoretical significance and application value. This paper studies the SOC estimation using extended Kalman filter(EKF), which is based on the Thevenin equivalent circuit model. And then a reasonable optimization method of the parameters of the model is presented to improve the SOC estimation accuracy. The simulation results demonstrate that the optimization method can improve the SOC estimation precision remarkably with little influence on the initial error convergence by means of EKF." @default.
- W2754190665 created "2017-09-25" @default.
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- W2754190665 date "2017-09-21" @default.
- W2754190665 modified "2023-09-27" @default.
- W2754190665 title "SOC Estimation of Extended Kalman Filter Based on the Model Data Optimization" @default.
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- W2754190665 doi "https://doi.org/10.1007/978-981-10-6496-8_39" @default.
- W2754190665 hasPublicationYear "2017" @default.
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