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- W4387011738 abstract "An improved AUKF algorithm is proposed based on the adaptive traceless Kalman filter (AUKF), and the main factors that affect SOC estimation are parametrically corrected in the algorithm. The goal of this research is to be able to accurately estimate the battery state of charge (SOC) of lithium batteries. In order to do this, the main factors that affect the accuracy of battery SOC estimation as well as the advantages and disadvantages of traditional battery SOC estimation are considered. The algorithm is derived from the second-order RC equivalent circuit model of the battery. To obtain the improved AUKF algorithm, the output deviation covariance of each measurement is taken as the noise covariance. This allows the noise covariance to be updated with time and eliminates the issue that the noise covariance is a constant source of error. The results of the experiments demonstrate that an upgraded version of the AUKF algorithm may provide an accurate estimation of the battery SOC value." @default.
- W4387011738 created "2023-09-26" @default.
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- W4387011738 date "2023-09-25" @default.
- W4387011738 modified "2023-09-26" @default.
- W4387011738 title "Study on SOC estimation of lithium battery based on improved AUKF algorithm" @default.
- W4387011738 doi "https://doi.org/10.1117/12.3004422" @default.
- W4387011738 hasPublicationYear "2023" @default.
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