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• W2955194639 abstract "Accurate estimation of the state of charge (SOC) of a lithium-ion battery in electric vehicles closely depends on the health status of the current and voltage acquisition sensors. In this paper, a simple and effective model-based sensor fault detection method for lithium-ion batteries is presented. In this method, the SOC of the battery is estimated in real time by the unscented Kalman filter (UKF), and the ampere-time integration method can calculate the cumulative discharge&#x002F;charge amount for a certain period. Therefore, the ratio of the amount of SOC change to the amount of charge&#x002F;discharge during a certain period is the estimated capacity. The difference between the capacity used for SOC estimation and the estimated capacity is defined as the residual used to detect whether a sensor failure has occurred. The proposed sensor fault detection method was verified by the dynamic stress test." @default.
• W2955194639 created "2019-07-12" @default.
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• W2955194639 date "2019-04-01" @default.
• W2955194639 modified "2023-09-23" @default.
• W2955194639 title "Model-Based Sensor Fault Detection for Lithium-Ion Batteries in Electric Vehicles" @default.
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• W2955194639 doi "https://doi.org/10.1109/vtcspring.2019.8746512" @default.
• W2955194639 hasPublicationYear "2019" @default.
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