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• W4376269185 abstract "Accurate ultracapacitor state of charge (SOC) estimation directly affects safety, durability and reliability of hybrid energy storage system. For that, this paper presents a multistate joint estimation method of ultracapacitor based on trans-scale dual extended Kalman filter to predict SOC and model parameters in real-time. Firstly, an ultracapacitor model is established by using experimental data. Then, the model is combined with two Kalman filters, one of which is used to estimate SOC, and another one is applied to achieve trans-scale update the model parameters. Finally, the effectiveness of the method is verified in the urban dynamometer driving schedule at different temperatures. The validation results show that the mean absolute errors of voltage, SOC and capacity estimation are within 0.49 mV, 0.63% and 0.04 Ah, respectively. Moreover, compared with the other two traditional SOC estimation methods, whose results show that the proposed algorithm has higher estimation accuracy and more stable convergence ability." @default.
• W4376269185 created "2023-05-13" @default.
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• W4376269185 date "2023-08-01" @default.
• W4376269185 modified "2023-10-18" @default.
• W4376269185 title "Multistate joint estimation of ultracapacitor based on trans-scale dual extended Kalman filter" @default.
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• W4376269185 doi "https://doi.org/10.1016/j.conengprac.2023.105555" @default.
• W4376269185 hasPublicationYear "2023" @default.
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