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外文期刊>International Journal of Electrochemical Science
>The Power State Estimation Method for High Energy Ternary Lithium-ion Batteries Based on the Online Collaborative Equivalent Modeling and Adaptive Correction - Unscented Kalman Filter
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The Power State Estimation Method for High Energy Ternary Lithium-ion Batteries Based on the Online Collaborative Equivalent Modeling and Adaptive Correction - Unscented Kalman Filter
Accurate power state estimation plays an important role in the real-time working state monitoring andsafety control of high energy lithium-ion batteries. To solve the difficulty and low accuracy problems inits real-time power state estimation under various operating conditions, the working characteristics ofthe lithium cobalt oxide batteries are analyzed comprehensively under various operating conditions. Animproved collaborative equivalent model is established to characterize its working characteristics andthen the initial power state value is calibrated by using the experimental relationship between open circuitvoltage and state of charge considering the importance of the precious estimation accuracy for the lateriterate calculation and correction. And then, an adaptive correction - Unscented Kalman Filter algorithmis put forward and applied for the state of charge estimation and output voltage tracking so as to realizethe real-time high-precision lithium-ion battery power state estimation. The experimental results showthat the established model can predict the power state of high energy lithium-ion batteries convenientlywith high convergency speed within 30 seconds, accurate output voltage tracking effect within 32 mVand high accuracy, the max estimation error of which is 3.87%, providing an effective working statemonitoring and safety protection method in the cleaner production and power supply processes of thehigh energy lithium-ion batteries.
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