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• W4385990810 abstract "The purpose of this chapter is to extract health indicators strongly related to the health state of energy storage lithium-ion batteries, including the maximum solid-phase lithium-ion concentrations in the positive and negative electrodes, the loss of active material (LAM), and the loss of lithium inventory (LLI). This chapter firstly describes the basic structure of an improved cooperation competition particle swarm optimization (CCPSO) algorithm, and then studies the identification process of important electrochemical parameters in the ESP model using this algorithm. The important electrochemical parameters are the maximum solid-phase lithium-ion concentrations in the positive and negative electrodes. Secondly, based on the incremental capacity-differential voltage (IC-DV) method, this chapter conducts the corresponding quantitative analysis of the LAM and the LLI, which are two lithium-ion degradation modes. Among them, LAM obtains quantification results through IC curves, and LLI obtains quantification results through DV curves. Finally, this chapter studies two correlation analysis methods based on multidimensional health indicators and health state, including Pearson correlation analysis (PCA) method and grey relational analysis (GRA) method, and explains the importance of strong correlation verification between health indicators and health state." @default.
• W4385990810 created "2023-08-19" @default.
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• W4385990810 date "2023-01-01" @default.
• W4385990810 modified "2023-10-14" @default.
• W4385990810 title "Extraction of Multidimensional Health Indicators Based on Lithium-Ion Batteries" @default.
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• W4385990810 doi "https://doi.org/10.1007/978-981-99-5344-8_3" @default.
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