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• W2100073360 abstract "Many researchers have worked to develop methods to analyze and characterize capacity fade in lithium-ion batteries. As a complement to approaches to mathematically model capacity fade that require detailed understanding of each mechanism, capacity fade was accurately and efficiently predicted for future cycles using a discrete approach by extrapolating the change in effective transport and kinetic parameters with cycle number (N) for a battery tested under controlled experimental conditions. The effective parameters and their uncertainties are estimated using a mathematical reformulation of a porous electrode model, whose computational efficiency enables the integration of the proposed approach into an inexpensive microprocessor for estimating the remaining lifetime of a battery based on past charge-discharge curves. The approach may also provide some guidance for designers as to which battery components to focus on for redesign to reduce capacity fade." @default.
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• W2100073360 date "2011-01-01" @default.
• W2100073360 modified "2023-10-01" @default.
• W2100073360 title "Parameter Estimation and Capacity Fade Analysis of Lithium-Ion Batteries Using Reformulated Models" @default.
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• W2100073360 doi "https://doi.org/10.1149/1.3609926" @default.
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