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.

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