The Incremental Capacity (IC) analysis is used to characterise the capacity and the battery state of health, aged by cycling patterns with randomly selected pulsed current levels and duration. The batteries are periodically characterised at 1C current, which is a high value with respect to the typical IC tests in pseudo-equilibrium condition. The high-current IC curves generation from raw voltage/current data includes two filtering stages, one for the input voltage and one for the incremental capacity curve smoothing, which are optimised for the application on the basis of the data characteristics. The correlations between the IC main peak features and the battery full capacity for 28 Lithium-Cobalt oxide batteries with 18650 packaging were evaluated, finding that the main peak area is a general feature to evaluate the state of health under high current tests and random usage pattern, and, therefore, it can be used as a battery health indicator in practical applications. The effects of the computational parameters on the relationship between the peak area and the battery capacity are also investigated. The results are confirmed by a further analysis performed over an additional set of cells with different technology, aged with a fixed cycling pattern. Additionally, the performance of the peak area as a health indicator was compared with an ohmic resistance-based estimation approach.
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