Abstract

Lithium-ion batteries are prone to aging, which decreases the battery performance. The term battery State of Health (SOH) is widely used to describe many different aspects of battery performance. One critical aging characteristic is the loss of cyclable energy quantified by the decrease in capacity. Algorithms that estimate the capacity fade using voltage measurements are widely published in literature and are commonly used in commercial Battery Management Systems (BMS). However, there are fewer studies identifying the aging mechanisms, such as the loss of cyclable lithium, or the loss of active material, both of which manifest as capacity fade. Furthermore, many of these algorithms require voltage measurement data acquired during a full charge or discharge cycle, which is inconvenient to obtain while the battery is in use. In the following, we present a methodology to identify the aging mechanisms by changes in the capacity of active material in each electrode, and the changes in the stoichiometric operating window of the half-cell potentials. The proposed method utilizes measurement obtained from only two operating points, with no requirement on a constant current while traversing between these two operating points. The method is tested via simulating the LiFePO4 (LFP) chemistry, where identification is particularly difficult due to its flat voltage characteristics. Furthermore, unlike previously presented methods, the identifiability of the aging mechanisms is studied with respect to location of the two operating points in the voltage curve. It is important to note that the techniques explored and proposed in this paper rely on opportunistic measurements of terminal voltage after a rest period due to its reliance on the invariant characteristic of the half-cell potentials.

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