Abstract
The prediction of capacity degradation, and more generally of the behaviors related to battery aging, is useful in the design and use phases of a battery to help improve the efficiency and reliability of energy systems. In this paper, a stochastic model for the prediction of battery cell degradation is presented. The proposed model takes its cue from an approach based on Markov chains, although it is not comparable to a Markov process, as the transition probabilities vary with the number of cycles that the cell has performed. The proposed model can reproduce the abrupt decrease in the capacity that occurs near the end of life condition (80% of the nominal value of the capacity) for the cells analyzed. Furthermore, we illustrate the ability of this model to predict the capacity trend for a lithium-ion cell with nickel manganese cobalt (NMC) at the cathode and graphite at the anode, subjected to a life cycle in which there are different aging factors, using the results obtained for cells subjected to single aging factors.
Highlights
Over the past two decades, batteries have become an important part of our lifestyle: from portable electronics to electric vehicles, to the recent integration of renewable energy into the power grid
The cells under consideration use a technology based on lithium nickel cobalt manganese oxide (NCM) at the positive electrode and graphite at the negative electrode
Since the anode and cathode compositions are fundamental in the determination of the degradation process of lithium-ion cells, the results obtained during the study are strictly valid only for the analyzed technology
Summary
Over the past two decades, batteries have become an important part of our lifestyle: from portable electronics to electric vehicles, to the recent integration of renewable energy into the power grid. Cycle life is influenced by additional factors, such as the intensity of the current and the depth of discharge of the cycles These aging factors act in such a way that the effects are not linearly correlated, which greatly complicates the understanding and description of the aging process. The temperature represents a very relevant factor in the degradation of the batteries, both in the operating conditions defined by the battery manufacturer, [11,12] and in the case of uncontrolled temperature conditions [12] Since this aging factor has been extensively covered in the literature, in the present work, the temperature remains constant during the life tests, to emphasize the effects of the other stress factors.
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