Each week, we select a recently published Open Access article to feature. This week’s article comes from Applied Stochastic Models in Business and Industry   and proposes a class of linear models for describing the capacity paths of lithium-ion batteries (LIB).

The article’s abstract is given below, with the full article available to read here.

Schmitz, C, Kamps, U, Kateri, M. A longitudinal degradation set-up for calendar aging of lithium-ion batteries in view of sparse experimental data. Appl Stochastic Models Bus Ind. 2023; 1– 15. doi: 10.1002/asmb.2774

A class of linear models for describing the capacity paths of lithium-ion batteries (LIB) is proposed in case of sparse data from a calendar aging experiment. This way the reliability of LIB is monitored and modeled based on degradation data. The introduced family of models allows for random effects and includes tuning parameters, both of which make it a powerful tool for modeling LIB capacities. Because of sparsity of data, a procedure for simulating degradation data based on the model fitted on the sampled data is discussed and illustrated. The robustness of such models against misspecification in terms of tuning parameters is assessed by a simulation study.