... combining data- and model-driven techniques for battery health estimation, estimating both capacity loss and resistance increase. Specifically, we use a Bayesian method, Gaussian process regression, to estimate model parameters as functions of states, operating conditions, and lifetime. Computational...

... ( u i , u j ) = σ f 2   exp ( − | | u i − u j | | 2 2 σ l 2 ) For each track in the multitrack part, we collect the following data for the Gaussian process training: (i) deposition distance of each sampling point s i measured from the start...

... indicated mean effective pressure (IMEP) and peak pressure. To identify the specific impact of each operating parameter on the pressure trace, a surrogate model was produced based on a functional Gaussian process (GP) regression approach. The pressure trace is modeled as a function of the operating...