High-Temperature Proton-Exchange Membrane Fuel Cells (HT-PEMFCs) are a candidate for electrical energy supply devices in more and more applications. Most notably in the aeronautic industry. Before any use, an HT-PEMFC is preheated and after that supplied with its active gases. Only at this state, the diagnostics can be performed. A method of testing not requiring a complete start-up would be beneficial for many reasons. This article describes an extended version of the charging and discharging diagnostic method of HT-PEMFCs with no active gases. This extended approach is named “Test Without Active Gases” (TWAG). This paper presents original research on the influence of nitrogen temperature and pressure on the HT-PEMFC response to charging and discharging. A lumped-element model of an HT-PEMFC is also presented. A numerical result of using this model to recreate an experimentally obtained curve is also presented.

The problem of lithium-ion cells, which degrade in time on their own and while used, causes a significant decrease in total capacity and an increase in inner resistance. So, it is important to have a way to predict and simulate the remaining usability of batteries. The process and description of cell degradation are very complex and depend on various variables. Classical methods are based, on the one hand, on fitting a somewhat arbitrary parametric function to laboratory data and, on the other hand, on electrochemical modelling of the physics of degradation. Alternative solutions are machine learning ones or nonparametric ones like support-vector machines or the Gaussian process (GP), which we used in this case. Besides using the GP, our approach is based on current knowledge of how to use non-parametric approaches for modeling the electrochemical state of batteries. It also uses two different ways of dealing with GP problems, like maximum likelihood type II (ML-II) methods and the Monte Carlo Markov Chain (MCMC) sampling.