An extensive model for renewable energy electrochemical storage with Solid Oxide Cells based on a comprehensive analysis of impedance deconvolution

Solid Oxide Cells are potentially one of the most efficient energy conversion systems, yet unfavourable operating conditions may cause a performance drop. These electrochemical devices can be operated in reversible mode (fuel cell /electrolysers); therefore, they are suitable in chemical storage applications. However, reversible operation and inversion cycles further jeopardise performance stability. Advanced processing of experimental data such as Distribution of Relaxation Times (DRT) on Electrochemical Impedance Spectroscopy (EIS) measurements is a powerful tool to investigate physicochemical processes occurring in Solid Oxide Cells and to analyse ageing mechanisms. This paper presents a method to identify the main processes behind polarisation losses in order to build an equivalent circuit model (ECM) suitable for real-time diagnosis based on EIS. The fuel cell operation is chosen as a reference for degradation detection and diagnosis. A comprehensive experimental campaign was executed on a commercial cell operated in fuel cell mode in a laboratory test apparatus by systematically varying operating temperature, current density, fuel flow and its composition. DRT deconvolution highlights five main processes, namely: oxygen transport and charge transfer in the anode, anodic diffusion, charge transfer at the cathode and cathodic diffusion. Therefore, the proposed ECM for the cell can be schematised as LR0(R(a1)Q(a1))(R(a2)Q(a2))W-FLWaG(R(c1)Q(c1)). Beyond determining the model, a complete look-up table for the circuital elements is built thanks to EIS measurements fit. This is a rich database for solid oxide fuel cell electrochemical performance simulation, and it allows the future implementation of the model in a useful diagnostic tool, even in the broader case of reversible operation in energy storage systems.

Automated summary

Solid Oxide Cells are efficient energy conversion systems, but unfavorable operating conditions can cause performance drop, especially in reversible and inversion cycles. Advanced data processing and equivalent circuit modeling can help diagnose aging mechanisms and build a real-time diagnostic tool for fuel cell operation.