Aimed at companies bringing fuel cell technology – PEMFC, SOFC and others – to market, GProms Fuel Cell helps reduce time-to-market and optimise fuel stack and system design and operation through the application of predictive modelling, the company said.

GProms Fuel Cell bundles high-fidelity models from PSE’s Advanced Model Library for Fuel Cells (AML: FC) within the GProms modelling and optimisation framework. It allows simultaneous analysis of detailed micro-scale effects and optimisation of cell design and operation within the context of the whole fuel cell system, providing a means to quantitatively manage the technology risk inherent in this technology.

GProms Fuel Cell analyses aspects such current density distribution over the stack, water management (for PEMFC), deactivation and stack longevity, and integration of the stack with fuel processing and other systems. An optional interface can be used to link membrane-electrode assembly (MEA) models with computational fluid dynamics (CFD) models of flow channels for calculation of full-stack performance.

Dynamic modelling provides facilities for control system design, analysing temperature dynamics on change in power demand, and modelling and optimising start-up and other operations. Optimisation capabilities make it possible to determine optimal platinum load and trade-offs between stack size and power output, the company added.

A key use of the high-fidelity cell and stack models is to provide a framework for interpreting experimental data and estimating key model parameters using model-based mathematical techniques.

GProms is used by process industry companies in the oil & gas, chemicals and petrochemicals, power generation, clean energy, food & beverage, FMCG, pharmaceutical and other process sectors.

Zbigniew Urban, chief technical officer and technology leader of fuel cells at PSE, said: “The complex interactions within the fuel cell itself and between stack and system – coupled with time-to-market pressures and the associated technology risk – make modelling an essential tool. There is no other way to address these issues comprehensively.’’