Process Systems Enterprise Limited
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Fuel cell modeling, simulation and optimization

The benefits of modelling

We save $250K every time we avoid the need to build a test rig

– major US fuel cell developer

fuel cell stack

The key benefit of modelling is the ability to base design and operational decisions on accurate numbers generated by high-fidelity predictive models.

This helps to accelerate development while at the same time reducing risk and cost, and resulting in better designs.

Faster time-to-market at lower cost

Modelling helps reduce time-to-market by allowing the design space to be explored more rapidly and cost-effectively.

Once a validated predictive model has been constructed it can be used to optimise virtually any aspect of component and system design and operation at a relatively small incremental cost.

Reduced physical testing and more effective experimentation

Modelling helps developers to screen out less successful designs or inappropriate materials before proceeding to physical testing. This provides an immediate saving in time and money.

Similarly, model-based data analysis techniques help to pinpoint areas where data is weak and where further research is required, by providing a reliable quantitative measure of the risk involved in using a particular item of data.

Having identified areas of risk, model-based experiment design technologies can can be used to design the optimal 'next set of experiments' to obtain the maximum amount of parameter information, saving further time and resources.

These capabilities allow companies to focus valuable R&D resources where they are required. Unnecessary, time-consuming and costly experimentation and physical testing can be eliminated or significantly reduced.

Specific benefits of modelling

The reasons that more and more companies are systematically turning to high-accuracy predictive modelling are to:

  • accelerate innovation in fuel cell component and system design and operation
  • design components and systems taking all effects into account simultaneously
  • support all decisions using accurate numbers
  • screen design alternatives quickly and reduce physical testing
  • quantify and manage the risk involved in design decisions
  • improve equipment designs – for example, using accurate predictive modelling to determine the effects on performance of geometry changes
  • optimise operational performance and troubleshoot
  • improve the effectiveness of R&D experimentation to reduce time and costs
  • integrate experimentation and engineering design more closely
  • generally, speed up time-to-market while saving money.

The "soft benefits"

An equally important "soft benefit" is that modelling provides a means to capture knowledge and understanding, and transfer this between the different groups involved in the development.

Experience in the companies who have adopted a systematic approach to modelling is that this provides significant scope for parallel rather than sequential working between different disciplines.

The most significant benefits are of course achieved by embarking on modelling early on in the development process. A reliable membrane model can be used for quantification of cell stack effects; a reliable cell-stack model can be used for control design and analysis of system dynamics, and so on.

Not only is the time invested in model development repaid many times over, but a consistent basis is used for all stages of design.