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

accelerated
development ...

  ... reduced
      technology
            risk...

...better designs

The key benefit of modelling is the ability to back up design and operational decisions with accurate numbers. This helps to accelerate development while at the same time reducing risk and cost.

Another major benefit is that not only can time-to-market be reduced, but also that design alternatives can easily and rapidly be investigated – in days rather than months – to come up with significantly improved designs.

Once a validated 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.

Reduction in physical testing

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, modelling helps to pinpoint areas where data is weak and where further research is required. This allows companies to focus valuable R&D resources where they are required and eliminate unnecessary time-consuming and potentially costly experimentation.

Framework for analysing experimental data

Modelling also provides a valuable framework in which experimental data can be analysed. Model-based data analysis techniques use the information already within the model to determine accurate model parameters such as kinetic constants.

If performed in the correct way, such analyses are capable of providing a reliable quantitative measure of the risk involved in using a particular item of data on key aspects of the design.

Specific benefits of modelling

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

accelerate fuel cell innovation
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.

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