Arcola has leading capability in modelling of hybrid powertrains in real world applications – an essential foundation for powertrain design.
Our powertrain modelling allows us to define and interrogate fuel cell and battery sizing, heat recovery and power management strategies. We have collaborated with partners, including world-leading academics, to ensure our powertrain model is representative, verified and optimised.
Key to our approach is the combination of science-based (“academic”) modelling with actual powertrain component (“engineering”) models. This means that our optimised designs are immediately realisable (no unobtainium required) and costed. We can thus design and build power systems to meet end-user performance requirements whilst and also achieving optimal efficiency, capital cost, through-life cost and TCO.
“Building a detailed understanding and model of real-world vehicle duty-cycles typically enables the powertrain to be down-sized. Using a smaller fuel cell and battery results in lower BoM cost, better fuel economy and reduced lifetime costs“.
It is often the case, particularly for diesel vehicles, that power-flows and fuel consumption are not logged or well understood. To address these limitations, we have developed a wide range of mechanisms for providing input data for our modelling – including GIS, powertrain hardware specification and vehicle parameters, carry-on loggers, CAN logging and individual sensors.
Our flexible approach allows initial estimates to be made quickly (even from route timetables) and then continually refined as better data becomes available. All of our modelling is done on a through-route-basis (second-by-second); this is critical to understanding the implications of route profiles, which for example have a strong impact on battery sizing.
Through-route modelling also allows for variations in performance and efficiency of powertrain components to be captured (e.g. motor & power electronics efficiency may be significantly influenced by battery state-of-charge) and thus results are significantly more reliable than estimations based on fixed parameters and peak and average power requirements. Inclusion of heat transfer in the model enables understanding and optimisation of fuel cell and battery lifetime as well as evaluation of options for waste-heat recovery.
Read more about Powertrain modelling at Arcola Energy
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