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High Resolution Image Download MS PowerPoint Slide Well-to-wheel (WTW) performance is an important metric for alternative fuels. Current methods for model-based fuel design optimize either the well-to-tank (WTT) or the tank-to-wheel (TTW) performance, and address the respectively other aspect only indirectly, e.g., via simple approximations, if at all. To enable WTW fuel design, we combine a superstructure-based WTT fuel design method with a TTW model that estimates achievable engine efficiencies with a dynamic, zero-dimensional engine model. For computational tractability, we approximate the engine model with an artificial neural network as surrogate model. We then design alternative fuels with optimal WTW performance. We find that aiming at very strong TTW performance by means of an aggressive constraint on the research octane number can impair the WTW performance. Alternative fuels for tailored engines offer significantly more flexibility in terms of fuel components and production processes and thus potential for cost and global warming impact reductions than drop-in fuels designed with the same superstructure. The findings emphasize the importance of addressing the entire life cycle of a fuel at early stage design.
Ackermann et al. (Thu,) studied this question.