The objective of this article is to identify appropriate low-degree polynomial fuel consumption models for use in intelligent transportation systems (ITSs), eco-drive assist systems, and microscopic traffic simulation software. The different models that are assessed include models found in the literature and new models developed using a subsearch regression based on the Akaike information criterion. The models are evaluated based on model structures and their effectiveness in predicting instantaneous vehicle fuel consumption levels. Measurement data obtained from an engine dynamometer, a chassis dynamometer, and on-road testing are used to conduct the study. The study demonstrates that several low-degree polynomial fuel consumption models with a quadratic control term are appropriate for use in ITS applications (R 2>0.9).
['Bart Saerens', 'Hesham Rakha', 'Kyoungho Ahn', 'Eric Van den Bulck']
Assessment of Alternative Polynomial Fuel Consumption Models for Use in Intelligent Transportation Systems Applications