Simulation, Estimation, and Experimentation of Vehicle Longitudinal Dynamics That Effect Fuel Economy

Abstract

In this thesis, longitudinal vehicle dynamics are researched with an emphasis on heavy trucks and fuel economy. Commercial vehicles display large variations in their parameters, and due to many current trends in transportation systems, estimating these parameters has been the subject of much research. Additionally, fuel economy enhancement has become a major issue due to man-kind’s reliance on oil. In this research a longitudinal truck model is developed and the longitudinal dynamics are simulated in various conditions. Algorithms are developed to estimate vehicle parameters and are used in simulation to perform an analysis of their accuracy. Simulated results show the difficulty of estimating individual vehicle parameters in the presence of sensor noise and low levels of vehicle excitation, such as with the heavy trucks at the Auburn University National Center for Asphalt Technology facility. Finally, a class 8 commercial vehicle is instrumented as a test-bed. Estimation results from the test bed support the simulation, while simple parameters are shown to be identified with reasonable accuracy. Road load data for fuel economy evaluation was also collected on the trucks and variations over the asphalt sections are shown.