Fuel economy and performance vary significantly with the vehicle design and configuration, road profile, and payload. The variation is more pronounced for heavy-duty trucks and understanding its origin is critical to maximizing fleet profitability. In this paper we demonstrate a method to continuously estimate fuel consumption breakdown over resistive forces while the vehicle is driven on a public highway. The method is fast, cost-effective, and capable of analyzing trip segments as short as one second. The method utilizes a non-linear Kalman filter and a vehicle dynamical model that has a coupled longitudinal and vertical motion.
The paper presents the breakdown of fuel consumption and an estimate of road grade profile obtained by driving a heavy-duty vehicle at the MnROAD research facility in Albertville MN. The road grade profile of the high-volume segment on Westbound Interstate 94 and the fuel consumption breakdown of the MnROAD heavy-duty test truck were estimated from recorded Control Area Network (CAN) signals and known vehicle parameters. The resulting estimates of the grade profile showed accuracy and repeatability within ± 0.15 degrees when compared to grade measured with a high precision differential GPS, thus confirming the accuracy of the estimation method. Also presented is a detailed breakdown of fuel consumption by grade resistance, rolling resistance, aerodynamic resistance, inertial forces, accessories, and driveline components. We discuss the implications of the results for vehicle fuel economy optimization, vehicle customization, and large scale grade profile determination.
