Excess vehicle fuel consumption, the percentage change in fuel consumption caused by road roughness, is an important part of the environmental and cost assessment of a pavement’s life cycle. Flexible and efficient computational methods make it possible to use mechanistic models to estimate excess fuel consumption. A stochastic pavement–vehicle interaction model was developed recently based on a half-truck model and stationary road roughness profiles. Although the introduced method was a step forward, it does not allow roll vibration. In addition, the error caused by stationary assumption on roughness profiles has not been quantified. This study proposes a numerical approach to assess the roughness-induced fuel consumption of a semi-trailer truck on non-deformable rough pavements. A three-dimensional (3D) semi-trailer truck model is formulated with a nonstationary parallel road roughness model. The simulation results of the integrated truck–pavement model are validated against empirical formulas. Tire stiffness is identified as the most important truck property, followed by suspension damping, suspension stiffness, and cargo loading. For road roughness characteristics, local roughness variance—overlooked by the stationary assumption—can underestimate excess fuel consumption by 42%. Using the 3D truck model and corresponding roughness profiles as excitation inputs would reduce the computation error by more than 10%. This study also proposes an extended roughness–speed–impact model, considering a second-order International Roughness Index term and effect of local roughness variance. The new regression model increases the prediction explanation R2 from 88.7% to 99.2%.
ASJC Scopus subject areas
- Civil and Structural Engineering
- Mechanical Engineering