Road Load Based Model for Vehicle Repair and Maintenance Cost Estimation

Abstract

A techno-economic model is developed based on road-load simulation results expressed in relation to slip energy (SE) at the tire–pavement interface and the repair and maintenance (R&M) cost obtained from published sources and data from state agencies. Tire SE allows for the consideration of aggressive acceleration and deceleration, high torque conditions (for instance, driving an upslope grade), and roadway curvature. Tire SE data used in this effort were generated using physics-based simulation models of different vehicle types for arrays of road conditions (e.g., grades, curvatures) and driving cycles (i.e., vehicle speed profiles). R&M costs were estimated for various vehicle categories and accumulated vehicle mileage. The approach is based on relating the probability density functions (PDFs) of SE and R&M costs. Asymptotic series expansion for an incomplete gamma function was used to approximate the gamma functions and to determine the gamma ratio function that is used as the coefficient to SE to estimate R&M costs. The average R&M cost per mile results from the model compared with the arithmetic mean R&M cost data from fleet operators and published data. The model can serve as a method for predicting R&M cost as a function of road load to vehicle fleet.