Steidel, S., Halfmann, T., Baecker, M., and Gallrein, A., "Prediction of Rolling Resistance and Tread Wear of Tires in Realistic Commercial Vehicle Application Scenarios," SAE Technical Paper 2016-01-8027, 2016, doi:10.4271/2016-01-8027.
Rolling resistance and tread wear of tires do particularly influence the maintenance costs of commercial vehicles. Although tire labeling is established in Europe, it is meanwhile well-known that, due to the respective test procedures, these labels do not hold in realistic application scenarios in the field. This circumstance arises from the development phase of tires, where the respective performance properties are mainly evaluated in tire/wheel standalone scenarios in which the wide range of usage variability of commercial vehicles cannot be considered adequately. Within this article we address a method to predict indicators for rolling resistance and tread wear of tires in realistic application scenarios considering application-based factors of influence like specific customers, operation circumstances, regional dependencies, fleet specific characteristics etc. Moreover, the prescribed methodology may also be transferred to the prediction of fuel consumption and pollutant emission. The basic framework of the overall procedure is based on a geo-referenced description of the world. This framework is realized in the software tool VMC® (Virtual Measurement Campaign) which allows a systematic analysis of the usage variability of commercial vehicles in the sense mentioned above. The basic idea for predicting rolling resistance and tread wear of tires is the decomposition of actual routes into a suitable set of load cases depending on curvature radius, longitudinal slope and velocity. The respective tire energy losses are computed for all load cases - by means of a simulation model of the vehicle equipped with a CDTire/3D tire model - and are finally stored in a result catalogue. In order to predict the tire energy loss for a realistic application scenario one partitions actual routes into the predefined load cases and superposes the total energy loss from the result catalogue.