A Grey Box Model Approach for the Prediction of Tire Energy Loss
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The maintenance costs of vehicles, and particularly commercial vehicles, are influenced by rolling resistance and tread wear of tires. In this context, the tire label is established in Europe for indicating the energy efficiency of a tire, although the respective test procedures do not reflect realistic application scenarios in daily use. Therefore, we propose a grey box model approach for predicting rolling resistance and tread wear of tires, i.e., tire energy losses, as a function of route, vehicle, driver and traffic parameters by means of physical models for the vehicle and tire dynamics in combination with machine learning techniques. This enables the prediction of tire energy loss for different customer groups in arbitrary regions around the world under realistic conditions.
KeywordsTire simulation Tire energy loss Machine learning Neural networks Support vector machines
The authors thank Amrut Pisolkar and the CDTire-Team for supporting the generation of the training data via CDTire/Driver. Moreover, we thank Simon Gottschalk for assisting the analysis of the present validation data.
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