Mathematical modelling for optimization of truck tyres selection
This thesis, which consists of an introduction and three appended papers, concerns the optimal selection of tyres for a given vehicle configuration and an operating environment in which the vehicle is to be used. The optimization problem stems from an industrial project performed in cooperation between Chalmers University of Technology and Volvo Group Trucks Technology (GTT). The project began in August 2012 and the expected termination is in January 2016.
We analyze the tyres selection problem from the mathematical optimization point of view. Our aim is to develop a tool for determining an optimal set of tyres for each vehicle and operating environment specification. The overall purpose is to reduce the cost of operations---which is in this case measured by fuel consumption and tyre wear---while preserving the levels of other tyre dependent features such as startability, handling, and ride comfort. We develop a computationally efficient vehicle dynamics model of the vehicle, the tyres, and the operating environment. The tyres are modelled using a surrogate model of the rolling resistance coefficient, i.e., the energy losses caused by the tyre. The development of the surrogate model motivated the development of a methodology for connecting the existing expert knowledge about a certain simulation-based function into its radial basis function interpolation. Suitable solvers for the resulting optimization model with a simulation-based objective function and simulation-based constraints have also been identified by a~literature review.
An algorithm for the global optimization of a combinatorial set of problem instances has been developed and tested on a set of test problem instances. This algorithm enables a computationally efficient search for an approximately optimal tyre design for each vehicle configuration and each operating environment specification, in case at least one such design does exist.
combinatorial set of problem instances
rolling resistance coefficient
radial basis function interpolation
truck tyres selection