Mathematical modelling for optimization of truck tyres selection
Licentiatavhandling, 2015

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.

global optimization

simulation-based optimization

combinatorial set of problem instances

rolling resistance coefficient

radial basis function interpolation

truck tyres selection

surrogate model

KB-salen, Kemigården 4, Chalmers University of Technology
Opponent: Oleg Burdakov


Zuzana Sabartova

Chalmers, Matematiska vetenskaper, Matematik

Göteborgs universitet


Hållbar utveckling






KB-salen, Kemigården 4, Chalmers University of Technology

Opponent: Oleg Burdakov

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