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**Harvard**

Sabartova, Z., Lindroth, P., Strömberg, A. och Patriksson, M. (2014) *An optimization model for truck tyres selection*.

** BibTeX **

@conference{

Sabartova2014,

author={Sabartova, Zuzana and Lindroth, Peter and Strömberg, Ann-Brith and Patriksson, Michael},

title={An optimization model for truck tyres selection},

booktitle={Proceedings of the 4th International Conference on Engineering Optimization, ENGOPT 2014; Lisbon; Portugal; 8 September 2014 through 11 September 2014},

isbn={978-1-138-02725-1},

pages={561-566},

abstract={To improve the truck tyre selection process at Volvo Group Trucks Technology which is currently based on convention rather than on scientific methodology, an optimization model has been developed with the aim of determining an optimal set of tyres for each vehicle and operating environment specification. The overall purpose is to reduce the cost of operation, 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 have developed a joint model of the vehicle, the tyres, and the operating environment. The model is based on vehicle dynamics equations describing the vehicle and is implemented in Matlab and Simulink. To be able to distinguish between different tyres, the part of the model describing tyres must be able to describe more complex properties than the commonly used Pacejka's model. Hence, a surrogate model of the function describing the rolling resistance coefficient of a truck tyre and regression models of vertical and lateral stiffness have been developed and inserted into the part of the model describing tyres; the surrogate model is based on sample points evaluated through a finite element analysis. The road is then generated based on the operating environment classification of the actual truck.
Since the resulting optimization model has a simulation-based objective function and simulation-based constraints, a global derivative-free optimization algorithm has to be used to solve the problem. Characteristics of available solvers for the resulting optimization problem, i.e., rbfSolve, EGO, ConstrLMSRBF, and NOMAD, are discussed.},

year={2014},

}

** RefWorks **

RT Conference Proceedings

SR Electronic

ID 205166

A1 Sabartova, Zuzana

A1 Lindroth, Peter

A1 Strömberg, Ann-Brith

A1 Patriksson, Michael

T1 An optimization model for truck tyres selection

YR 2014

T2 Proceedings of the 4th International Conference on Engineering Optimization, ENGOPT 2014; Lisbon; Portugal; 8 September 2014 through 11 September 2014

SN 978-1-138-02725-1

SP 561

OP 566

AB To improve the truck tyre selection process at Volvo Group Trucks Technology which is currently based on convention rather than on scientific methodology, an optimization model has been developed with the aim of determining an optimal set of tyres for each vehicle and operating environment specification. The overall purpose is to reduce the cost of operation, 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 have developed a joint model of the vehicle, the tyres, and the operating environment. The model is based on vehicle dynamics equations describing the vehicle and is implemented in Matlab and Simulink. To be able to distinguish between different tyres, the part of the model describing tyres must be able to describe more complex properties than the commonly used Pacejka's model. Hence, a surrogate model of the function describing the rolling resistance coefficient of a truck tyre and regression models of vertical and lateral stiffness have been developed and inserted into the part of the model describing tyres; the surrogate model is based on sample points evaluated through a finite element analysis. The road is then generated based on the operating environment classification of the actual truck.
Since the resulting optimization model has a simulation-based objective function and simulation-based constraints, a global derivative-free optimization algorithm has to be used to solve the problem. Characteristics of available solvers for the resulting optimization problem, i.e., rbfSolve, EGO, ConstrLMSRBF, and NOMAD, are discussed.

LA eng

DO 10.1201/b17488-101

LK http://dx.doi.org/10.1201/b17488-101

OL 30