Washing Machine Design Optimization Based on Dynamics Modeling
Doktorsavhandling, 2011

The spinning process in a washing machine is a source of undesired vibrations and noise and may cause discomfort both to the user as well as for the machine itself due to vibrations which have impact on system lifetime, reliability of operation and capacity. The aim of this thesis is to develop mathematical and computational models of a washing machine of modern type and use these models for dynamics analysis and in optimization routines to make improvements of the machine mechanical design. In the thesis a multibody system model of a commercial front loaded washing machine is presented and used for analysis of the vibration dynamics and system design optimization. The model has been built using a theoretical-experimental methodology consisting of integration of multibody system (MBS) formalism, detailed modeling of machine functional components and experimental data based validation. The complete model of a washing machine is implemented in the commercial MBS environment Adams/View from MSC.Software. Several test rigs for experiments on components and the complete washing machine have been developed. Validation of the developed computational models has shown acceptable agreement both with tub kinematics as well as forces transmitted to the hosting structure. In this thesis the vibrations of a washing machine have been channeled into kinematic, dynamic and stability cost functions. The defined kinematic cost function deals with the tub motion and can be used to ensure margins to collision between parts inside the machine or constitute a step in the process if increasing the system capacity. The dynamic cost function measures transmitted vertical forces to the hosting structure, forces which are found cause the most noise and vibration impact on the surroundings. A cost function based on the necessary and sufficient criterion for stability of a washing machine in the sense of walking avoidance is also presented. The introduced cost functions are used for multiobjective optimization of washing machines, and several problems have been formulated and solved by changing suspension geometry and component parameters. To solve multiobjective optimization problems of a washing machine on a set of spinning operational scenarios a multistep approach has been proposed. The approach reduces the number of variables in the considered generic complex multiobjective constrained optimization problem of a washing machine and makes use of engineering knowledge and other requirements on the system, e.g. such as esthetics. The utilization of several vibration control technologies for washing machines, such as a semi-active suspension system, automatic balancing, etc are also investigated. The solution comprising a magnetorheological damper, validated by incorporation into a washing machine suspension system, giving force propagation amplitude reduction of up to 40% is presented.


Multiobjective Optimization


Vibration dynamics

Washing machine


Semi-active control.

Automatic balancing

sal EA, Hörsalsvägen 11, Chalmers
Opponent: Aki M. Mikkola


Thomas Nygårds

Chalmers, Tillämpad mekanik, Dynamik

Pareto optimization of a washing machine suspension system

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Proc. of The 9th International Conference on Motion and Vibration Control, September 15-18, 2008, Technishe Universitaet Muenchen, Munich, Germany,; Vol. CD proceedings(2008)p. 1-10

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Vibration Control of Washing Machine with Magnetorheological Dampers

Proc. The 8th International Conference on Motion and Vibration Control (MOVIC 2006), August 27-30, 2006, KAIST, Daejeon, Korea,; (2006)p. 480-485

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An Adams/View-Matlab Computational Interface for Clustered Optimization of Washing Machines

Proceedings of the Twenty Second Nordic Seminar on Computational Mechanics,; (2009)p. 197-200

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Hållbar utveckling

Innovation och entreprenörskap


Teknisk mekanik

Tillförlitlighets- och kvalitetsteknik

Annan materialteknik






Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie

sal EA, Hörsalsvägen 11, Chalmers

Opponent: Aki M. Mikkola