Alexanders project 'Nonlinear fractional order derivative models of components and materials in hearing aids and transducers' involved how design of electroacoustic systems relies on accurate models of the components used. The response at low levels can be represented in the linear domain using lumped parameter models, where it is straightforward to include viscoelastic effects of materials, and lossy inductances. However, linear system analysis is rarely sufficient in finding the optimal solution. Therefore, understanding the nonlinear behavior of components and systems is required.
Currently, there is a gap between the advanced linear lumped parameter models, and the nonlinear models, which rely on simpler descriptions of materials and components. The project aimed to develop robust and efficient nonlinear models that are able to predict the frequency dependent behavior of materials and components. This was done using fractional order derivative models, which have shown promising results in the linear domain.
The models developed are expected to give a significant increase in modelling capability and accuracy, while improving system performance in terms of size, efficiency and cost.
The examiners agreed that the submitted thesis presents original work in the field of nonlinear modelling of material properties in electroacoustical transducers, combing several complex disciplines from normally unrelated fields of research. The scope of the research is clearly defined and coherent and the topic highly relevant for the description of nonlinear effects and development of transducers.
Alexanders competent responses in all of the relevant and connected areas, displayed a clear understanding of the multiple underlying concepts, demonstrating a solid grasp of the theoretical elements described in the thesis, including its limitation. Overall, Alex convincingly demonstrated his mastering of the scientific topic and led the discussion with the examiners on a highly professional level.
Congratulations to Alex on his achievement.
Alexander Weider King with Supervisors Associate Professors Jonas Brunskog & Finn T. Agerkvist