2 resultados para Shape Design Optimization

em Memorial University Research Repository


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The direct drive point absorber is a robust and efficient system for wave energy harvesting, where the linear generator represents the most complex part of the system. Therefore, its design and optimization are crucial tasks. The tubular shape of a linear generator’s magnetic circuit offers better permanent magnet flux encapsulation and reduction in radial forces on the translator due to its symmetry. A double stator topology can improve the power density of the linear tubular machine. Common designs employ a set of aligned stators on each side of a translator with radially magnetized permanent magnets. Such designs require doubling the amount of permanent magnet material and lead to an increase in the cogging force. The design presented in this thesis utilizes a translator with buried axially magnetized magnets and axially shifted positioning of the two stators such that no additional magnetic material, compared to single side machine, is required. In addition to the conservation of magnetic material, a significant improvement in the cogging force occurs in the two phase topology, while the double sided three phase system produces more power at the cost of a small increase in the cogging force. The analytical and the FEM models of the generator are described and their results compared to the experimental results. In general, the experimental results compare favourably with theoretical predictions. However, the experimentally observed permanent magnet flux leakage in the double sided machine is larger than predicted theoretically, which can be justified by the limitations in the prototype fabrication and resulting deviations from the theoretical analysis.

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The main focus of this research is to design and develop a high performance linear actuator based on a four bar mechanism. The present work includes the detailed analysis (kinematics and dynamics), design, implementation and experimental validation of the newly designed actuator. High performance is characterized by the acceleration of the actuator end effector. The principle of the newly designed actuator is to network the four bar rhombus configuration (where some bars are extended to form an X shape) to attain high acceleration. Firstly, a detailed kinematic analysis of the actuator is presented and kinematic performance is evaluated through MATLAB simulations. A dynamic equation of the actuator is achieved by using the Lagrangian dynamic formulation. A SIMULINK control model of the actuator is developed using the dynamic equation. In addition, Bond Graph methodology is presented for the dynamic simulation. The Bond Graph model comprises individual component modeling of the actuator along with control. Required torque was simulated using the Bond Graph model. Results indicate that, high acceleration (around 20g) can be achieved with modest (3 N-m or less) torque input. A practical prototype of the actuator is designed using SOLIDWORKS and then produced to verify the proof of concept. The design goal was to achieve the peak acceleration of more than 10g at the middle point of the travel length, when the end effector travels the stroke length (around 1 m). The actuator is primarily designed to operate in standalone condition and later to use it in the 3RPR parallel robot. A DC motor is used to operate the actuator. A quadrature encoder is attached with the DC motor to control the end effector. The associated control scheme of the actuator is analyzed and integrated with the physical prototype. From standalone experimentation of the actuator, around 17g acceleration was achieved by the end effector (stroke length was 0.2m to 0.78m). Results indicate that the developed dynamic model results are in good agreement. Finally, a Design of Experiment (DOE) based statistical approach is also introduced to identify the parametric combination that yields the greatest performance. Data are collected by using the Bond Graph model. This approach is helpful in designing the actuator without much complexity.