Nasir Abdulai Boakye-Boateng

Variable reluctance motor airgap geometry for maximizing force production: a data analysis approach using finite element generated characteristics

A Dissertation Presented for the Doctor of Philosophy in Computational Engineering, The University of Tennessee at Chattanooga

Nasir Abdulai Boakye-Boateng, May 2020

Abstract:

Recent widespread utilization of variable reluctance (VR) motors and growing computational capability motivate further research to improve VR motor modeling and control. The primary objective of this study is to identify airgap geometries that maximize force density and minimize force ripple for linear variable reluctance (LVR) motors with both magnetically coupled and uncoupled phases. Complementary objectives include expanding the scope for candidate geometries to include a finer variation of tooth width and non-rectangular tooth shapes and using a comprehensive data analysis framework based on a nonlinear model for LVR motors formed from finite element analysis (FEA) generated characteristics.

The main contribution of this study is the identification of the LVR motor geometry that meets the specified objectives. Further to the existing literature, it establishes the non-monotonous nature of the effect of tooth width on force density and force-ripple; force-ripple reduction is a primary concern of most LVR drive design. The study specifies a narrower range of tooth widths for both high thrust and low force ripple applications. The study introduces tooth fillet parameters; specific values of these further increase LVR output thrust, and the data shows which range of tooth fillets maximize thrust.

Three salient applications of this study are as follows. (i) The detailed FEA-based characterization of the large family of motors has highlighted the effect of airgap geometry and motor characteristics and the set of tooth geometry parameters that impact attributes such as force density. (ii) The data generated from characterization forms a nonlinear model of the motor that compares well with FEA-based results and is applicable as a predictive plant model in LVR drive design. (iii) The optimal commutation of the family of LVR motors confirms the effect of tooth geometry on attributes such as root mean square (RMS) force density.

The findings regarding the uncoupled configuration of the motor apply to the rotary VR motor and have a more extensive application. The document has suggestions for further study regarding areas of additional refinement for the optimal LVR motor geometry, tools to aid future research, and improvement of the LVR motor's nonlinear model.

Click here to access a copy of Nasir's dissertation.