Date of Award

9-20-2019

Publication Type

Doctoral Thesis

Degree Name

Ph.D.

Department

Electrical and Computer Engineering

First Advisor

Kar, N.C.

Rights

info:eu-repo/semantics/embargoedAccess

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Abstract

In commercially existing electric vehicles (EVs), power is transferred from the motor to the wheels through a fixed gear mechanical transmission system. However, such a transmission system contributes to a power loss between 2% to 20% of output power of the motor depending on the operating speed and torque of the motor. Therefore, by removing the transmission, a direct–drive EV configuration is obtained with lower component count, improved motor to wheel efficiency and frequency dependent losses. However, challenges in developing a single on–board permanent magnet synchronous machine (PMSM) for such a configuration include high torque density, low torque ripple and high torque per permanent magnet (PM) volume. Therefore, this dissertation proposes a novel PMSM addressing the aforementioned challenges for a direct–drive application. Initially, the design targets, stator and rotor configuration and phase numbers of the PMSM are chosen to satisfy the requirements of a direct drive application. A novel torque and torque ripple model based on multiple reference frames is proposed, in which the torque ripple from spatial harmonics of flux, inductances and the time harmonics of stator currents are included. Using the analytical model, optimal slot–pole combination of the machine is selected based on adaptive gradient descent algorithm. A new consequent pole rotor topology is proposed to improve the torque density and torque per PM volume thereby reducing the usage of expensive rare earth magnets. The proposed PMSM with novel rotor is further improved in terms of torque density, losses and cost by performing an intensive structural optimization based on novel hybrid analytical model, finite element analysis and supervised learning. The optimized PMSM is then analyzed for various drive cycles and performance in terms of torque, speed and efficiency are discussed. A scaled–down prototype of the proposed PMSM is developed and comprehensive experimental analysis in terms of torque ripple, torque–speed characteristics and efficiency are performed under different speeds and load conditions and are compared with the results obtained from proposed analytical model.

Available for download on Thursday, November 12, 2020

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