Design and performance improvement of AC machines sharing a common stator
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Authors
Guo, Lusu
Issue Date
2016-05
Type
Electronic thesis
Thesis
Thesis
Language
ENG
Keywords
Electrical engineering
Alternative Title
Abstract
Sometimes, torque pulsation is the major drawback of permanent magnet synchronous machines. There are several sources of torque pulsations, such as back-EMF distortion, inductance variation and cogging torque due to presence of permanent magnets. To reduce torque pulsations in permanent magnet machines, all the efforts can be classified into two categories: one is from the design stage, the structure of permanent magnet machines can be optimized with the aid of finite element analysis. The other category of reducing torque pulsation is after the permanent magnet machine has been manufactured or the machine structure cannot be changed because of other reasons. The currents fed into the permanent magnet machine can be controlled to follow a certain profile which will make the machine generate a smoother torque waveform. Torque pulsation reduction methods in both categories will be discussed in this dissertation. In the design stage, an optimization method based on orthogonal experimental design will be introduced. Besides, a universal current profiling technique is proposed to minimize the torque pulsation along with the stator copper losses in modular interior permanent magnet motors. Instead of sinusoidal current waveforms, this algorithm will calculate the proper currents which can minimize the torque pulsation. Finite element analysis and Matlab programing will be used to develop this optimal current profiling algorithm.
With the increasing demand on electric motors in various industrial applications, especially electric powered vehicles (electric cars, more electric aircrafts and future electric ships and submarines), both synchronous reluctance machines (SynRMs) and interior permanent magnet (IPM) machines are recognized as good candidates for high performance variable speed applications. Developing a single stator design which can be used for both SynRM and IPM motors is a good way to reduce manufacturing and maintenance cost. SynRM can be used as a low cost solution for many electric driving applications and IPM machines can be used in power density crucial circumstances or work as generators to meet the increasing demand for electrical power on board. In this research, SynRM and IPM machines are designed sharing a common stator structure. The prototype motors are designed with the aid of finite element analysis (FEA). Machine performances with different stator slot and rotor pole numbers are compared by FEA. An 18-slot, 4-pole structure is selected based on the comparison for this prototype design.
Permanent magnet machines are becoming more attractive in some modern traction applications, such as traction motors and generators for an electrified vehicle. The operating speed or the load condition in these applications may be changing all the time. Compared to electric machines used to operate at a constant speed and constant load, better control performance is required. In this dissertation, a novel model reference adaptive control (MRAC) used on five-phase interior permanent magnet motor drives is presented. The primary controller is designed based on artificial neural network (ANN) to simulate the nonlinear characteristics of the system without knowledge of accurate motor model or parameters. The proposed motor drive decouples the torque and flux components of five-phase IPM motors by applying a multiple reference frame transformation. Therefore, the motor can be easily driven below the rated speed with the maximum torque per ampere (MTPA) operation or above the rated speed with the flux weakening operation. The ANN based primary controller consists of a radial basis function (RBF) network which is trained on-line to adapt system uncertainties. The complete IPM motor drive is simulated in Matlab/Simulink environment and implemented experimentally utilizing dSPACE DS1104 DSP board on a five-phase prototype IPM motor. The proposed model reference adaptive control method has been applied on the commons stator SynRM and IPM machine as well.
With the increasing demand on electric motors in various industrial applications, especially electric powered vehicles (electric cars, more electric aircrafts and future electric ships and submarines), both synchronous reluctance machines (SynRMs) and interior permanent magnet (IPM) machines are recognized as good candidates for high performance variable speed applications. Developing a single stator design which can be used for both SynRM and IPM motors is a good way to reduce manufacturing and maintenance cost. SynRM can be used as a low cost solution for many electric driving applications and IPM machines can be used in power density crucial circumstances or work as generators to meet the increasing demand for electrical power on board. In this research, SynRM and IPM machines are designed sharing a common stator structure. The prototype motors are designed with the aid of finite element analysis (FEA). Machine performances with different stator slot and rotor pole numbers are compared by FEA. An 18-slot, 4-pole structure is selected based on the comparison for this prototype design.
Permanent magnet machines are becoming more attractive in some modern traction applications, such as traction motors and generators for an electrified vehicle. The operating speed or the load condition in these applications may be changing all the time. Compared to electric machines used to operate at a constant speed and constant load, better control performance is required. In this dissertation, a novel model reference adaptive control (MRAC) used on five-phase interior permanent magnet motor drives is presented. The primary controller is designed based on artificial neural network (ANN) to simulate the nonlinear characteristics of the system without knowledge of accurate motor model or parameters. The proposed motor drive decouples the torque and flux components of five-phase IPM motors by applying a multiple reference frame transformation. Therefore, the motor can be easily driven below the rated speed with the maximum torque per ampere (MTPA) operation or above the rated speed with the flux weakening operation. The ANN based primary controller consists of a radial basis function (RBF) network which is trained on-line to adapt system uncertainties. The complete IPM motor drive is simulated in Matlab/Simulink environment and implemented experimentally utilizing dSPACE DS1104 DSP board on a five-phase prototype IPM motor. The proposed model reference adaptive control method has been applied on the commons stator SynRM and IPM machine as well.
Description
May 2016
School of Engineering
School of Engineering
Full Citation
Publisher
Rensselaer Polytechnic Institute, Troy, NY