Research Projects
1. Design and Control of Linear Permanent Magnet Machine
Applications for energy generation, energy conversion, or actuation can benefit from the use of linear machines. To further investigate the possibilities and challenges with linear machine technology, a linear permanent magnet machine was designed and manufactured in the EMDL. An experimental setup including a linear dynamometer and cooling system was assembled to characterize the designed machine so the capabilities of this machine topology can be validated. The results from this project can help build the knowledge of the design of linear permanent magnet machines and this knowledge can be extended to apply this linear machine topology to a variety of applications.
2. Operation of Interior Permanent Magnet Synchronous Machines with Fractional Slot Concentrated Windings Under Both Healthy and Faulty Conditions
This project evaluates the performance and reliability of fault tolerant fractional slot concentrated winding machine designs experiencing stator winding insulation failure. Additionally, this project explores methods for improving machine reliability through online detection of incipient stator winding faults. This project also explores control methods for improving the torque performance of permanent magnet synchronous machines with single-layer fractional slot concentrated windings.
3. Turn-to-turn fault mitigation for permanent magnet synchronous motors (PMSM)
The objective of the project is to reduce the thermal stress in the faulted winding to decelerate the fault-propagation and extend the post-fault life span of the machine. Having a mitigation technique is vital in applications where human interaction is required; such as, hybrid electric vehicles and aerospace application. To protect lives it’s essential to develop safety protocols for all types of faults, in order to guarantee a safe fault operation.
4. Condition Monitoring and Failure Prognosis of Permanent Magnet Machine Stator Insulation Faults
The effectiveness of electric machine stator winding insulation lessens with age, leading to short circuits and catastrophic failure. By monitoring the insulation condition with terminal voltages and currents, the extent of the insulation damage can be known before a low resistance short occurs. Determining the degree of degradation is useful for avoiding: risks to life, extensive equipment damage, lengthy repair times due to extensive damage, and costs caused by a catastrophic failure. With fault prognosis, the remaining useful life can be estimated with information about the insulation condition and knowledge of how the insulation deteriorates. Being able to determine the winding condition and predict failure can result in timely repair, such as rewinding the machine before a catastrophic short. Condition monitoring and failure prognosis schemes are developed and verified with simulations and experiments using an interior
5. Fault Detection and classification in permanent Magnet Synchronous Machines
Work on detection of faults in permanent magnet synchronous machines (PMSM), using signal-processing techniques like Fast Fourier Transform and Linear Discriminant Analysis (LDA) to classify the severity and detect the type of the fault. Two main faults are under tests; static eccentricity and stator short circuit faults. Both finite element analysis (FEA) and experimental data are used to validate the detection method. Two machines are under tests; the first machine has a concentrated winding stator while the second machine has a distribution winding stator.
6. Detection of Stator Winding Short Faults in IPM Machines at Standstill
The project objective is to detect winding short faults in the Interior Permanent Magnet (IPM) at standstill. This could provide early detection and improve reliability of electric propulsion systems. The method uses the dq frame of reference to keep the motor at zero speed while injecting currents to the motor. The three phase currents are measured and compared using Fast Fourier Transform (FFT) frequency analysis. A Finite Elements model of the machine was used to simulate different faults and experimental tests were conducted for two different types, turn short fault and phase-to-phase short fault. The results show that the extracted signature between healthy and faulted machines is significant and easy to be detected.
7. Fault prognosis and RUL Estimation of Bearings
Condition based maintenance, which includes both diagnosis and prognosis of faults, is a topic of growing interest for increasing the reliability of complex systems. Although many signal processing and machine learning techniques have been successfully applied to fault diagnosis, prognosis of faults and predicting the remaining useful life (RUL) of the components is a remaining challenge. One reason for this challenge is the lack of accurate physical models and labeled training data. However prognosis, if performed accurately, on rotary machinery will improve system reliability and decrease maintenance costs. The objective of this work is to perform prognosis and obtain accurate RUL estimations of bearings in situ, since bearings constitute a large portion of the failure causes in rotary machines.
8. Direct torque control (DTC) strategies for Permanent magnet synchronous machines (PMSMs)
Direct torque control (DTC) is a powerful and widely adopted control strategy. During the past few years, many improved DTC control methods have been presented to tackle the problems of basic DTC, such as model predictive DTC (MPDTC), DTC with duty ratio modulation (DDTC) etc. The objective of this project is to conduct a comprehensive comparison between different DTC control strategies through simulations and experiments. Furthermore, make improvements of different control strategies, especially MPDTC and DDTC, to obtain better control performance. The whole control system is implemented based on a two-level VSI fed 1 kW PMSM. A NI real-time model is employed to implement the control strategies using C language produced by Matlab/Simulink real-time workshop. A three-phase IGBT module equipped with insulated firing circuits is used for the invertor. The PWM signals are generated by FPGA embedded in the real-time model and then sent to the invertor through NI PCIE-7852R RIO board which is also used to finish the sampling of system variables. The load is applied using a DC machine fed by a single-phase controller.
