PhD Oral Exam - Yupeng Liu, Electrical and Computer Engineering
Induction Machine Emulation for Asymmetrical Conditions
This event is free
School of Graduate Studies
When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.
Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.
The induction machine can be used as generator or motor, to convert mechanical power to electrical power or via versa. The induction generator is an essential element of many renewable energy systems such as wind power plants, etc. The induction motor is commonly adopted in industry. The advantages of induction machines are well-known compared to other types of machines. Thus, it is important to investigate induction machines with accurate models and replace expensive test benches and equipment by more efficient and economical test procedures.
To describe induction machines, different mathematical models have been devoted over the years to examine different problems. For instance, the abc frame model, dq frame model, hybrid model of abc and dq, and multiple coupled circuit (MCC) models. Based on those models, the developed model-based induction machine emulator is able to offer a flexible and easy platform for testing and analyzing characteristics of the induction machine in the laboratory environment. Therefore, accurate mathematical models are essential for further applications of induction machines.
Generally, the induction machine works under balanced conditions, but the unbalanced condition is inevitable in practice. Self-excited induction generator (SEIG) is a good option for standalone wind energy conversion systems and other renewable energy sources. In such SEIG systems, the majority of unbalanced cases occur due to load disconnection. On the other hand, the generator will have to supply nonlinear loads in most scenarios. Thus, the SEIG supplying three-phase unbalanced loads and nonlinear loads is relatively common.
Inside the induction machine, due to the combination of working environment, installation, and manufacturing factors, unbalance caused by internal faults can occur. Stator windings, rotor bars, and end rings are the most common internal faults. Such faults not only reduce the machine working efficiency and cause excessive heating but also cause potential hazards for continuous work and safety. As a result, it can lead to the failure of the machine.
Continuing to drive the induction machine with asymmetrical conditions can cause consequent failures and even permanent damage to the machine. This thesis proposes a power electronic converter-based machine emulator replacing the actual machine to investigate the performance of the machine under different kinds of asymmetrical conditions. The machine emulator provides a laboratory environment to test and analyze the characteristics of the actual machine, especially under critical operating conditions. Therefore, the risk, time and cost associated with generating real faults can be reduced, helping to overcome safety issues with actual faulted machines. Such techniques can also be applied in fault detection, diagnosis, and fault control areas. In this thesis, the emulation of a SEIG supplying unbalanced and nonlinear loads, an induction motor with stator winding faults and rotor cage faults conditions are researched.
The mathematical model of the SEIG system is established and the emulation results of balanced loads, unbalanced loads, transients during loading and nonlinear load conditions are compared with an actual SEIG system. The mathematical model of an induction machine with stator winding faults is also built. The emulator setup for a faulted induction motor is proposed and established, the experimental results of an actual machine with 5% and 10% faults have been done and then compared with simulation and emulation results. Different loading conditions are investigated. For the rotor cage fault induction motor, a novel machine parameter measurement method is introduced, which is able to measure the machine parameters without opening the machine, making it easier and more convenient to acquire rotor parameters. Usually, the faults inside the machine are hard to distinguish. In this thesis, the rotor cage fault is identified by analyzing the stator current frequency components, then the emulation setup is established. The simulation and emulation are compared with an actual faulted induction motor including loading conditions, which demonstrates the validity of the machine emulator.