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Type: Thesis
Title: Integrated Motor System Estimation Using Efficiency Maps
Author: Haines, Gabriel Graham
Issue Date: 2020
School/Discipline: School of Electrical and Electronic Engineering
Abstract: A motor combined with an inverter based variable speed drive and an end load device forms a motor system that can operate over a wide area of different speed and load combinations. The majority of the motor systems used in the world are low power systems that have poor motor and system efficiency, resulting in higher energy consumption. Because of cost considerations, such systems rarely include the sensors required for more efficient feedback control schemes. In cases where physical sensors are used, those motor systems experience higher cost and reduced reliability. Using models of the motor and/or load, it is possible for a variable speed drive to estimate some motor system quantities. Position sensorless control is the most common form of sensorless operation, but it is also possible to estimate motor torque, pump pressure and pump flow. Sensorless estimates can replace physical sensors, increasing reliability and reducing both the size and cost of the motor system. For efficient and effective sensorless motor operation, accurate knowledge of a motor system’s operation over a wide area must be understood in terms of the real time system state and the efficiency of the system components. This research considers sensorless state estimation of a low-cost motor system integrated with an end application/load. A focus is given to expanding the operating area of sensorless techniques, and to better understand a motor system’s performance over a wide operating area. Motor systems using permanent magnet (PM) machines were studied because of their high efficiency, high power density, and ability to operate using a range of position sensorless control schemes. An improved method of position sensorless control for brushless DC motors was developed, enabling wider speed operation compared to methods of similar complexity. The method was implemented on a low-cost motor drive, and the performance was verified experimentally. To better understand the performance of an integrated motor system over a large operating area, a method of autonomous testing was developed. The flexible hardware and software-based test system was adaptable to different motor system applications and collected large volumes of temperature-controlled efficiency data, allowing for a motor system to be characterised in greater detail over its operating area. Using large sets of experimental data, a new method for general motor state sensorless estimation was developed. Estimator models were developed for speed, torque, DC power, AC power, mechanical power, inverter efficiency, motor efficiency and system efficiency. The estimators were implemented in the firmware of a low-cost inverter, and the performance over the operating area of the motor system was experimentally verified. The method of sensorless state estimation was then extended to a pump system, demonstrating the method’s ability to model the nonlinear relationship between motor and pump quantities. Estimator models were developed for pump head pressure, flow, hydraulic power, efficiency and total volume pumped. Estimator performance over the system’s operating area was experimentally verified, with temperature changes and dynamic performance also being considered. The methods discussed are not limited to pump systems, but are applicable to fans, compressors, vehicles and other motor systems with multiple components, sensors, and room for efficiency improvements.
Advisor: Ertugrul, Nesimi
Soong, Wen L.
Dissertation Note: Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 2020
Keywords: Permanent-magnet (PM) machines
efficiency maps
variable speed drives
motor testing
Provenance: This electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exceptions. If you are the owner of any included third party copyright material you wish to be removed from this electronic version, please complete the take down form located at:
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