NOVEL MODELING, TESTING AND CONTROL APPROACHES TOWARDS ENERGY EFFICIENCY IMPROVEMENT IN PERMANENT MAGNET SYNCHRONOUS MOTOR AND DRIVE SYSTEMS

This thesis investigates energy efficiency improvement in permanent magnet synchronous motor (PMSM) and drive system to achieve high–performance drive for practical industrial and primarily, traction applications. In achieving improved energy efficiency from a system level, this thesis proposes: (1) Accurate modeling and testing of loss components in PMSM considering inverter harmonics; (2) Easy–to–implement, accurate parameter determination techniques to understand variations in motor parameters due to saturation, cross–saturation and temperature; and (3) Control methodologies to improve system level efficiency considering improved loss models and parameter variations. An improved loss model to incorporate the influence of motor–drive interaction on the motor losses is developed by taking time and space harmonics into account. An improved winding function theory incorporating armature reaction fields due to fundamental and harmonic stator magnetic fields is proposed to calculate the additional harmonic losses in the PMSM. Once all contributing losses in the motor are modelled accurately, an investigation into control variables that affect the losses in the motor and inverter is performed. Three major control variables such as DC link voltage, switching frequency and current angle are chosen and the individual losses in the motor and inverter as well as the system losses are studied under varying control variables and wide operating conditions. Since the proposed loss as well as efficiency modeling involves machine operation dependent parameters, the effects of parameter variation on PMSM due to saturation and temperature variation are investigated. A recursive least square (RLS) based multi–parameter estimation is proposed to identify all the varying parameters of the PMSM to improve the accuracy and validity of the proposed model. The impact of losses on these parameters as well as the correct output torque considering the losses are studied. Based on the proposed loss models, parameter variations and the investigation into control variables, an off–line loss minimization procedure is developed to take into account the effects of parameter variations. The search–based procedure generates optimal current angles at varying operating conditions by considering maximization of system efficiency as the objective. In order to further simplify the consideration of parameter variations in real–time conditions, an on–line loss minimization procedure using DC power measurement and loss models solved on–line using terminal measurements in a PMSM drive is proposed. A gradient descent search–based algorithm is used to calculate the optimal current angle corresponding to maximum system efficiency from the input DC power measurement and output power based on the loss models. During the thesis investigations, the proposed models and control techniques are extensively evaluated on a laboratory PMSM drive system under different speeds, load conditions, and temperatures

An Approach for Estimating the Reliability of IGBT Power Modules in Electrified Vehicle Traction Inverters

The reliability analysis of traction inverters is of great interest due to the use of new semi-conductor devices and inverter topologies in electric vehicles (EVs). Switching devices in the inverter are the most vulnerable component due to the electrical, thermal and mechanical stresses based on various driving conditions. Accurate stress analysis of power module is imperative for development of compact high-performance inverter designs with enhanced reliability. Therefore, this paper presents an inverter reliability estimation approach using an enhanced power loss model developed considering dynamic and transient influence of power semi-conductors. The temperature variation tracking has been improved by incorporating power module component parameters in an LPTN model of the inverter. A 100 kW EV grade traction inverter is used to validate the developed mathematical models towards estimating the inverter performance and subsequently, predicting the remaining useful lifetime of the inverter against two commonly used drive cycles