Equivalent Circuit Parameters for Large Brushless Doubly Fed Machines (BDFM)

This paper presents analytical methods to calculate the equivalent circuit parameters for large-scale brushless doubly fed machines (BDFMs) with magnetic wedges utilized for closing stator open slots. The use of magnetic wedges reduces the magnetizing currents in the machine, reflected in the values of magnetizing inductances, but also increases leakage fluxes affecting the value of series inductances in the equivalent circuit. Though such effects can be modeled by numerical models, the proposed analytical methods are particularly helpful in optimizing machine design, inverter rating, reactive power management, and grid low-voltage ride-through performance. The conventional analytical methods cannot be readily applied to the BDFM due to its complex magnetic field distribution; this paper presents analytical methods to calculate the magnetizing and leakage inductances for the BDFM with magnetic wedges used in the stator slots. The proposed methods are assessed by experimentally verified finite-element models for a 250 kW BDFM

DFIG machine design for maximizing power output based on surrogate optimization algorithm

This paper presents a surrogate-model-based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine's previous operational performance, the DFIG's stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization-based surrogate optimization techniques are used in conjunction with the finite element method to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies

Fault detection of electric vehicle motor based on flux performance using FEM

This paper presents the early faults detection in electric vehicle motor based on flux performance examination in defective electrical machine using finite element methods (FEM). Depend on time step, the proposed technique has been designed and examine to produce efficient method under high accuracy and short time to detect the faults in Electric Vehicle motors. To decrease the probability and time of electric motor faults, the early detection of these faults will give enough time to prevent many problems during the motion. The different waveforms timing of motor torque in every situation associated with the waveforms of stator current provide spreading in the proposed method. The results show fast fault detections and a Novel technology was established to extort the fault of induction motor

Holistic Physics-of-Failure Approach to Wind Turbine Power Converter Reliability

As the cost of wind energy becomes of increasing importance to the global surge of clean and green energy sources, the reliability-critical power converter is a target for vast improvements in availability through dedicated research. To this end, this thesis concentrates on providing a new holistic approach to converter reliability research to facilitate reliability increasing, cost reducing innovations unique to the wind industry. This holistic approach combines both computational and physical experimentation to provide a test bench for detailed reliability analysis of the converter power modules under the unique operating conditions of the wind turbine. The computational models include a detailed permanent magnet synchronous generator wind turbine with a power loss and thermal model representing the machine side converter power module response to varying wind turbine conditions. The supporting experimental test rig consists of an inexpensive, precise and extremely fast temperature measurement approach using a PbSe photoconductive infra-red sensor unique in the wind turbine reliability literature. This is used to measure spot temperatures on a modified power module to determine the junction temperature swings experienced during current cycling. A number of key conclusions have been made from this holistic approach. -Physics-of-failure analysis (and indeed any wind turbine power converter based reliability analysis) requires realistic wind speed data as the temporal changes in wind speed have a significant impact on the thermal loading on the devices. -The use of drive train modelling showed that the current throughput of the power converter is decoupled from the incoming wind speed due to drive train dynamics and control. Therefore, the power converter loading cannot be directly derived from the wind speed input without this modelling. -The minimum wind speed data frequency required for sufficiently accurate temperature profiles was determined, and the use of SCADA data for physics-of failure reliability studies was subsequently shown to be entirely inadequate. -The experimental emulation of the power converter validated a number of the aspects of the simulation work including the increase in temperature with wind speed and the detectability of temperature variations due to the current's fundamental frequency. Most importantly, this holistic approach provides an ideal test bench for optimising power converter designs for wind turbine, or for other industries with stochastic loading, conditions whilst maintaining or exceeding present reliability levels to reduce wind turbine's cost of energy, and therefore, society

Impact of wind conditions on thermal loading of PMSG wind turbine power converters

Power converter reliability is critical for permanent magnet synchronous generator (PMSG) wind turbines. Converter failures are linked to power module thermal loading but studies often neglect turbine dynamics, control and the impact of wind speed sampling rate on lifetime estimation. This paper addresses this using a 2MW direct-drive PMSG wind turbine model with a 2-level converter, and simulating junction temperatures (Tj) using a power module thermal equivalent circuit under various synthetic wind speed conditions. These synthetic wind conditions include constant and square wave profiles representing stable and gusty wind conditions. Responses to square wave wind speeds showed that the lower the gust frequency, the higher ∆Tj becomes, demonstrating that low turbulence sites have greater thermal variation in the converter. In contrast, wind speed variations with frequencies greater than 0.25Hz deliver only small increases in ∆Tj . It is concluded that reasonable approximations of Tj profiles can be made with 0.25Hz wind speed data, but that lower data rate wind measurements miss essential, damaging characteristics