Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.572934
Title: Lifetime prediction for power converters
Author: Huang, Hui
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2012
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Abstract:
Renewable energy is developing rapidly and gaining more and more commercial viability. High reliability of the generation system is essential to maximize the output power. The power inverter is an important unit in this system and is believed to be one of the most unreliable parts. In the case of wind power generation, especially in off-shore wind, when the system reliability requirement is high, a technique to predict the inverter lifetime is invaluable as it would help the inverter designer optimize his design for minimal maintenance. Previous researchers studying inverter lifetime prediction, focus either at device level such as device fatigue damage models, or at system level which require experimental data for their selected device. This work presents a new method to estimate the inverter lifetime from a given mission profile within a reasonable simulation time. Such model can be used as a converter design tool or an on-line lifetime estimation tool after being configured to a real converter system. The key contribution of this work is to link the physics of the power devices to a large scale system simulation within a reasonable framework of time. With this technique, the system down time can be reduced and therefore more power can be generated. Also, the failure damage to the system is avoided which reduces the maintenance cost. A power cycling test is designed to gather the lifetime data of a selected IGBT module. Die-attach solder fatigue is found out to be the dominant failure mode of this IGBT module. The accuracy of widely accepted Miner’s rule, which accumulates damage linearly, is discussed and a nonlinear accumulation method is promoted to predict the lifetime of power inverters.
Supervisor: Not available Sponsor: Engineering and Physical Sciences Research Council (EPSRC)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.572934  DOI: Not available
Keywords: TK Electrical engineering. Electronics Nuclear engineering
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