By Topic

Reliability Prediction for Inverters in Hybrid Electrical Vehicles

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)

Due to the increasing importance of power electronic components in automobiles, it becomes necessary to consider their reliability. This applies especially to hybrid electrical vehicles (HEV) where a malfunction of the power electronics may prevent the vehicle to operate. Of paramount importance for the reliability of power electronics is the component operating temperature and temperature cycling. This paper deals with the development of an advanced simulation tool which is capable of determining the component temperature of a three-phase converter over long mission profiles. In addition, the expected converter reliability is calculated. To accomplish this, losses in the semiconductors and dc-link capacitors are determined first. Next, this loss data is fed into a thermal model to compute the component temperatures, for the whole mission profile. As basis for the reliability computation, failure-rate catalogs, such as Military Handbook 217F or RDF 2000, are used. Also an approach using simple formulas for lifetime prediction is presented. According to failure-rate catalogs, temperature cycles are of particular importance for the reliability of power semiconductors. A novel algorithm, detecting all relevant temperature cycles within the computed temperature curve is developed. Finally, the applicability and significance of the presented reliability prediction methods is assessed.

Published in:

Power Electronics, IEEE Transactions on  (Volume:22 ,  Issue: 6 )