Abstract
One of the primary design requirements of automotive generation systems is maximizing power density subject to the constraint of minimizing the overall system cost. However, with the progress made in the reduction of automotive drive train noise, the torque ripple of the generator has been found to be a dominant noise source under idle conditions at high electrical loads. Thus, an added design constraint is the minimization of the torque ripple produced by the machine. in order to evaluate alternative machine designs (and select an optimal), numerical tools are typically applied. in this research, a focus is placed on the creation of numerical tools that can be used to effectively search for an optimal design. a primary tool is an evolutionary algorithm (EA) that has been integrated within a customized magnetic equivalent circuit (MEC) model of the machine. the selection of an EA that is most likely to converge to an optimal solution in the least amount of time is described along with its use in selecting an optimal rotor-pole geometry. © 2006 IEEE.
Recommended Citation
A. C. Koenig et al., "Evaluation of Alternative Evolutionary Programming Techniques for Optimization of an Automotive Alternator," IEEE Transactions on Vehicular Technology, vol. 55, no. 3, pp. 933 - 942, Institute of Electrical and Electronics Engineers, May 2006.
The definitive version is available at https://doi.org/10.1109/TVT.2005.863430
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Alternator; Evolutionary algorithm (EA); Generator; Magnetic circuits; Optimization
International Standard Serial Number (ISSN)
0018-9545
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 May 2006
Comments
National Science Foundation, Grant 01202531