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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Taher, A.A. Pekarek, S.D. |
| Copyright Year | 2013 |
| Description | Author affiliation: Purdue Univ., West Lafayette, IN, USA (Taher, A.A.; Pekarek, S.D.) |
| Abstract | In the research presented herein, population-based design of mechanically-commutated DC machines is considered. To set the stage for design, a model of the machine is derived to predict the electromagnetic torque, commutation interval, conduction loss, and core loss based upon material property, geometry, and excitation. A key component of the model is an analytical expression for the flux density within the machine from which the armature winding inductance and voltage constant are obtained. Using the model, multi-objective optimization is performed to establish Pareto-optimal front between mass and power loss for a host of design constraints. Finally, a design from the Pareto-optimal front is validated using Finite Element Analysis (FEA). |
| Sponsorship | IEEE Ind. Electron. Soc. |
| Starting Page | 1397 |
| Ending Page | 1404 |
| File Size | 1827860 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781467349758 |
| e-ISBN | 9781467349741 |
| e-ISBN | 9781467349734 |
| DOI | 10.1109/IEMDC.2013.6556320 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-05-12 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Analytical models Predictive models optimization DC machines GA FEA machine design machine model fitness function |
| Content Type | Text |
| Resource Type | Article |
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