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An Improved Sampling Algorithm for Stochastic Modelling of Random-Wound Electrical Machines
1. The 9th International Conference on Power Electronics, Machines and Drives
17 - 19 April 2018
Liverpool ACC, Liverpool, UK
An Improved Sampling Algorithm for Stochastic Modelling of
Random-Wound Electrical Machines
Antti Lehikoinen1, Nicola Chiodetto2, Antero Arkkio1, Anouar Belahcen1
1Dept. of Electrical Engineering and Automation, Aalto University, Espoo, Finland
2School of Electrical and Electronic Engineering, Newcastle University, Newcastle upon Tyne, England
Email: antti.lehikoinen@aalto.fi / antti@smeklab.com
Problem background
• Stranded winding = parallel
subconductors
• Circulating currents = total phase
current unevenly divided between
parallel strands Significant loss
increase
• Random loss variation
Methods
• Random positioning of
strands in slots
Monte Carlo sampling
• Two important constraints:
1. Correlated positions between
successive slots.
2. Strands tend to stay in
spontaneous bundles.
Ignoring either underestimates
the variance of losses
Results
• Winding losses of 230 high-speed IMs
measured Comparison to simulated results
Example of spontaneously-occurring bundles of
strands in the end-winding region.
