Normalized Analytical, FEA, and Measured Performance Dataset for Automotive Traction Machines with Star, Delta, and Parallel Winding Configurations

Zenodo (CERN European Organization for Nuclear Research)

Abstract

This dataset contains normalized analytical, FEA, and measured performance data for six baseline automotive traction machines evaluated under star ($\Upsilon$), delta ($\Delta$), and parallel ($\Pi$) winding configurations. The data supports reproducible assessment of active winding reconfiguration benefits in permanent-magnet synchronous machines using the normalized characteristic-current framework established in the work: R. Kallur-Krishnamoorthy, H. Wang, H. Currimbhoy, M. Eisenbarth, and J. Andert, Normalized-Characteristic-Current-Based Methodology for Quantifying Active Winding Reconfiguration Benefits in Permanent Magnet Synchronous Machines, MDPI Machines (submitted, in Review) The dataset includes machine metadata, torque vs. speed envelopes, and copper-loss/power-factor maps. Analytical data are generated using the extended normalized parameter plane model from the associated publication, while FEA data are derived from the simulation workflow described therein. Measured data are provided for machine M3 in $\Upsilon$ and $\Delta$ configurations from dynamometer test-bench measurements. The six machines include three commercially available and one development rare-earth IPMSM traction machines and two virtual ferrite PMaSynRM benchmark designs. The normalized format enables comparison across different voltage classes, current limits, torque ratings, and speed ranges, making the dataset suitable for benchmarking, model validation, and evaluation of winding reconfiguration strategies.

Authors 5

1. Rajesh Kallur-Krishnamoorthy Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

2. Haoran Wang Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

3. Hassan Currimbhoy Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

4. Markus Eisenbarth Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

5. Jakob Andert Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University