Optimizing Resolver Excitation: A Rotary Transformer-Based Filter for Sinusoidal Wave Generation From Square-Wave Input
One key factor influencing the accuracy of resolver output is the type of sensor excitation waveform, which significantly impacts the computational load in the signal generation process. Historically, sinusoidal waveforms have been the ideal choice for feeding resolvers, as they yield the lowest output errors. However, generating high-frequency sine waves presents a challenge for resolver-to-digital converters. This article addresses this challenge by using the rotary transformer of the brushless wound rotor (WR) resolver as a filter to provide sinusoidal excitation while reducing computational requirements. The stator of the rotary transformer is fed with a square wave, producing a sine wave on the rotor section to feed the resolver. The design process of an effective filter with the rotary transformer is detailed, and a model for evaluating and optimizing transformer performance is proposed. Afterward, the effect of varying the transformer's electrical elements on filter performance is analyzed. Subsequently, a hybrid model for wound rotor resolvers is presented, and the performance of the sensor with square wave feeding and the designed filter is assessed. Finally, the sensor, along with the designed filter, is built and tested to validate the findings.
Authors
- Saeed Hajmohammadi (ORCID: https://orcid.org/0000-0002-3240-8532)
- Zahra Nasiri‐Gheidari (ORCID: https://orcid.org/0000-0003-0744-1442)
- Farid Tootoonchian
- Ali Farhadi-Beiranvand
- Ramin Alipour-Sarabi (ORCID: https://orcid.org/0000-0002-4066-1132)
Institutions
- Sharif University of Technology (IR)
- Iran University of Science and Technology (IR)
- K. N. Toosi University of Technology (IR)
Publication Details
- Journal
- IEEE Transactions on Transportation Electrification
- Published
- 2025-09-16
- DOI
- https://doi.org/10.1109/tte.2025.3610153
- Primary Topic
- Sensor Technology and Measurement Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00