In-situ digital twinning of induction machines via sensitivity-based genetic algorithm parameter estimation
Abstract
This paper presents a novel, non-invasive methodology for creating a high-fidelity digital twin using only steady-state operational data. The proposed approach employs a fourstep workflow with two-stage parameter identification algorithm. First, a grid-based sensitivity analysis is conducted to establish robust and constrained search boundaries. Subsequently, a genetic algorithm performs a precise search within these boundaries to identify the final T-equivalent circuit parameters. The methodology was validated on a 1.5 kW induction motor. All but core loss identified parameters demonstrated similarity with those obtained from standard offline tests, and the resulting digital twin accurately reproduced the machine?s behaviour when compared to experimental measurements.
Fields of Study & Subjects
Sensorless Control of Electric Motors
Wind Turbine Control Systems
Electric Motor Design and Analysis
Publication details
- Journal / source
- Facta universitatis - series Electronics and Energetics
- Publisher
- National Library of Serbia
- Volume
- 39
- Issue
- 1
- Pages
- 285–306
- Publication date
- 1 January 2026
- Language
- EN