Year: 2026
Type: article
Abstract: In recent years, the digital emulation of power systems, such as induction machines, has increased, driven by advances in computational resources and the processing capabilities of digital platforms. These platforms offer a versatile approach to the design, analysis, and optimization of solutions in electric machine drive research. This work presents the design of an Induction Machine (IM) using a digital twin, simulating its performance and behavior under failure conditions using the DQ model. Additionally, this study presents the design and real-time digital emulation of an IM, incorporating a bearing-fault model. The implementation on an FPGA platform enables high-fidelity simulation and analysis of the machine’s performance under both healthy and faulty operating conditions. This approach introduces a distinctive and critical tool for pre-experimental validation, enabling the precise identification of key fault signatures and system responses under real-time conditions, a capability that is not explicitly addressed in existing studies. Quantitative results demonstrate that the digital model implementation is highly accurate in replicating the theoretical IM with a relative error below (<1%). Additionally, through frequency-domain analysis, the signatures of the injected fault can be observed.
Source: Processes
DOI: 10.3390/pr14030456
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7125973269