Deep learning models for electric motor winding temperature estimation and control
US12278583B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 20, 2022 |
| Grant date | Apr 15, 2025 |
| Priority date | — |
| Expiry date | May 19, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A motor control system includes a motor including a plurality of windings, a first sensor configured to sense a first operating parameter of the motor, a second sensor configured to sense a second operating parameter of the motor, and memory hardware configured to store a machine learning model and computer-executable instructions. The machine learning model is trained to generate a winding temperature estimation output based on motor operating parameter inputs. The motor control system includes processor hardware configured to execute the instructions and use the machine learning model to cause the motor control system to generate a winding temperature estimation output using the machine learning model based on the first operating parameter and the second operating parameter, the temperature estimation output indicative of a predicted temperature of the plurality of windings, and control the motor based on the winding temperature estimation output.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.