A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is
Accurate temperature prediction plays an important role in the thermal protection of permanent magnet synchronous motors. A temperature prediction method of permanent magnet synchronous machines (PMSMs) based on proximal policy optimization is proposed. In the proposed method, the actor-critic framework of reinforcement learning is introduced to model the effective temperature prediction mechanism, and the correlations between the input features are then analyzed to select the appropriate inputdoi:10.3390/info11110495 fatcat:f37hjcwysfak5pqvrlcvregt3a