Parameter Identification of IoT-Embedded PMSMs Using an AWS Cloud-Computing Platform

Permanent magnet synchronous machines (PMSM) represent the core of many industrial processes. Therefore, the monitoring of electrical and mechanical parameters and variables allows to obtain important information for a predictive maintenance and fault detection. However, some parameters are not directly measurable and need to be estimated. For this purpose, it is good to define a parameter estimation approach relevant in large-scale industrial processes. In this paper a parameter identification of IoT-Embedded PMSMs approach is defined. This approach combines the benefits of IoT, edge computing and cloud computing technologies. AWS services are used in the implementation of the parameter identification algorithm in cloud environment. So, a scalable, reliable, and secure solution is obtained to be applied in contexts related to facility management.