System and method of predicting behavior of electric machines

A system for predicting behavior of an electric machine, the system comprising:

• a processor;
• and
• a memory unit communicatively coupled to the processor, wherein the memory, when executed by the processor, is configured to:
• generate a simulated-dataset comprising simulated design results for electromagnetic properties, structural properties, and acoustic properties of the electric machine, wherein the simulated-dataset is generated by simulating at least one operating condition of the electric machine on parametric models generated from design parameters of the electric machine;
• train artificial neural network models using the simulated design results and an output of the parametric models for the at least one operating condition of the electric machine;
• and
• predict the behavior of the electric machine by orchestrating execution of the artificial neural network models for custom design parameters.

A non-transitory computer-readable medium having stored thereon instructions that, in response to execution, cause a system comprising a processor to:

• generate a simulated-dataset comprising simulated design results for electromagnetic properties, structural properties, and acoustic properties of an electric machine, wherein the simulated-dataset is generated by simulating at least one operating condition of the electric machine on parametric models generated from design parameters of the electric machine;
• train artificial neural network models using the design parameters and the simulated design results output from the parametric models in response to the at least one operating condition of the electric machine;
• and
• predict behavior of the electric machine by orchestrating execution of the artificial neural network models for custom design parameters.