Design of Induction Machines using Reinforcement Learning
Yasmin SarcheshmehPour Tommi Ryyppo Victor Mukherjee Alex Jung
The design of induction machine is a challenging task due to different
electromagnetic and thermal constraints. Quick estimation of machine's
dimensions is important in the sales tool to provide quick quotations to
customers based on specific requirements. The key part of this process is to
select different design parameters like length, diameter, tooth tip height and
winding turns to achieve certain torque, current and temperature of the
machine. Electrical machine designers, with their experience know how to alter
different machine design parameters to achieve a customer specific operation
requirements. We propose a reinforcement learning algorithm to design a
customised induction motor. The neural network model is trained off-line by
simulating different instances of of electrical machine design game with a
reward or penalty function when a good or bad design choice is made. The
results demonstrate that the suggested method automates electrical machine
design without applying any human engineering knowledge.