Reduction of transients in switches using embedded machine learning

P. Suresh (SRM Institute of Science and Technology)
S. George Fernandez (SRM Institute of Science and Technology)
S. Vidyasagar (SRM Institute of Science and Technology)
V. Kalyanasundaram (SRM Institute of Science and Technology)
K. Vijayakumar (SRM Institute of Science and Technology)
Vaidheeswaran Archana (National university of Singapore)
Soham Chatterjee (Nanyang Technical University)

International Journal of Power Electronics and Drive Systems (IJPEDS)
Vol 11, No 1: March 2020

Non-linear loads can cause transients in electronic switches. They also result in a fluctuating output when the device is switched ON or OFF. These transients can harm not only the switches but also the devices that they are connected to, by passing excess currents or voltages to the devices. By applying machine learning, we can improve the gate drive voltages of the switches and thereby reduce switch transients. A feedback system is built that measures the output transients and then feeds it to a neural network algorithm that then gives a proper gate drive to the device. This will reduce transients and also improve performances of switch based devices like inverters and converters.