Load identification of domestic induction heating based on Particle Swarm Optimization

Resonant power converters are widely used in domestic induction heating (IH) cooktops due to their advantages in terms of size, efficiency, and power density. The wide range of different induction loads (with different electrical equivalent) and the wide range of required output powers, lead to the load identification as a mandatory and specially challenging aspect. This identification is needed to improve static operation, by identifying IH load that may lead to too high currents through the inverter, and dynamic operation, by correcting the gain of the digital controller according to the identified IH load. This work focuses on applying and evaluating the Particle Swarm Optimization (PSO) algorithm to identify the system load in domestic induction heating. Therefore, the obtained load parameters lead to a more efficient control strategy of the delivered power according to the user requirements. Simulation and experimental results in an induction heating prototype are performed in order to validate the proposed identification algorithm.