Non-invasive condition monitoring for boost converter based on crow search algorithm

Condition monitoring is an effective methodology to evaluate the health state of power electronics converters. Aiming at multiple devices health state estimation for boost converters, a non-invasive condition monitoring technique is proposed in this paper. Taking the equivalent circuit model of these components into consideration, the formulations of failure precursors with detection signals are derived based on hybrid system theory. Then, the parameter identification problem is translated into an objective function optimization issue. Therefore, the precursor parameter values of inductor, capacitor, diode and power MOSFET can be obtained using crow search algorithm. Meanwhile, the boost converters under variable operating conditions are also analyzed. Compared with particle swarm optimization (PSO) method, both simulations and experiments are conducted to validate the effectiveness of the presented approach. The results show that these parameters can be estimated simultaneously and the identification accuracy of them reaches to more than 90%.