Meta-Heuristic Optimization and Variable Sparsity Combination of Two LMS Framework Based Charging Solutions for Electric Transportation

A grid-tied hybrid charging station is developed to provide fast charging. It is designed with incorporation of two framework adaptive filters, aiming to enhance power quality and detect variable sparsity in a multifunctional charging station. To regulate dc-link voltage to the desired level, a cascaded proportional-integral controller is utilized in conjunction with a bidirectional converter. Proportional-integral controller's parameters are optimized through a meta-heuristic swarm-based technique, with integral time square error as the optimization criterion. This optimization ensures that proportional-integral controller delivers the desired response. The efficacy of this proposed control is validated through both simulated and experimental laboratory prototype results.