PEAS Ph.D. Student Mohsen Hosseinzadehtaher received the prestigious best paper award from 2019 International IEEE Conference on Smart Grid and Renewable Energy

PEAS Ph.D. Student Mohsen Hosseinzadehtaher received the prestigious best paper award from 2019 International IEEE Conference on Smart Grid and Renewable Energy for his paper co-authored with Ph.D. students Ahmad Khan, Matt Baker and Dr. Mohammad Shadmand. Their paper proposed novel self-healing predictive control scheme of battery energy storage system for pulse power loads in navy applications.

Paper title: Model Predictive Self-healing Control Scheme for Dual Active Bridge Converter

This paper presents a model predictive self-healing control (MPSC) of dual active bridge (DAB) converter for battery energy storage system (BESS) application. The main feature of the proposed MPSC scheme is an autonomous corrective action at the prediction stage in comparison to conventional model predictive control (MPC) approach. This feature is required in particular for predictive controlled DAB converter to ensure and validate the predicted AC link inductor’s current n-step ahead in horizon of time. The proposed MPSC for DAB converter doesn’t require substantial tuning effort in comparison to conventional control schemes for DAB converters. The MPSC cost function is developed based on the desired phase shift between the primary and secondary sides’ voltages of the DAB transformer. The self-healing loop utilizes the feasible range of power transfer in conjunction with the AC link inductor’s voltage status i.e. profile, to validate the predicted current and phase shift for the cost function. The AC link inductor voltage profile in DAB converter could cause high error in predicted current, thus the proposed self-healing loop autonomously corrects potential error in current prediction.