In the realm of power electronics, ensuring the efficiency of DC-DC converters is paramount. This study focuses on optimizing efficiency through switching frequency in multiphase interleaved DC-DC converters. It presents an in-depth analysis of power losses, emphasizing frequency-dependent variations and capacitor losses at both input and output. Experimental results using a three-phase interleaved boost converter highlight the influence of switching frequency and phase-shift on efficiency. The study also explores the feasibility of real-time switching frequency correction, suggesting it may not always be beneficial due to potential increases in voltage and current ripple and energy imbalances. This research provides valuable insights and practical recommendations for improving the design and operation of these converters.

Battery Energy Storage Systems (BESS) play a crucial role in enhancing Distributed Energy Resources (DERs) efficiency and reliability. Managing these systems across diverse DER environments presents challenges due to the dynamic nature of the grid, market fluctuations, and the inherent complexities of both DERs and the batteries themselves. This paper proposes a new approach for adaptive battery management in DERs, utilizing meta learning for Deep Q Networks. We trained an autonomous agent in a reinforcement learning environment, enabling it to optimize battery operations across multiple DER locations with minimal training data. The effectiveness of the proposed method is validated through a two-stage process. First, the agent undergoes meta-learning training in the reinforcement environment, equipping it with the necessary decision-making capabilities. Second, its performance is evaluated through a simulation using real world data on energy consumption, generation, and pricing. The agent excels at handling multiple objectives simultaneously and pursues three key goals: maximizing renewable energy usage, maintaining healthy battery states of charge, and potentially reducing energy costs for consumers.

This paper presents an improved current sensor fault-tolerant control for vector control of induction motors. This work aims to reconstruct the three current phases even under the failure of two or three current sensors and make the vector control in service under this situation. Therefore, the proposed scheme is made up of three blocks, vector control, sliding mode observers for the diagnosis process, and the reconfiguration algorithm. In the case of the failure of two or three current sensors, we will use the DC-link current sensor of the inverter to reconstruct the three phases currents. In addition, a synchronization technique named as PFCE (Positive Fundamental Component Estimator) is used to obtain results similar to real currents. Simulation results are presented discussing the studied approach.

In this paper, the harmonic components of the input current of an interleaved boost converter under an open switch fault (OCF) are analyzed. A deep investigation of harmonic under different situations such as CCM, DCM, and Load’s change is conducted for a diagnosis purpose. Moreover, the study will show the effect of parameter change and switching frequency on the harmonic spectrum of the input current. Simulation results with experimental tests investigating the frequency analysis of the interleaved three boost converter under an OCF switch fault are presented.

Open-loop synchronization techniques OLSs can be classified into True (TOLS) and Pseudo or Quasi-OLSs (POLS/QOLS). The TOLS means a system that has no feedback in its structures which results in unconditional stability. Roughly speaking the advanced TOLSs suffers from two main drawbakcks:1) compromising performances under off-nominal frequencies in faulty conditions, 2) inefficiency under large frequency drifts and high computation time. To tackle the problem of frequency adaptivity, the POLS uses a frequency estimator. This technique works efficiently under large frequency drifts even in faulty conditions and benefits from low computation time. However, one of the main challenges in OLS techniques is how to improve dynamic performance without compromising the ability to reject disturbances. In this paper, an enhancement is made to the standard POLS to tackle this problem. The use of a cascade positive fundamental components estimator (PFCE) will allow us to enhance the response time while keeping the phase and magnitude error at their lowest. The mathematical model is presented then simulated. The simulation results validate this proposal.