The main component of the hydrogen production system is the electrolyzer (EL), which is used to convert electrical energy and water into hydrogen and oxygen. The power converter supplies the EL, and the controller is used to ensure the global stability and safety of the overall system. This review aims to investigate and analyze each one of these components: Proton Exchange Membrane Electrolyzer (PEM EL) electrical modeling, DC/DC power converters, and control approaches. To achieve this desired result, a review of the literature survey and an investigation of the PEM EL electrical modeling of the empirical and semi-empirical, including the static and dynamic models, are carried out. In addition, other sub-models used to predict the temperature, gas flow rates (H₂ and O₂), hydrogen pressure, and energy efficiency for PEM EL are covered. DC/DC power converters suitable for PEM EL are discussed in terms of efficiency, current ripple, voltage ratio, and their ability to operate in the case of power switch failure. This review involves analysis and investigation of PEM EL control strategies and approaches previously used to achieve control objectives, robustness, and reliability in studying the DC/DC converter-PEM electrolyzer system. The paper also highlights the online parameter identification of the PEM electrolyzer model and adaptive control issues. Finally, a discussion of the results is developed to emphasize the strengths, weaknesses, and imperfections of the literature on this subject as well as proposing ideas and challenges for future work.

In road transportation, the market for electric vehicles (EVs) is considered a potential solution for addressing issues related to gas emissions and noise pollution. Due to the limited driving range of the EV battery pack, the charging process must be fast and safe for EV drivers. Wireless charging technology for EVs has gained attention in recent years, and in this research, the authors explore the analysis and design of a resonant magnetic wireless system for charging electric vehicles. The authors propose a design methodology for a serial–serial (SS) wireless system, which outlines how to determine the appropriate pad dimensions for transferring power to the EV battery. The design approach is crucial to attaining the best possible coupling performance and efficiency. Additionally, the magnetic design of the pad is validated using Ansys Maxwell software, and the proposed design is co-simulated using Ansys Simplorer to analyze the performance of the system. Simulation results demonstrate that the proposed model can transfer over 3.7 kW of power with an efficiency of over 90.02%. The paper also discusses the bifurcation phenomenon at the resonance condition to ensure maximum efficiency.

It is well known that the classical topologies of Buck–Boost converters drain pulsating current from the power source. These pulsating currents entail acceleration of the aging rate of the fuel cell. In this paper, we are considering a Buck–Boost DC–DC converter topology featuring continuous input current. The converter interleaved structure ensures the substantial increase in power density compensating power losses related to the converter switching nature. The control objective is to enforce the DC-bus voltage to track its desired value despite load uncertainties and to ensure adequate current sharing between the different parallel modules of the fuel cell interleaved Buck–Boost converter (FC-IBBC). The point is that the internal voltage of the fuel cell is not accessible for measurement. Therefore, the state-feedback control, which consists of nonlinear control laws, is designed on the basis of a nonlinear model of the FC-IBBC system. We formally prove that the proposed controller meets its objectives, i.e., DC-bus voltage regulation and equal current sharing. The theoretical proof relies on the asymptotic stability analysis of the closed-loop system using Lyapunov stability tools. The theoretical results are well confirmed both by simulation, using MATLAB^®/Simulink^®, and by experimental tests using DS 1202 MicroLabBox.

The high cost and complexity of Proton Exchange Membrane (PEM) electrolyzers pose substantial challenges for their integration and testing within smart grid emulators. Addressing this, our research offers two pivotal contributions. First, we introduce an innovative Equivalent Electrical Circuit (EEC) for PEM electrolyzers. This electrical model serves as an essential tool for evaluating the performance of PEM electrolyzers, especially within the framework of renewable energy systems in smart grids. Our second major contribution is the design and implementation of a hardware PEM electrolyzer emulator based on a DC/DC boost converter. Unlike conventional approaches, our emulator accurately reproduces the nonlinear polarization curve and dynamic behavior of PEM electrolyzers under a large range of operating conditions. By seamlessly integrating into a smart grid emulator, it provides an environment for efficient and cost-effective testing of PEM electrolyzers. Experimental results offer strong validation of the emulator’s ability to replicate the characteristics of the PEM electrolyzer, establishing it as a practical alternative for evaluating and improving smart grid emulators and their management strategies.

In wireless sensor networks (WSNs), optimizing energy consumption, and ensuring efficient data transmission are crucial for network longevity and performance. This paper introduces an enhanced clustering technique for WSNs that aims to extend network lifetime and ensure reliable data delivery. Instead of regular K-Means clustering, we integrate the Silhouette score method to evaluate cluster quality and decide the optimal number of clusters. This improves how nodes are grouped together in the network. Additionally, we strategically select routing paths from cluster heads to the base station that minimize energy drainage. Comprehensive simulations show our dual optimization approach outperforms standard K-Means in terms of energy efficiency, stable network organization and effective data transmission and overall, the proposed improvements to clustering and routing significantly advance energy-constrained WSNs toward more sustainable and dependable real-world applications

Smart parking is common in contemporary cities. These smart parking lots are outfitted mostly with wireless sensor networks (WSNs), which are used to detect, monitor, and collect data on the availability status of all existing parking spaces in a given area. Sensors make up WSN, which may gather, process, and transmit informations to the sink. However, the power and communication limitations of the sensors have an effect on the performance and quality of the WSNs. The decrease in the battery and the energy of the nodes causes a decrease in the life of the nodes and also of the entire WSN network. In this article, we present a routing protocol that implements an efficient and robust algorithm allowing the creation of clusters so that the base station can receive data from the entire WSN network. This protocol adopts a reliable and efficient algorithm allowing to minimize the energy dissipation of the sensors and to increase the lifetime of the WSN. In comparison to alternative parking lot management protocols already in use, the simulation results of the proposed protocol are effective and robust in terms of power consumption, data transmission reliability, and WSN network longevity.