The high-voltage battery is a crucial element for EV traction systems. It is the primary energy source that must be regularly recharged to reach the autonomy declared by the manufacturer. Therefore, an EV charging system is required to ensure the battery charging process. This review thoroughly investigates the available EV charging technologies and the most popular batteries for EV applications. The contributions of this work can be summarized as follows: the classification and topologies of electric vehicle chargers are examined, an overview of the current EV charging standards is provided, the state-of-the-art of EV charging couplers is discussed, and the most widely used batteries in EV applications are reviewed.

In this paper, the major factors that affect the performance of wireless power transfer systems, such as coil inner radius and coil number of turns, are discussed. A comparison of three coil shapes covering the coreless case, the case with ferrite, and the case with ferrite and aluminum is also carried out. Another comparison is proposed by addressing the combination of different coil shapes in the wireless power transfer (WPT)system. The analysis covers the coupling coefficient, the mutual inductance, and the self-inductance. Due to the complexity of calculating these parameters, the finite element analysis (FEA) method is adopted by using the Ansys Maxwell software. An introduction to the typical WPT system for electric vehicle charging is also presented.

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.

This paper compares the performance of different control techniques applied to a high-performance brushless DC (BLDC) motor. The first controller is a classical proportional integral (PI) controller. In contrast, the second one is based on adaptive neuro-fuzzy inference systems (proportional integral-adaptive neuro-fuzzy inference system (PI-ANFIS) and particle swarm optimization-proportional integral-adaptive neuro-fuzzy inference system (PSO-PI-ANFIS)). The control objective is to regulate the rotor speed to its desired reference value in the presence of load torque disturbance and parameter variations. The proposed controller uses a dSPACE platform (MicroLabBox controller board). The experimental prototype comprises a PEMFC system (the Nexa Ballard FC power generator: 1.2 kW, 52 A) and a brushless DC motor BLDC of 1 kW 1000 rpm. The PSO-PI-ANFIS controller presents better performance than the PI-ANFIS and classical PI controllers due to its ability to optimize the PI-ANFIS controller’s parameters using the particle swarm optimization (PSO) algorithm. This optimization results in improved tracking accuracy and reduced overshoot and settling time.

Wireless power transfer (WPT) chargers are promising solutions for charging electric vehicles (EVs). Due to their advantages such as ease and safety of use, these chargers are increasingly replacing conductive ones. In this paper, we first provide a detailed analysis to illustrate the effect of varying parameters on the operation of the WPT charger. Secondly, we present the main design steps of the charger elements while respecting the recommendations of the SAEJ2954 standard in terms of operating frequency, efficiency and misalignments. Regarding the design of the ground-side and vehicle-side coils, we propose three different circular geometries whose parameters are determined using an iterative approach. The latter is compared with a finite element analysis performed under Ansys Maxwell software showing the convergence between theoretical calculations and the simulation results. Finally, an experimental prototype with a power of 500 W is realized. In addition, different test scenarios are performed to validate the proposed design approach. In this respect, an efficiency of 90% is obtained for a power of 500 W and a distance between coils of 125 mm. Moreover, the test of the charger in the most unfavorable operating case (misalignments of Δx = 70 mm, Δy = 10 mm and Δz = 150 mm) gives an efficiency of 83.5%, which remains above the limit of the SAEJ2954 standard.

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.