Owing to the constantly rising energy demand, Internal Combustion Engine (ICE)-equipped vehicles are being replaced by Electric Vehicles (EVs). The other advantage of using EVs is that the batteries can be utilised as an energy storage device to increase the penetration of renewable energy sources. Integrating EVs with the grid is one of the recent advancements in EVs using Vehicle-to-Grid (V2G) technology. A bidirectional technique enables power transfer between the grid and the EV batteries. Moreover, the Bidirectional Wireless Power Transfer (BWPT) method can support consumers in automating the power transfer process without human intervention. However, an effective BWPT requires a proper vehicle and grid coordination with reasonable control and compensation networks. Various compensation techniques have been proposed in the literature, both on the transmitter and receiver sides. Selecting suitable compensation techniques is a critical task affecting the various design parameters. In this study, the basic compensation topologies of the Series–Series (SS), Series–Parallel (SP), Parallel–Parallel (PP), Parallel–Series (SP), and hybrid compensation topology design requirements are investigated. In addition, the typical control techniques for bidirectional converters, such as Proportional–Integral–Derivative (PID), sliding mode, fuzzy logic control, model predictive, and digital control, are discussed. In addition, different switching modulation schemes, including Pulse-Width Modulation (PWM) control, PWM + Phase Shift control, Single-Phase Shift, Dual-Phase Shift, and Triple-Phase Shift methods, are discussed. The characteristics and control strategies of each are presented, concerning the typical applications. Based on the review analysis, the low-power (Level 1/Level 2) charging applications demand a simple SS compensation topology with a PID controller and a Single-Phase Shift switching method. However, for the medium- or high-power applications (Level 3/Level 4), the dual-side LCC compensation with an advanced controller and a Dual-Side Phase-Shift switching pattern is recommended.

Over the past decade, there has been a great interest in the changeover from cars powered by gasoline to electric vehicles, both within the automotive industry and among customers. The electric vehicle–grid (V2G) technology is a noteworthy innovation that enables the battery of an electric vehicle during idling conditions or parked can function as an energy source that can store or release energy whenever required. This results in energy exchange between the grid and EV batteries. This article reviews various bidirectional converter topologies used in the V2G system. Additionally, it can reduce the cost of charging for electric utilities, thus increasing profits for EV owners. Normally electric grid and the battery of an electric vehicle can be connected through power electronic converters, especially a bidirectional converter, which allows power to flow in both directions. The majority of research work is carried out over the converters for V2G applications and concerns utilizing two conversion stages, such as the AC-DC conversion stage used for correcting the power factor and the DC-DC conversion stage for matching the terminal voltage. Furthermore, a bidirectional conversion can be made for an active power transfer between grid–vehicle (G2V) and V2G effectively. This review explores and examines several topologies of bidirectional converters which make it possible for active power flow between the grid and the vehicle and vice versa. Moreover, different types of charging and discharging systems, such as integrated/non-integrated and on/off board, etc., which have been used for electric vehicle applications, are also discussed. A comparison study is carried out based on several other factors that have been suggested. The utilization of semiconductors in power converters and non-conventional resources in charging and discharging applications are the two improving technologies for electric vehicles.

EVs are the recent emerging automotive technology in the transportation sector to reduce the CO ₂ emission from the internal combustion engine. The issues in EVs technology development are battery tube capacity, heavy-size batteries, fast charging, and safe charging infrastructure. The dynamic wireless charging technology shows a suitable alternative to address the charging system-related issues in EV. However, a limited number of review studies are conducted to specifically address the wireless charging pad design challenges. The wireless inductive power pad and magnetic coupling circuit design are the main factors to decide the performance of the DWPT system. This review analyzes the current developments and challenges associated with wireless charging pad design. Further, this study investigates the potential parameters which improve the performance of a DWPT system to increase the distance traveled (mileage). First, this paper discusses WRIPT technology for DWPT EV charging application, and several parameters affecting the PTE are examined. Also, the aids factors considered for designing the DWPT power pad and different magnetic resonance coupling topologies are presented. In addition, the performance evaluation of the WRIPT power pad, with in-motion testing from the major findings in earlier studies is discussed. Finally, the challenges and opportunities of the WRIPT power pad for in-motion EV charging applications are also addressed. The current state of the art of DWPT and its future directions to make DWPT EV charging systems a full-fledged method are highlighted.

This paper proposes a novel Fuzzy-MPDTC control applied to a fuel cell battery electric vehicle whose traction is ensured using a permanent magnet synchronous motor (PMSM). On the traction side, model predictive direct torque control (MPDTC) is used to control PMSM torque, and guarantee minimum torque and current ripples while ensuring satisfactory speed tracking. On the sources side, an energy management strategy (EMS) based on fuzzy logic is proposed, it aims to distribute power over energy sources rationally and satisfy the load power demand. To assess these techniques, a driving cycle under different operating modes, namely cruising, acceleration, idling and regenerative braking is proposed. Real-time simulation is developed using the RT LAB platform and the obtained results match those obtained in numerical simulation using MATLAB/Simulink. The results show a good performance of the whole system, where the proposed MPDTC minimized the torque and flux ripples with 54.54% and 77%, respectively, compared to the conventional DTC and reduced the THD of the PMSM current with 53.37%. Furthermore, the proposed EMS based on fuzzy logic shows good performance and keeps the battery SOC within safe limits under the proposed speed profile and international NYCC driving cycle. These aforementioned results confirm the robustness and effectiveness of the proposed control techniques.

The study of power load forecasting is gaining greater significance nowadays, particularly with the use and integration of renewable power sources and external power stations. Power forecasting is an important task in the planning, control, and operation of utility power systems. In addition, load forecasting (LF) aims to estimate the power or energy needed to meet the required power or energy to supply the specific load. In this article, we introduce, review and compare different power load forecasting techniques. Our goal is to help in the process of explaining the problem of power load forecasting via brief descriptions of the proposed methods applied in the last decade. The study reviews previous research that deals with the design of intelligent systems for power forecasting using various methods. The methods are organized into five groups—Artificial Neural Network (ANN), Support Vector Regression, Decision Tree (DT), Linear Regression (LR), and Fuzzy Sets (FS). This way, the review provides a clear concept of power load forecasting for the purposes of future research and study.