The increasing adoption of renewable energy sources (RES), such as solar photovoltaics and wind turbines, is transforming electricity generation. However, integrating RES within DC microgrids (DCM) for applications such as fast DC charging in electric vehicles (EVs) presents challenges, including low inertia, power fluctuations, and voltage instability. This study addresses these challenges with novel control strategies and optimization algorithms. A hybrid Firefly Algorithm-Particle Swarm Optimization (FA-PSO) approach is used to tune Takagi-Sugeno Fuzzy Inference Systems (TSFIS), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), and Fractional Order Proportional-Integral-Derivative (FO-PID) controllers. This strategy optimizes power management within the DCM, ensuring faster convergence, superior accuracy, and reduced topological constraints. In addition, a comprehensive Small Signal Stability Analysis (SSSA) evaluates the impact of the proposed hybrid optimization techniques on DC microgrid stability. Crucially, a hardware prototype validates these strategies under real-world uncertainties, such as varying wind speed and solar insolation, demonstrating their effectiveness and feasibility for practical DC microgrid applications with integrated EV charging.

This article proposes a review map for comparative designs of wireless high-power transfer (WHPT) systems using single- and double-resonance blocks. In-depth analyses and key guidelines are provided to design high-efficiency WHPT systems while keeping zero-phase-angle/unity-power-factor and constant - current/voltage supply to the load. Basic single- and double-resonance blocks based on LC- resonant circuits are analyzed. Then, resonant S- and T- blocks are recommended as the best transmission blocks for competitive designs. The proposed approach is applied to map recent developments on the wireless charging technologies for electric vehicles (EVs), especially for weak-coupling systems and dynamic-charging technologies. The proposed design approach offers a systematic and effective methodology to quickly evaluate current technologies and solutions for WHPTs in EVs applications. In extension, this article indicates different control strategies for WHPTs, especially for optimal-efficiency tracking. Design guidelines and control strategies are provided to achieve the maximum efficiency at a standard resonance frequency against variations from loads and coupling coefficients in operation which can easily map to recent research works and future research directions. Experimental verifications of dominant designs are also presented to validate the proposed approach. The map for comparative designs and control structures presented in this article aims to serve as a guideline and to ease the initial steps for other researchers in this area.

This article presents a new open-end winding induction motor (OEWIM)-based dual-motor differential four-wheel drive (D4WD) for the electric vehicle (EV). Constant speed operation through cruise control is achieved using direct torque control (DTC) algorithm. The redundant vectors are used in the switching vector selection of the DTC algorithm to achieve balanced battery currents. Fault-tolerant operation (FTO) of the drive is demonstrated, where the EV will work with full torque even if one of the inverters in rear motor drive or front motor drive or both fail. The dynamic model of the proposed drive is presented. The proposed drive and FTO are verified through simulation as per the FTP-75 driving cycle. An experimental prototype of the proposed drive is developed, and the abovementioned algorithms are verified experimentally as per the FTP-75 and HFET driving cycles. Both the simulation and experimental results are presented, and these results agree with the theoretical observations. Stable operation of EV for the entire test cycle under normal operation, as well as inverter fault conditions, is demonstrated.

For high-power electric vehicles (EVs), the drive propulsion based on induction motors is emerging as economical alternative. Compared to conventional induction motors, the open-end winding induction motor (OEWIM) requires only half the dc-bus voltage for the given torque. The EV power train based on the dual two-level voltage-source inverter (VSI)-fed OEWIM with isolated dc sources is used in this research. For uniform state-of-charge (SoC) distribution, the power flow from each isolated source needs to be controlled. A two-stage model-predictive direct torque control (MPDTC) scheme is proposed to balance the SoC of batteries by proper selection of the VSI voltage vectors. The proposed MPDTC scheme is free from weighting factor tuning and uses a ranking method to predict the optimal voltage vectors. The superiority of the proposed controller in terms of battery SoC balancing is demonstrated. The performance of the proposed MPDTC EV drive is verified for the FTP75 and HFET driving cycles under different operating conditions, both by simulation and hardware experimental tests.

The power transfer capacity of transmission lines is limited by the stability of the power system. Additionally, the dynamics of photovoltaic (PV) integration through the grid following inverter (GFI) affect the stability limits, which are not well studied in the literature. This paper, therefore, focuses on the stability-constrained power transfer capabilities of transmission lines with single-phase PV-GFI integration. An adaptive tuning method is proposed based on Lyapunov function analysis that increases the power transfer capability limit. Outer and inner control loop parameters are considered as candidates for the proposed method. The proposed tuning law is not affected by the active and reactive power requirements, low-voltage or over-voltage ride-through, network impedance, and load changes. Additionally, an active damping method utilizing a capacitor voltage feedback loop is proposed to eliminate the effect of resonance with improved power quality. The proposed method is validated through simulation and experimental verification for various test scenarios, such as sudden changes in solar irradiance, dynamic load changes, network parameter variation, and grid voltage sag-swell conditions. The proposed tuning method achieves an enhanced power transfer capacity limit compared with the existing method.

A PV three-phase grid following inverter (GFI) with LCL filters can reduce current harmonics and deliver active power to the grid. Controlling such higher-order systems is challenging due to system uncertainties, grid voltage variations, and filter resonance. Active disturbance rejection control (ADRC) provides resilience to these uncertainties and a prompt response to disturbances. A linear extended state observer and a phase-locked loop observer are integrated into the ADRC structure to optimize tracking performance. The proposed controller uses a structured inner and outer closed-loop ADRC that takes into account process delays and extended state observer dynamics. The GFI can operate under variable grid voltage frequencies or even deviations in frequency caused by grid failure, and is able to meet these challenges as part of the design process and the synchronization approach. Both simulation and experimental results are given to validate the dual ADRC-based methods for an 8 kW laboratory prototype PV-GFI system.