Wireless power transfer (WPT) has emerged as a key enabling technology for the large-scale adoption of electric vehicles (EVs), offering enhanced charging flexibility, improved safety, and seamless integration with intelligent transportation and renewable energy infrastructures. This paper presents a comprehensive review and technical synthesis of WPT technologies spanning both near-field and far-field domains, including inductive power transfer (IPT), magnetically coupled resonant WPT (MCR-WPT), capacitive power transfer (CPT), microwave power transfer (MPT), and laser wireless charging (LPT). Particular emphasis is placed on MCR-WPT, the most widely adopted approach for EV wireless charging, for which the coupler structures, resonant compensation networks, power converter architectures, and control strategies are systematically analyzed. The review further identifies that hybrid WPT architectures, adaptive compensation design and wide-coverage coupling mechanisms will be central to enabling high-power, long-distance, and misalignment-resilient wireless charging solutions for next-generation electric transportation systems.

This article proposes a three-port LCL resonant wireless power transfer system with hybrid power flow control methods for dc--dc energy conversion applications. Two half-bridge microinverters provide the dual input ports for DC energy sources, while the load port is connected through an LCL--LCL wireless coupling tank loaded with a full-bridge rectifier. The three-port topology allows flexible power transfer between dual input sources while the two sources share one LCL resonant tank to transfer energy to the load without additional components. The control function of this proposed system can be divided into two phases. In phase one, PWM method is employed to implement bidirectional power transfer between dual input sources by controlling the average dc offset current in the LCL resonant tank. In phase two, phase-shift modulation (PSM) method is applied to regulate wireless power output for load. The proposed modulation methods enable the system to take sources with different voltage levels at the dual input ports. Theoretical time domain analysis of the proposed topology and LCL coupling tank is presented in detail. Open-loop simulation is carried out to obtain the power transfer characteristics between the multiple ports, and closed-loop simulation is done to verify the efficiency of the designed control method. A 200 W prototype was built to evaluate the performance of the proposed topology. Experimental results show that the proposed system can achieve a peak efficiency of 93.6% with the load-independent constant current performance achieved.

The DC-DC boost converter plays a crucial role in interfacing low-voltage sources with high-voltage DC buses in DC microgrid systems. To enhance the dynamic response and robustness of the system under large-signal disturbances and time-varying system parameters, this paper proposes a hybrid control strategy that integrates proportional–integral (PI) control with a deep Q-network (DQN). The proposed framework leverages the advantages of PI control in terms of steady-state regulation and a fast transient response, while also exploiting the capabilities of the DQN agent to learn optimal control policies in dynamic and uncertain environments. To validate the effectiveness and robustness of the proposed hybrid control framework, a detailed boost converter model was developed in the MATLAB 2024/Simulink environment. The simulation results demonstrate that the proposed framework exhibits a significantly faster transient response and enhanced robustness against nonlinear disturbances compared to the conventional PI and fuzzy controllers. Moreover, by incorporating PI-based fine-tuning in the steady-state phase, the framework effectively compensates for the control precision limitations caused by the discrete action space of the DQN algorithm, thereby achieving high-accuracy voltage regulation without relying on an explicit system model.

The constant current followed by constant voltage (CC-CV) charging method is commonly employed for battery charging, effectively extending battery life and reducing charging time. However, as charging progresses, the battery’s internal resistance increases, complicating the charging circuit. This paper designs a wireless power transfer system utilizing an LCL coupling network for battery charging. The system employs frequency modulation (FM) to manage its CC and CV output characteristics at two fixed frequency points. The influence of the LCL coupling network parameters on system output characteristics was investigated using MATLAB. A simulation model was developed in the PSIM environment to validate the CC and CV output characteristics. The simulation results show that the system has load-independent constant-current and constant-voltage characteristics at two different frequency points. In order to verify the theoretical analysis, an experimental platform was also established. Experimental results demonstrate that the proposed system operates effectively in CC mode, maintaining constant output current across various loads, while in CV mode, it effectively regulates output voltage for different loads. The designed frequency modulation controller ensures a rapid response to sudden changes in load resistance, regardless of operating in CC or CV modes.

With the rapid development of smart grid (SG) technologies, massive system data has been generated for SG for grid operation status monitoring and fault warning, this massive integrated data has brought great challenges for data transmission and storage. Thus, the breakthrough of data compression technology has become more and more important for data processing, this proposal, a lossless data compression method is proposed. The proposed method improves the Lempel-Ziv-Welch (LZW) algorithm. Specifically, the proposed method employs a parallel search approach to search the index of the dictionary globally by dividing the dictionary into several small dictionaries of different sizes and bit widths. In addition, the dynamic variable-length coding method is used as the output code which can offer flexible bit widths instead of fixed values, and the optimal dictionary partition combination and size parameters are selected to construct dictionaries. At last, the improved algorithm is cascaded with Huffman algorithm to form the proposed data compression algorithm. The data compression efficiency has been successfully verified by comparing with conventional Huffman and LZW data compression algorithms through data simulation, and it is observed to offer a better compression ratio than those methods with only LZW algorithm or Huffman algorithm, and save storage space effectively. More than this, the proposed method has realized lossless compression for power system data and guaranteed the integrity of the data, which will have better applicability for dealing with any similar information data.

This study proposes an adaptive fault-tolerant control strategy for parametric strict-feedback systems subject to actuator faults and unknown dead-zone nonlinearities, a combination that presents significant challenges for controller design. First, a novel prescribed-performance fault-tolerant control framework is developed by incorporating a funnel function, a barrier Lyapunov function, and a bounded estimation mechanism to address the issue of multiple constrained nonlinear disturbances. Second, the proposed strategy offers two key improvements: (1) adequate compensation for the coupled effects of actuator faults and dead-zone nonlinearities, and (2) guaranteed globally prescribed transient performance, making the settling time and tracking accuracy independent of initial conditions and design parameters. Lastly, simulation results verify the approach’s effectiveness, showing rapid convergence within 0.8 s and a tracking error bounded by $\pm 0.05$, thus surpassing traditional methods.