Wireless power transfer (WPT) has emerged as a prominent research and application area, particularly in electric vehicle charging and implantable biomedical devices. Given that coil misalignment reduces the magnetic coupling factor k, the resulting perturbations in output voltage and power directly undermine the system’s dynamical equilibrium, making stability maintenance exceedingly difficult. The choice of compensation topology is very important to the ability to resist offset, which can be said to determine the anti-offset of the system. However, there is still a lack of systematic analysis on the quantitative comparison of the output characteristics of the two typical topologies of SS and LCC-S when k changes. Therefore, this paper studies the SS and LCC-S compensation topologies. Simulink is used to build a simulation model, including the main circuit and the control link. The coupling coefficient k is used to evaluate and compare the power performance of both topologies. It is concluded that the characteristics of LCC-S approximate a constant current source make its anti-offset ability much stronger than SS when it is weakly coupled. This study provides a clear, quantitative basis for selecting the compensation topology of WPT systems when the coil is offset.
The society’s demand for express delivery storage is growing, the requirements for the automation and intelligence of goods allocation have significantly increased. Warehouse robots based on traditional path planning algorithms have drawbacks such as long planning times and lengthy paths in the context of the current large-scale and complex logistics warehousing environment. This paper aims to sort out the development process of various deep learning-based path planning methods in warehouse robots. Systematically classify those into three types: value function algorithms, policy algorithms, and value-policy hybrid algorithms, and analyze their principles. Then, by discussing the research results of various algorithms, it demonstrates the applicability of deep learning-based path planning in modern warehouse applications. Next, the advantages and disadvantages of various algorithms in the development process are compared in the form of a list, reflecting recent achievements in path planning and pointing out the future prospects and development directions in this field.
Dynamic wireless power transfer (DWPT) promises to charge electric vehicles on the move, yet doing so efficiently is hard: as the vehicle travels, the coupling inductance keeps changing, and lateral offset and abrupt load shifts only deepen the trouble. What follows is a chain of failures — resonant detuning, lost soft switching, and a restless output power—that undermines both efficiency and stability. This paper addresses them on an LCC-LCC symmetric topology through a dual-loop "frequency- and-phase" strategy. The outer loop reads the impedance angle and nudges the switching frequency to follow the drifting resonant point, holding the inverter in zero-voltage switching (ZVS); the inner loop, built on FCS-MPC, searches each cycle for the phase-shift angle that best steadies the output power. The point is to treat frequency and phase-shift angle as two separate handles—one for soft switching, one for power—so a single framework handles what earlier designs kept apart. Simulation confirms the idea: after a sudden load change, the output power settles in 7.1 ms without overshoot, about 62% faster than a comparably tuned PI controller. The strategy thus offers a workable path to efficient, stable DWPT.
The train operation control system demands extremely high positioning accuracy and real-time control. A single sensor struggles to provide continuous, high-precision positioning in complex environments like tunnels and mountains, while traditional mechanical sensors suffer from limited reliability. This paper systematically investigates three dimensions: precise positioning via multi-source information fusion, fault prediction and health management of critical components, and control strategies for stable maneuvering based on multi-source information fusion. At the positioning level, the principles of integrated navigation are elucidated and optimization pathways for filtering and fusion algorithms in complex environments are analyzed. At the health management level, an on-board PHM architecture is established and pattern-mining-based methods for advanced fault warning are studied. At the control level, sensorless position/velocity control and precise station-stop technologies are investigated, exploring the deep integration of positioning information into control decisions. Results indicate that multi-source information fusion effectively compensates for single-sensor limitations; PHM technology enables a shift from reactive to proactive maintenance; and sensorless control provides a redundant speed feedback channel for traction systems. These findings offer theoretical support for developing a train operation control system that balances safety and comfort.
The drone’s lithium battery has limited endurance, traditional wired power replenishment relies on manual labor, it is difficult to meet the demand for round-the-clock automated operations. The article conducts a systematic comparative study on five types of wireless power transmission technologies: solar energy, laser, ECPT electric field coupling, MCPT magnetic coupling, and microwave. This article examines the topology structures and energy conversion principle of five wireless charging schemes, build a customized circuit and power calculation model, analysis the influence of lighting, atmospheric loss, plate, coil, transmission distance and other parameters on charging power and efficiency, combined with simulation results, the advantages and disadvantages of the five types of technologies are compared from four dimensions: transmission distance, environmental adaptability, airborne volume, and full life cycle cost. Analysis shows: there are significant differences in the adaptation scenarios of various wireless charging technologies for drones, there are inherent shortcomings in a single solution, difficult to achieve a full scenario, all- weather self-replenishing energy. Multi-energy hybrid power supply, lightweight integration, and directional beam control are the mainstream developments in this field.
