Due to the need for highly efficient and compact power electronic converters to operate at higher frequencies, traditional wire-wound magnetics are not suitable. This paper provides a comprehensive review of planar magnetic technologies, discussing their advantages as well as associated disadvantages. An extensive review of the research literature is presented with the aim of suggesting models for planar magnetics. Several strategies are proposed to overcome the limitations of planar magnetics, including winding conduction loss, leakage inductance, and winding capacitance. The goal of this study is to provide engineers and researchers with a clear roadmap for designing planar magnetic devices.

Electric shovels have been widely used in heavy industrial applications, such as mineral extraction. However, the performance of the electric shovel is often affected by the complicated working environment and the proficiency of the operator, which will affect safety and efficiency. To improve the extraction performance, it is particularly important to study an intelligent electric shovel with autonomous operation technology. An electric shovel experimental platform for intelligent technology research and testing is proposed in this paper. The core of the designed platform is an intelligent environmental sensing/perception system, in which multiple sensors, such as RTK (real-time kinematic), IMU (inertial measurement unit) and LiDAR (light detection and ranging), have been employed. By appreciating the multi-directional loading characteristics of electric shovels, two 2D-LiDARs have been used and their data are synchronized and fused to construct a 3D point cloud. The synchronization is achieved with the assistance of RTK and IMU, which provide pose information of the shovel. In addition, in order to down-sample the LiDAR point clouds to facilitate more efficient data analysis, a new point cloud data processing algorithm including a bilateral-filtering based noise filter and a grid-based data compression method is proposed. The designed platform, together with its sensing system, was tested in different outdoor environment conditions. Compared with the original LiDAR point cloud, the proposed new environment sensing/perception system not only guarantees the characteristic points and effective edges of the measured objects, but also reduces the amount of processing point cloud data and improves system efficiency. By undertaking a large number of experiments, the overall measurement error of the proposed system is within 50 mm, which is well beyond the requirements of electric shovel application. The environment perception system for the automatic electric shovel platform has great research value and engineering significance for the improvement of the service problem of the electric shovel.

This paper investigates the effect of different designs and arrangements of conductors on the operational parameters of a planar inductor. Accordingly, it is suggested that there is no one-size-fits-all design that can achieve all desired parameters in every application, and the best design should be determined by the needs of the application. In order to have a comprehensive study, four different structures are considered and compared. Numerous design parameters such as track width, track length, location of the conductors between the central limb and the lateral limb, and number of transposition points among subtracks for both air-core and ferrite-core inductors are considered. Each structure is evaluated according to AC resistance, $R_{AC}/R_{DC}$, and inductance. Measurement results reveal that it is critical to take into account all three characteristics when deciding the suitable structure for the conductors. Studies are carried out based on measurement results for experimental prototypes in the frequency range of 10 Hz–1 MHz, and a set of guidelines is provided with regard to the design of planar inductors to achieve desired characteristics.

In this paper, a novel control method for back-to-back converters used in grid-to-motor connections is explored.To increase the robustnessoflow DC-link capacitances, a controlmethod based on variable switching point model predictive controlis proposed. While previous model predictive control methods forthe back-to-back converter selected a certain switching state tofulfill all control goals, we use the switching time in additionto the switching statein order to minimise deviations from thetarget voltage. Choosing a variable switching point provides anadditional degree of freedom to the control frameworkand allowsthe system to copewith the large number of control variables. Inthis case, the variable switching point is used to minimize theeffects of low DC-link capacitances on the system. This caneitherbeachieved by selecting a switching point that yields low DC-link capacitor charging or by selecting a switching point thataims to keep the DC-link voltage close to the reference. Theproposed method is verified through numerical simulations andhardware-in-the-loop (HIL) experiments and compared to existingapproaches. The results show that it is possible to control the DC-link using only the switching point of the converter.