4H-SiC lateral double implanted metal–oxide–semiconductor field effect transistors (LDIMOSFET) were fabricated on on-axis semi-insulating SiC substrates without using an epi-layer. The LDIMOSFET adopted a current path layer (CPL), which was formed by ion-implantation. The CPL works as a drift region between gate and drain. By using on-axis semi-insulating substrate and optimized CPL parameters, breakdown voltage (BV) of 1093 V and specific on-resistance (Ron,sp) of 89.8 mΩ·cm2 were obtained in devices with 20 µm long CPL. Experimentally extracted field-effect channel mobility was 21.7 cm2·V−1·s−1 and the figure-of-merit (BV2/Ron,sp) was 13.3 MW/cm2.
In the study, we develop a method to improve the accuracy of master-slave synchronization in EtherCAT networks. The method involves two key compensations that are not considered in the EtherCAT protocol. First, the propagation delay between the master and reference slave is measured, and the system time of the reference slave is then compensated for the measured propagation delay. Second, the bias component of the synchronization error between the master and reference slave is periodically estimated, and system time of each slave is then compensated for the estimated bias component. The entire method is implemented as part of the master application without modifying the EtherCAT protocol or requiring excessive computation load or large memory space. Thus, the developed method is advantageous because it can be immediately applied at low cost to existing EtherCAT networks. By performing extensive experiments based on a Linux-based EtherCAT master, we demonstrate that the developed method significantly improves the accuracy of the master-slave synchronization in EtherCAT networks.
The authors propose a parameter identification method for sequential identification of electrical and mechanical parameters of surface-mounted permanent magnet synchronous motors (SPMSMs). Two normalised least mean square (NLMS) adaptive filters (AFs) are designed for identifying the electrical parameters, where the first AF identifies the stator inductance and the second AF identifies the stator resistance and rotor flux linkage. The NLMS AFs achieve faster transient responses than recursive least squares (RLS) AFs owing to lower computing load and smaller memory size. Regarding mechanical parameters, an extended sliding-mode mechanical parameter observer (ESMMPO) is employed to estimate the system disturbance and angular velocity, from which the rotational inertia, viscous damping coefficient, and load torque are identified. The rotor flux linkage identified from the second NLMS AF is used for estimating the real-time system disturbance of the ESMMPO, which enables the identification of mechanical parameters with higher accuracy. The proposed method effectively integrates the NLMS AFs and ESMMPO into a single framework to identify both electrical and mechanical parameters of the SPMSMs. The experimental results of the proposed method are compared with those of RLS AFs and the conventional ESMMPO, which demonstrates the faster response and less steady-state parameter errors of the proposed method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.