With the emergence of large-scale, high-frequency modular converters, high-performance distributed control systems (DCSs) are receiving increasing attention. These systems demand both high-data-rate communication and low synchronization error (SE). Xilinx Aurora, an interface Intellectual Property (IP), supports multi-gigabit data rates but lacks timing distribution capabilities. This paper proposes Synchronous Aurora (Sync-A), an enhanced Aurora-like IP that implements White Rabbit (WR)-based synchronization techniques on top of the existing Xilinx Aurora IP, achieving both multi-gigabit data rates and sub-nanosecond SE timing distribution. The operating principles of WR and the implementation of WR-based synchronization techniques in the Sync-A IP are explained in detail. An overview of the proposed IP is presented to highlight its ease of use. Experimental results validate its performance.

With the emergence of multilevel converters, distributed control systems (DCSs) are becoming increasingly popular due to their scalability, modularity, and flexibility. However, DCSs present a significant challenge: synchronization among controllers, particularly when implementing advanced control schemes. Ultra-precise synchronization requires the concurrent realization of frequency, time, and phase synchronization. This paper gives an overview of FPGA-based synchronization techniques covering all three subcategories, including: 1) clock-sharing-based and clock-recovery-based frequency synchronization, 2) Precision Time Protocol (PTP)-based time synchronization, 3) White Rabbit Network (WRN)-based phase synchronization. The operating principles, FPGA implementation, and experimental results of these techniques will be discussed.

Electric machines are sensitive to parameter variations and faults, which manifest as long-term or abrupt changes, gradually leading to a loss of regulation if neglected. Detecting and identifying them is crucial for ensuring these machines’ robust performance and reliability, especially for electromagnetic parts, which are more implicit and difficult to detect than mechanical parts. This paper explores a dq-axis frequency-sweeping approach to construct the terminal-behavior model, which analyzes the electrical interface’s input small-signal response. The response is later decoupled from the source output impedance and mechanical load input impedance to obtain an un-terminated model by suppressing load torque oscillation. The electrical terminal-behavior of healthy and faulty machines is captured as frequency response functions, which can be used for real-time detection of parameter variations or faults. A mapping between the un-terminated electrical terminal-behavior models and various faulty or parameter-varying cases can be established by systematically sweeping through different fault conditions and operating points. Simulation results are presented to demonstrate the validity and practicability of this approach, especially for inter-turn short-circuit faults. The interior permanent magnet synchronous motor (IPMSM) is used as an example, but the method is extendable to other types of motors.