Patents by Inventor Pingan Tan

Pingan Tan has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Efficiency optimization control method and system for permanent magnet synchronous motor
    Patent number: 12348160
    Abstract: An efficiency optimization control method and system for permanent magnet synchronous motor are provided, and the method includes: step 1: obtaining an approximate optimal direct axis (d-axis) current of a permanent magnet synchronous motor by using a loss model algorithm; step 2: performing, by using the approximate optimal d-axis current as an initial value and using a deep reinforcement learning algorithm, an optimizing process on the approximate optimal d-axis current to construct an optimal deep reinforcement learning model; and step 3: inputting currently acquired state data of the permanent magnet synchronous motor into the optimal deep reinforcement learning model to obtain a control parameter value corresponding to an optimal efficiency of the permanent magnet synchronous motor, and controlling the permanent magnet synchronous motor based on the control parameter value. Therefore, real-time target control for the permanent magnet synchronous motor is achieved.
    Type: Grant
    Filed: August 30, 2023
    Date of Patent: July 1, 2025
    Assignees: XIANGTAN UNIVERSITY, FOSHAN GREEN INTELLIGENT MANUFACTURING RESEARCH INSTITUTE OF XIANGTAN UNIVERSITY, FOSHAN SHUNDE LEPUDA MOTOR CO., LTD
    Inventors: Siqi Peng, Weijun Li, Dan Guo, Hongyu Peng, Hui Li, Pingan Tan
  • EFFICIENCY OPTIMIZATION CONTROL METHOD AND SYSTEM FOR PERMANENT MAGNET SYNCHRONOUS MOTOR
    Publication number: 20230412098
    Abstract: An efficiency optimization control method and system for permanent magnet synchronous motor are provided, and the method includes: step 1: obtaining an approximate optimal direct axis (d-axis) current of a permanent magnet synchronous motor by using a loss model algorithm; step 2: performing, by using the approximate optimal d-axis current as an initial value and using a deep reinforcement learning algorithm, an optimizing process on the approximate optimal d-axis current to construct an optimal deep reinforcement learning model; and step 3: inputting currently acquired state data of the permanent magnet synchronous motor into the optimal deep reinforcement learning model to obtain a control parameter value corresponding to an optimal efficiency of the permanent magnet synchronous motor, and controlling the permanent magnet synchronous motor based on the control parameter value. Therefore, real-time target control for the permanent magnet synchronous motor is achieved.
    Type: Application
    Filed: August 30, 2023
    Publication date: December 21, 2023
    Inventors: Siqi Peng, Weijun Li, Dan Guo, Hongyu Peng, Hui Li, Pingan Tan