TY - GEN
T1 - Research on Torque Ripple Suppression Based on RNN Neural Network Amplitude Optimization of Pulsating Injection
AU - Yu, Zhuoming
AU - Chen, Zhen
AU - Mao, Xuefei
N1 - Publisher Copyright:
© Beijing Paike Culture Commu. Co., Ltd. 2026.
PY - 2026
Y1 - 2026
N2 - The high-frequency square-wave injection approach is frequently utilized for rotor position estimation in IPMSMs operating without position sensors, particularly under low or zero speed conditions. To mitigate torque ripple induced by high-frequency excitation, this work develops an adaptive scheme that continuously adjusts injection amplitude in closed-loop systems via a Recurrent Neural Network. In this method, the RNN adjusts the injection amplitude based on d-axis current data and position error details, ensuring accurate position extraction while effectively reducing current harmonics and torque ripple. Simulation results demonstrate that compared to traditional fixed-amplitude injection methods, while ensuring the position tracking accuracy, the peak-to-peak value of torque ripple and the THD drop of current are reduced by 24.93% and 46.24% respectively.
AB - The high-frequency square-wave injection approach is frequently utilized for rotor position estimation in IPMSMs operating without position sensors, particularly under low or zero speed conditions. To mitigate torque ripple induced by high-frequency excitation, this work develops an adaptive scheme that continuously adjusts injection amplitude in closed-loop systems via a Recurrent Neural Network. In this method, the RNN adjusts the injection amplitude based on d-axis current data and position error details, ensuring accurate position extraction while effectively reducing current harmonics and torque ripple. Simulation results demonstrate that compared to traditional fixed-amplitude injection methods, while ensuring the position tracking accuracy, the peak-to-peak value of torque ripple and the THD drop of current are reduced by 24.93% and 46.24% respectively.
KW - Amplitude Optimization
KW - High-Frequency Injection Method
KW - Recurrent Neural Network
KW - Sensorless Control
UR - https://www.scopus.com/pages/publications/105028158421
U2 - 10.1007/978-981-95-4282-6_33
DO - 10.1007/978-981-95-4282-6_33
M3 - Conference contribution
AN - SCOPUS:105028158421
SN - 9789819542819
T3 - Lecture Notes in Electrical Engineering
SP - 283
EP - 295
BT - The Proceedings of the 12th Frontier Academic Forum of Electrical Engineering (FAFEE2025) - Volume IV
A2 - Yang, Qingxin
PB - Springer Science and Business Media Deutschland GmbH
T2 - 12th Frontier Academic Forum of Electrical Engineering, FAFEE 2025
Y2 - 23 May 2025 through 25 May 2025
ER -