Torque Ripple Reduction Based on Adaptive-Linear-Neuron Algorithm Caused by Offset Errors of Current Measurement

The current offset errors has negative influence on the accurate current control-the output electromagnetic torque will oscillate at the fundamental frequency. Therefore, a method based on adaptive-linear- neuron algorithm is proposed to extract the useful dc component of the feedback and neglect th...

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Bibliographic Details
Published inInternational Conference on Electrical Machines and Systems (Online) pp. 1 - 5
Main Authors Zhang, Wentao, Huang, Huidong, Xu, Yongxiang, Zou, Jibin
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2019
Subjects
adaptive-linear-neuron algorithm
Current measurement
Current offset error
Frequency control
Harmonic analysis
harmonic decomposition
Heuristic algorithms
Motors
Neurons
Noise
Rotors
Torque
Torque measurement
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ISSN2642-5513
DOI10.1109/ICEMS.2019.8922547

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Summary:The current offset errors has negative influence on the accurate current control-the output electromagnetic torque will oscillate at the fundamental frequency. Therefore, a method based on adaptive-linear- neuron algorithm is proposed to extract the useful dc component of the feedback and neglect the noise signal. Two current harmonic decomposers are utilized to obtain the current of d axis and q axis separately. The proposed method covers no additional hardware circuits and does not rely on the motor parameters. The experimental results are provided to verify the effectiveness of the proposed method.
ISSN:2642-5513
DOI:10.1109/ICEMS.2019.8922547