doi: 10.3934/dcdss.2020209

Vibration noise suppression algorithm of permanent magnet synchronous motor for new energy vehicles

School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China

* Corresponding author: Yong Chen

Received  March 2019 Revised  April 2019 Published  December 2019

Taking the permanent magnet synchronous motor for new energy vehicles as the research object, the causes and mechanisms of electromagnetic vibration noise of fractional-slot permanent magnet synchronous motor are analyzed and summarized. According to the analysis results, a new control strategy-hysteresis current tracking technology is proposed and applied to the three-level voltage source inverter (VSI) to achieve the purpose of suppressing torque ripple and reduce electromagnetic noise of permanent magnet synchronization caused by motor torque fluctuations. On the basis of the above, the band-stop filter method is introduced to quantitatively analyze the influence of controller parameters on the control effect. Based on the theoretical research of harmonic voltage and electromagnetic force, the finite element method is used to study the relationship among the initial phase angle, frequency and amplitude of the electromagnetic force and the injected harmonic voltage of the stator, and optimize the control parameters. The analysis and experimental results show that the error rate curve of the proposed algorithm is closer to the curve without phase noise when the phase noise line width is small. The vibration and noise can be effectively reduced by injecting the corresponding harmonic voltage with the optimization result.

Citation: Zizhen Qiu, Yong Chen, Yuming Guan, Yang Kang. Vibration noise suppression algorithm of permanent magnet synchronous motor for new energy vehicles. Discrete & Continuous Dynamical Systems - S, doi: 10.3934/dcdss.2020209
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show all references

References:
[1]

V. Awati and M. Jyoti, Homotopy analysis method for the solution of lubrication of a long porous slider, Applied Mathematics and Nonlinear Sciences, 1 (2016), 507-516.  doi: 10.21042/AMNS.2016.2.00040.  Google Scholar

[2]

M. Bie and W. Xiao, Ultra-wideband low phase noise dual mode lc voltage controlled oscillator design, Journal of China Academy of Electronics and Information Technology, 11 (2016), 383-387.   Google Scholar

[3]

B. ClaudioM. Marco and M. Paolo, Periodic controllers for vibration reduction using actively twisted blades, Aeronautical Journal, 120 (2016), 1763-1784.   Google Scholar

[4]

W. Gao and W. Wang, New isolated toughness condition for fractional (g, f, n) - critical graph, Colloquium Mathematicum, 147 (2017), 55-65.  doi: 10.4064/cm6713-8-2016.  Google Scholar

[5]

W. Gao and W. Wang, A tight neighborhood union condition on fractional (g, f, n', m)-critical deleted graphs, Colloquium Mathematicum, 149 (2017), 291-298.  doi: 10.4064/cm6959-8-2016.  Google Scholar

[6]

Y. GuanS. GaoH. LiuL. Jin and Y. Zhang, Vibration sensitivity reduction of micromachined tuning fork gyroscopes through stiffness match method with negative electrostatic spring effect, Sensors, 16 (2016), 1146.  doi: 10.3390/s16071146.  Google Scholar

[7]

S. Hattori, Vibration suppression control method for pmsms based on learning control corresponding to operating point changes, Ieej Transactions on Industry Applications, 137 (2017), 10-16.   Google Scholar

[8]

Q. Hu and J. Zhang, Attitude control and vibration suppression for flexible spacecraft using control moment gyroscopes, Journal of Aerospace Engineering, 29 (2016), 04015027.  doi: 10.1061/(ASCE)AS.1943-5525.0000513.  Google Scholar

[9]

J. Jin and W. Mi, An aimms-based decision-making model for optimizing the intelligent stowage of export containers in a single bay, Discrete and Continuous Dynamical Systems Series S, 12 (2019), 1101-1115.   Google Scholar

[10]

T. Kosaka, Noise and vibration reduction of sr motor, Journal of the Institute of Electrical Engineers of Japan, 137 (2017), 825-828.   Google Scholar

[11]

K. H. LeeJ. H. BakJ. L. Park and C. H. Lee, Vibration reduction of h/shaft using an electromagnetic damper with mode change, International Journal of Automotive Technology, 18 (2017), 255-261.  doi: 10.1007/s12239-017-0025-5.  Google Scholar

[12]

J. Q. LouY. P. ZhouJ. J. LiaoG. P. Li and Y. D. Wei, Armax model identification and vibration suppression of a piezoelectric flexible manipulator using optimal pole shifting control, Zhendong Gongcheng Xuebao/journal of Vibration Engineering, 31 (2018), 132-139.   Google Scholar

[13]

W. W. Luo, Median filtering method for suppressing high-density salt and pepper noise, Automation and Instrumentation, 4 (2016), 193-194.   Google Scholar

[14]

W. J. TianJ. Y. WangM. Li and Q. Cong, Design and optimization of vibration reduction structure imitating pore structure in goat capsula ungulae, Zhendong Gongcheng Xuebao/journal of Vibration Engineering, 31 (2018), 352-357.   Google Scholar

[15]

Q. WangK. RajashekaraY. Jia and J. Sun, A real-time vibration suppression strategy in electric vehicles, IEEE Transactions on Vehicular Technology, 66 (2017), 7722-7729.  doi: 10.1109/TVT.2017.2688416.  Google Scholar

[16]

S. S. WangM. Gong and Z. Song, Prediction of electromagnetic noise suppression effect of emi filter based on scattering parameter method, Journal of Electrotechnics, 31 (2016), 66-74.   Google Scholar

[17]

H. S. Ye, X. L. Chen and T. Zhou, e. al., Application of improving double-tree complex wavelet in white noise suppression of gis partial discharge monitoring, High Voltage Technology, 43 (2016), 851-858. Google Scholar

[18]

ŽiaranStanislav and O. Chlebo, Noise control transmission methods of the combustion engine by means of reduction of the vibration, Archives of Acoustics, 41 (2016), 277-284.   Google Scholar

Figure 1.  Effect before noise suppression
Figure 2.  Effect after noise suppression
Table 1.  Noise test results after rectification of motor
Test point Background noise's sound pressure $ L_{pi} $ Motor noise's sound pressure $ L'_{pi} $ Average background noise's sound pressure $ L''_{pi} $ Average sound pressure level $ L''_p $ Background noise's correction value $ K1 $ Surface sound pressure level $ L'_p $ Sound power level $ L_w $
1 19.3 56.5 19.98 56.72 0 56.72 64.5
2 20.2 55.1
3 21.5 56.4
4 19.2 57.5
5 19.5 57.8
Test point Background noise's sound pressure $ L_{pi} $ Motor noise's sound pressure $ L'_{pi} $ Average background noise's sound pressure $ L''_{pi} $ Average sound pressure level $ L''_p $ Background noise's correction value $ K1 $ Surface sound pressure level $ L'_p $ Sound power level $ L_w $
1 19.3 56.5 19.98 56.72 0 56.72 64.5
2 20.2 55.1
3 21.5 56.4
4 19.2 57.5
5 19.5 57.8
Table 2.  Armature parameter
Coercive force of the magnet H (KAm) Armature length L (mm) Coil number (N) Coil current I (A)
350 35 32 5
Coercive force of the magnet H (KAm) Armature length L (mm) Coil number (N) Coil current I (A)
350 35 32 5
Table 3.  Comparison results of operation efficiency of different methods
Number of experiments/(times) Operational efficiency/(%)
AQ BQ CQ
10 99.89 87.89 80.67
20 99.76 85.34 78.36
30 99.46 84.26 87.09
40 99.93 82.89 76.89
50 99.41 80.12 81.34
60 99.34 83.45 85.67
Number of experiments/(times) Operational efficiency/(%)
AQ BQ CQ
10 99.89 87.89 80.67
20 99.76 85.34 78.36
30 99.46 84.26 87.09
40 99.93 82.89 76.89
50 99.41 80.12 81.34
60 99.34 83.45 85.67
Table 4.  Comparison of error rate of different methods
Methods Error rate/(%)
AQ 0.0001
BQ 0.25
CQ 0.14
Methods Error rate/(%)
AQ 0.0001
BQ 0.25
CQ 0.14
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