Diagnosing and Reducing Noise and Vibration in Automotive DC Motors with Time Synchronous Averaging
Source abstract
Abstract
This study explores the application of Time Synchronous Averaging (TSA) for diagnosing Noise, Vibration, and Harshness (NVH) characteristics in an automotive sunroof assembly powered by a Direct Current (DC) motor. TSA is an advanced signal-processing technique that isolates periodic signals from noise, enhancing fault detection. The research identifies rotor misalignment as the dominant cause of excessive NVH. To address this, an experimental modification to the motor’s end washer was implemented, resulting in a significant reduction in vibration amplitudes at upper harmonics. These findings demonstrate TSA’s effectiveness in optimizing NVH characteristics for smaller rotating systems and demonstrate an effective approach for optimizing NVH performance in small-scale rotating systems, particularly in automotive applications.
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Research context
OpenAlex topics: Control Systems in Engineering · Machine Fault Diagnosis Techniques · Sensorless Control of Electric Motors
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Applied Mechanics and Mechatronics, Faculty of Mechanical Engineering, Slovak University of Technology, Námestie Slobody 2910/17, 812 31 Bratislava, Slovakia
Funding
Ministry of Education, Science, Research and Sport of the Slovak Republic
References (33)
Show source-provided references
1. Shinde, G.J., Rajamanickam, R., Karanth, N.V., and Pande, D.W. (2017). Quantification of NVH Parameters in DC Electric Motors Used for Automobile Application, SAE International.10.4271/2017-26-0209 ↗
2. The Study of DC Motor Noise and Vibration
3. Noise and Vibration Modeling of Permanent Magnet Synchronous Motors: A Review10.1109/TTE.2024.3365151 ↗
4. Gieras, J., Wang, C., and Lai, J. (2005). Noise of Polyphase Electric Motors, CRC Press.
5. Cho, Y. (2018). Characterizing Sources of Small DC Motor Noise and Vibration. Micromachines, 9.10.3390/mi9020084 ↗
6. Optimum design of the stator parameters for noise and vibration reduction in BLDC motor10.1049/iet-epa.2017.0691 ↗
7. Pindoriya, R.M., Mishra, A.K., Rajpurohit, B.S., and Kumar, R. (2018, January 5–10). An Analysis of Vibration and Acoustic Noise of BLDC Motor Drive. Proceedings of the 2018 IEEE Power & Energy Society General Meeting (PESGM), Portland, OR, USA.10.1109/PESGM.2018.8585750 ↗
8. Jin, C.-S., Kim, C.-M., Kim, I.-J., and Jang, I. (2021). Proposed Commutation Method for Performance Improvement of Brushless DC Motor. Energies, 14.10.3390/en14196023 ↗
9. Reduction of Magnetically Induced Vibration of a Spoke-Type IPM Motor Using Magnetomechanical Coupled Analysis and Optimization10.1109/TMAG.2013.2255307 ↗
10. Optimization Techniques for Cogging Torque Reduction and Thermal Characterization in Brushless DC Motor10.1007/s40998-024-00699-w ↗
11. Vibration Reduction of IPM-Type BLDC Motor Using Negative Third Harmonic Elimination Method of Air-Gap Flux Density10.1109/TIA.2011.2128850 ↗
12. Kim, H., Kim, J., Han, K., and Won, D. (2022). 1D Modeling Considering Noise and Vibration of Vehicle Window Brushed DC Motor. Appl. Sci., 12.10.3390/app122211405 ↗
13. Simulation of the Noise Radiated by an Automotive Electric Motor: Influence of the Motor Defects10.4271/2014-01-2070 ↗
14. Pfliegel, P., Augusztinovicz, F., and Granát, J. (2000, January 13–15). Noise Analysis and Noise Reduction of Small DC Motors. Proceedings of the 25th International Conference on Noise and Vibration Engineering (ISMA 2000), KU Leuven, Belgium.
15. Iorgulescu, M., Magdalena, A., and Beloiu, R. (2012, January 24–26). Noise and vibration monitoring for diagnosis of DC motor’s faults. Proceedings of the 13th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), Brasov, Romania.10.1109/OPTIM.2012.6231919 ↗
16. Time Synchronous Averaging Based on Cross-power Spectrum10.1186/s10033-023-00867-9 ↗
17. The synchronous (time domain) average revisited10.1016/j.ymssp.2010.07.016 ↗
18. A carrier wave extraction method for cavitation characterization based on time synchronous average and time-frequency analysis10.1016/j.jsv.2020.115682 ↗
19. Nguyen, T.-D., Nguyen, H.-C., Nguyen, V.-M., and Nguyen, P.-D. (2024). Tacholess Time Synchronous Averaging for Gear Fault Diagnosis in Wind Turbine Gearboxes Using a Single Accelerometer. Machines, 12.10.3390/machines12060424 ↗
20. Hu, L., Xu, Y., Gu, F., He, J., Hu, N., and Ball, A. (2019). Autocorrelation Ensemble Average of Larger Amplitude Impact Transients for the Fault Diagnosis of Rolling Element Bearings. Energies, 12.10.3390/en12244740 ↗
21. Time-synchronous-averaging of gear-meshing-vibration transducer responses for elimination of harmonic contributions from the mating gear and the gear pair10.1016/j.ymssp.2015.03.006 ↗
22. Analysis of vibration signals and detection for multiple tooth cracks in spur gearboxes10.1016/j.ymssp.2022.109780 ↗
23. Development of crack induced impulse-based condition indicators for early tooth crack severity assessment10.1016/j.ymssp.2021.108327 ↗
24. An Envelope Time Synchronous Averaging for Wind Turbine Gearbox Fault Diagnosis10.1007/s42417-023-01267-y ↗
25. Vibration analysis of planet gear bore-rim failure using enhanced planet time synchronous averaging10.1016/j.engfailanal.2020.104942 ↗
26. Inyang, U., Petrunin, I., and Jennions, I. (2023). Diagnosis of Multiple Faults in Rotating Machinery Using Ensemble Learning. Sensors, 23.10.3390/s23021005 ↗
27. Period-refined CYCBD using time synchronous averaging for the feature extraction of bearing fault under heavy noise10.1177/14759217231181514 ↗
28. Farhat, M.H., Chiementin, X., Chaari, F., Bolaers, F., and Haddar, M. (2021, January 25–26). Time Synchronous Averaging Based Detection of Bearing Defects. Proceedings of the Modelling and Simulation of Complex Systems for Sustainable Energy Efficiency, online.10.1007/978-3-030-85584-0_23 ↗
29. Boychuk, I., and Grinek, A. (2021, January 10–12). Experimental studies of single rotors noise of small scale. Proceedings of the International Conference on Actual Issues of Mechanical Engineering (AIME 2021), Ahmedabad, India.
30. A revisit of the tonal noise of small rotors
31. NASA Langley Research Center, Zawodny, N.S., Boyd, D.D., and Burley, C.L. (2016, January 16–19). Acoustic Characterization and Prediction of Representative, Small-Scale Rotary-Wing Unmanned Aircraft System Components. Proceedings of the Vertical Flight Society 72nd Annual Forum & Technology Display, West Palm Beach, FL, USA.
32. Similitude method for self-noise under boundary layer pressure fluctuation excitation10.1121/10.0021169 ↗
33. Vance, J. (1988). Rotordynamics of Turbomachinery, Wiley, Wiley-Interscience.