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Investigation of Model-Based Multiphysics Analysis on Vibro-Acoustic Noise Sources Identification In Brushless DC Motor for Electric Vehicles

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Journal of Vibration Engineering & Technologies Aims and scope Submit manuscript

Abstract

Purpose

The brushless direct current motor is gaining attention due to its dynamic characteristics, such as high density, power, and efficiency, but the vibration and noise resonance levels are high during various real-time driving conditions.

Methods

This research describes a novel approach to analysing the various noise and vibration sources of the BLDC motor for electric vehicle applications. This study integrates model-based simulation and experimental analysis under real-time driving conditions. Further, various vibroacoustic noise sources are examined through transient model-based multiphysics analysis.

Results

From the experimental results, greater noise and vibration levels are observed at different frequencies of 265.6, 620.2, 750.4, 1170.2, 1510.3, and 1790.5 Hz of the BLDC motor due to the uneven electromagnetic forces. To verify the presence of experimental vibro-acoustic noise resonance levels at different frequencies, the model-based transient analysis is investigated. The simulation results reveal an identical trend in frequency levels compared to experimentation.

Conclusion

Finally, the overall observation of simulation and experimental results revealed that electromagnetic forces, load current changes, flux density, cogging torque fluctuations, etc. are the significant reasons for developing maximal vibro-acoustic noise amplitudes in the BLDC motor under different real-time driving conditions.

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Abbreviations

A:

Flux line distribution

AED:

ANSYS electronic desktop

B:

Magnetic flux intensity

B actual :

Actual magnetic flux

B required :

Required magnetic flux

BLDC Motor:

Brushless direct current motor

CT:

Cogging torque

DAC:

Data acquisition card

EM Forces:

Electromagnetic forces

EV:

Electric vehicle

FEA:

Finite element analysis

GHG Emissions:

Greenhouse gas emissions

HEV:

Hybrid electric vehicles

HIL:

Hardware in-loop simulation

ICE:

Internal combustion engine

IRPM:

Interior permanent magnet

L:

Self-inductance

M:

Mutual inductance

MIL:

Model in-loop simulation

NF:

Natural frequency

NVH:

Noise, vibration, and harshness

PM:

Permanent magnet

R:

Total resistance

Te :

Electromagnetic torque

References

  1. Qian K, Wang J, Gao Y, Sun Q, Liang J (2018) Interior noise and vibration prediction of permanent magnet synchronous motor. J Vibroeng 20(5):2225–2236

    Article  Google Scholar 

  2. Kudelina K, Asad B, Vaimann T, Belahcen A, Rassõlkin A, Kallaste A, Lukichev DV (2020) Bearing fault analysis of bldc motor for electric scooter application. Designs 4(4):42

    Article  Google Scholar 

  3. Panza MA (2015) A review of experimental techniques for NVH analysis on a commercial vehicle. Energy Procedia 1(82):1017–1023

    Article  Google Scholar 

  4. Lee HJ, Chung SU, Hwang SM (2008) Acoustic resonance of outer-rotor brushless dc motor for air-conditioner fan. J Appl Phys 103(7):07F116

    Article  Google Scholar 

  5. Mulla L, Khuba P, Dhere A, Palanivelu S (2019) Extraction of vibration behavior in conventional and electric drive two-wheeler using order analysis. In IOP Conference Series Mater Sci Eng 624(1):012009

    Article  Google Scholar 

  6. Song P, Li W, Mukundan S, Kar NC (2020) An overview of noise-vibration-harshness analysis for induction machines and permanent magnet synchronous machines. In 2020 10th International Electric Drives Production Conference (EDPC). IEEE, pp. 1–8

  7. Cho D-H, Kim K-J (1997) Modeling of electromagnetic excitation forces of and induction motor for vibration and noise analysis. Proc KSME Autumn A 18(2):372–377

    Google Scholar 

  8. Bi C, Jiang Q, Lin S, Low TS et al (2003) Reduction of acoustic noise in FDB spindle motors by using drive technology. IEEE Trans Magn 39(2):800–805

    Article  Google Scholar 

  9. Zhu Z, Howe D, Bolte E, Ackermann B (1993) Instantaneous magnetic field distribution in brushless permanent magnet dc motors, Part III: effect of stator slotting. IEEE Trans Magn 29:143–151

    Article  Google Scholar 

  10. Lee HJ, Chung SU, Hwang SM (2008) Noise source identification of a BLDC motor. J Mech Sci Technol 22(4):708–713

    Article  Google Scholar 

  11. Rahman B, Lieu D (1991) The origin of permanent magnet induced vibration in electric machines. ASME J Vib Acoust 113(4):476–481

    Article  Google Scholar 

  12. Gan C, Wu J, Sun Q, Kong W, Li H, Hu Y (2018) A review on machine topologies and control techniques for low-noise switched reluctance motors in electric vehicle applications. IEEE Access 16(6):31430–31443

    Article  Google Scholar 

  13. Bilgin B, Emadi A, Krishnamurthy M (2012) Design considerations for switched reluctance machines with a higher number of rotor poles. IEEE Trans Ind Electron 59(10):37453756

    Article  Google Scholar 

  14. Inderka RB, De Doncker RW (2003) High-dynamic direct average torque control for switched reluctance drives. IEEE Trans Ind Appl 39(4):1040–1045

    Article  Google Scholar 

  15. Sahoo NC, Xu JX, Panda SK (2001) Low torque ripple control of switched reluctance motors using iterative learning. IEEE Trans Energy Convers 16(4):318–326

    Article  Google Scholar 

  16. Uddin MN (2010) An adaptive-filter-based torque-ripple minimization of a fuzzy-logic controller for speed control of IPM motor drives. IEEE Trans Ind Appl 47(1):350–358

    Article  Google Scholar 

  17. Bao M, Chen EW, Lu YM, Liu ZS, Liu S (2014) Vibration and noise analysis for a motor of pure electric vehicle. Adv Mater Res Trans Tech Publications Ltd. 915:98–102

    Google Scholar 

  18. Lee HJ, Chung SU, Hwang SM (2008) Noise source identification of a BLDC motor. J Mech Sci Technol 22:708–713

    Article  Google Scholar 

  19. Król E, Maciążek M, Wolnik T (2023) Review of vibroacoustic analysis methods of electric vehicles motors. Energies 16(4):2041

    Article  Google Scholar 

  20. Jafarboland M, Farahabadi HB (2018) Optimum design of the stator parameters for noise and vibration reduction in BLDC motor. IET Electr Power Appl 12(9):1297–1305

    Article  Google Scholar 

  21. Im H, Yoo HH, Chung J (2011) Dynamic analysis of a BLDC motor with mechanical and electromagnetic interaction due to air gap variation. J Sound Vib 330(8):1680–1691

    Article  Google Scholar 

  22. Mahadevan U, Kumar V, Sambharam T (2021) A multiphysics approach for NVH analysis of PMSM traction motor. SAE Technical Paper

  23. Florentin J, Durieux F, Kuriyama Y, Yamamoto T (2011) Electric motor noise in a lightweight steel vehicle. SAE Technical Paper

  24. Parida MR, Karthik KT, Vavilapalli K (2022) Reduction of Vibration & Noise in Permanent Magnet Motor. SAE Technical Paper

  25. Sumega M, Zoššák Š, Varecha P, Rafajdus P (2019) Sources of torque ripple and their influence in BLDC motor drives. Transport Res Procedia 1(40):519–526

    Article  Google Scholar 

  26. Mohanraj D, Aruldavid R, Verma R, Sathiyasekar K, Barnawi AB, Chokkalingam B, Mihet-Popa L (2022) A review of BLDC motor: state of art, advanced control techniques, and applications. IEEE Access 13(10):54833–54869

    Article  Google Scholar 

  27. Pindoriya RM, Thakur RK, Rajpurohit BS, Kumar R (2021) Numerical and experimental analysis of torsional vibration and acoustic noise of PMSM coupled with DC generator. IEEE Trans Industr Electron 69(4):3345–3356

    Article  Google Scholar 

  28. Podhajecki J, Rawicki S (2019) Numerical and experimental vibration analysis of BLDC motor. In: 2019 19th international symposium on electromagnetic fields in mechatronics, electrical and electronic engineering (ISEF). IEEE, pp. 1–2

  29. Lu S, Zhou P, Wang X, Liu Y, Liu F, Zhao J (2018) Condition monitoring and fault diagnosis of motor bearings using under sampled vibration signals from a wireless sensor network. J Sound Vib 3(414):81–96

    Article  Google Scholar 

  30. Cavagnino A, Saied S, Vaschetto S (2013) Experimental identification and reduction of acoustic noise in small brushed DC motors. IEEE Trans Ind Appl 50(1):317–326

    Article  Google Scholar 

  31. Vuddanti S, Shastri S, Salkuti SR (2022) Design of permanent magnet brushless DC motor for electric vehicle traction application. In Recent Advances in Power Electronics and Drives: Select Proceedings of EPREC 2021. Springer Nature Singapore, Singapore, pp. 317–333

  32. Patil SV, Saxena R (2022) Design & Simulation of Brushless DC Motor Using ANSYS for EV Application. In2022 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS). IEEE, pp. 1–5

  33. Hasan MK, Verma Y, Sharan P, Manna MS, Islam S (2022) Design and analysis of outer rotor brushless dc motor for robotics using ansys maxwell software. In: New trends and applications in internet of things (IoT) and big data analytics. Springer International Publishing, Cham, pp 93-107

  34. Mithunraj MK, Warrier GS, Pathivil P, Kanagalakshmi S, Archana R (2019) Design and performance analysis of brushless DC motor using ANSYS Maxwell. In: 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), Kannur, India 1:1049–1053

  35. Wang Y, Gao H, Wang H, Ma W (2020) NVH optimization analysis of permanent magnet synchronous motor by rotor slotting. Vehicles 2(2):287–302

    Article  Google Scholar 

  36. Karunakaran V, KandadaiNagaratnam S (2022) Electromagnetic, vibration and thermal analysis of 1.1 kw switched reluctance motor for electric vehicle application. J Electric Eng Technol. https://doi.org/10.1007/s42835-022-01318-6

    Article  Google Scholar 

  37. Gadewar SV, Jain AM (2017) Modelling and simulation of three phase BLDC motor for electric braking using MATLAB/Simulink. Int J Electric Electron Data Commun 5(7):48–53

    Google Scholar 

  38. Ubare P, Ingole D, Sonawane D (2019) Energy-efficient nonlinear model predictive control of bldc motor in electric vehicles. In: 2019 Sixth Indian Control Conference (ICC). IEEE, pp. 194–199

  39. Feng H, Zhang S, Wei J, Xu X, Gao C, Ai L (2022) Torque ripple reduction of brushless DC motor with convex arc-type permanent magnets based on robust optimization design. IET Electr Power Appl 16(5):565–574

    Article  Google Scholar 

  40. Rideout DG, Ghasemloonia A, Arvani F, Butt SD (2015) An intuitive and efficient approach to integrated modelling and control of three-dimensional vibration in long shafts. Int J Simul Process Model 10(2):163–178

    Article  Google Scholar 

  41. Poovizhi M, Kumaran MS, Ragul P, Priyadarshini LI, Logambal R (2017) Investigation of mathematical modelling of brushless dc motor (BLDC) drives by using MATLAB-SIMULINK. In: 2017 International Conference on Power and Embedded Drive Control (ICPEDC). IEEE, pp. 178–183

  42. Cho S, Hwang J, Kim CW (2018) A study on vibration characteristics of brushless dc motor by electromagnetic-structural coupled analysis using entire finite element model. IEEE Trans Energy Convers 33(4):1712–1718

    Article  Google Scholar 

  43. Tosun O, Serteller NF (2022) The design of the outer-rotor brushless dc motor and an investigation of motor axial-length-to-pole-pitch ratio. Sustainability 14(19):12743

    Article  Google Scholar 

  44. Aishwarya M, Brisilla RM (2022) Design of energy-efficient induction motor using ANSYS software. Results Eng 1(16):100616

    Article  Google Scholar 

  45. Jianjun L, Yongxiang X, Jibin Z (2008) A study on the reduction of vibration and acoustic noise for brushless DC motor. In: 2008 International Conference on Electrical Machines and Systems. IEEE, pp. 561–563

  46. Hur J, Reu JW, Kim BW, Kang GH (2011) Vibration reduction of IPM-type BLDC motor using negative third harmonic elimination method of air-gap flux density. IEEE Trans Ind Appl 47(3):1300–1309

    Article  Google Scholar 

  47. Yadghar A, Ketabi A, Navardi MJ, Mokhtari M (2016) A geometry optimization of fundamental characteristics of a brushless DC motor using FEM and evolutionary algorithms. J Electr Eng Electron Technol 5:1–2

    Google Scholar 

  48. Le Besnerais J, Souron Q, Devillers E (2016) Analysis of the electromagnetic acoustic noise and vibrations of a high-speed brushless DC motor. In: 8th IET International Conference on Power Electronics, Machines and Drives (PEMD 2016). IET, pp. 1-10

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Acknowledgements

The authors would like to thank the Management of Vellore Institute of Technology, Vellore for the facilities provided during the execution of this work. This research is supported by the funding from Royal Academy of Engineering, United Kingdom (Grant No: DIA-2022-150 & TSP-2325-5-IN/172).

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  1. School of Mechanical Engineering, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India

    Pemmareddy Saiteja & Bragadeshwaran Ashok

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  1. Pemmareddy Saiteja
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Correspondence to Bragadeshwaran Ashok.

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Saiteja, P., Ashok, B. Investigation of Model-Based Multiphysics Analysis on Vibro-Acoustic Noise Sources Identification In Brushless DC Motor for Electric Vehicles. J. Vib. Eng. Technol. (2023). https://doi.org/10.1007/s42417-023-01208-9

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