Advertisement

Identification of Torsional Vibration Modal Parameters: Application on a Ferrari Engine Crankshaft

  • Emilio Di LorenzoEmail author
  • Fabio Bianciardi
  • Simone Manzato
  • Simone Delvecchio
  • Claudio Manna
  • Karl Janssens
  • Bart Peeters
Conference paper
Part of the Applied Condition Monitoring book series (ACM, volume 15)

Abstract

Comfort plays a very important role in the development of cars. The pistons firing order of an internal combustion engine, by nature, do not generate a constant torque on the crankshaft. At specific crankshaft speed, where the engine’s excitation frequency and the driven-system’s natural frequency coincide, torsional vibrations can excite crankshaft resonances and other dynamic phenomena within the engine or further down the driveline, potentially leading to fatigue failure of the crankshaft, or to important NVH problems. In order to achieve very high standards, the behavior of the driveline system needs to be investigated. For this reason a technique named Torsional-Order Based Modal Analysis (T-OBMA) has been developed in order to identify the torsional resonance frequencies and their related damping ratios of driveline systems during operating conditions. The technique is based on the rotational speed measurements acquired in two or more points along the driveline. The modal parameters are identified from torsional orders measured during an engine speed runup. The technique has been validated in a simulation and in an industrial test environment identifying crankshaft modal parameters on a Ferrari engine.

Keywords

NVH Modal Analysis Order tracking Powertrain analysis Torsional vibrations 

References

  1. 1.
    Wu HL, Shao C, Feng ZD (1983) A study of the torsional vibration of automotive power trains. In: 2nd international pacific conference on automotive engineering, Tokyo, JapanGoogle Scholar
  2. 2.
    Reik W (1990) Torsional vibrations in the drive train of motor vehicles. In: 4th LuK international symposium, Baden-Baden, GermanyGoogle Scholar
  3. 3.
    Centea D, Rahnejat H, Menday MT (2001) Non-linear multi-body dynamic analysis for the study of clutch torsional vibrations. Appl Math Model 25(3):177–192CrossRefGoogle Scholar
  4. 4.
    Kushwaha M, Gupta S, Kelly P, Rahnejat H (2002) Elasto-multi-body dynamics of a multicylinder internal combustion engine. In: Proceedings of the institution of mechanical engineersGoogle Scholar
  5. 5.
    Rajendran S, Narasimhan MV (1997) Effect of inertia variation due to reciprocating parts and connecting rod on coupled vibration of crankshaft. J Eng Gas Turbines Power 119:257–264CrossRefGoogle Scholar
  6. 6.
    Janssens K, Kollar Z, Peeters B, Pauwels S, Van der Auweraer H (2006) Order-based resonance identification using operational PolyMAX. In: Proceedings of 24th international modal analysis conference, Saint Louis, MO, USGoogle Scholar
  7. 7.
    Blough J (1998) Improving the anaylsis of operating data on rotating automotive components. PhD thesis, University of Cincinnati, USGoogle Scholar
  8. 8.
    Peeters B, Van der Auweraer H, Vanhollebeke F, Guillaume P (2004) Operational modal analysis for estimating the dynamic properties of a stadium during a football game. Shock Vib 11:395–409CrossRefGoogle Scholar
  9. 9.
    Di Lorenzo E (2017) Operational modal analysis for rotating machines: challenges and solutions. PhD thesis, KU Leuven, Leuven, Belgium and University of Naples “Federico II”, Naples, ItalyGoogle Scholar
  10. 10.
    Colantoni C (2017) Characterization of torsional vibrations: torsional-order based modal analysis. Master thesis, University of Rome “La Sapienza”, Rome, ItalyGoogle Scholar
  11. 11.
    Di Lorenzo E, Colantoni C, Bianciardi F, Manzato S, Janssens K, Peeters B (2018) Characterization of torsional vibrations: torsional-order based modal analysis. In: Proceedings of 36th international modal analysis conference, Orlando, FL, USGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Emilio Di Lorenzo
    • 1
    Email author
  • Fabio Bianciardi
    • 1
  • Simone Manzato
    • 1
  • Simone Delvecchio
    • 2
  • Claudio Manna
    • 3
  • Karl Janssens
    • 1
  • Bart Peeters
    • 1
  1. 1.Siemens Industry Software NVLeuvenBelgium
  2. 2.NVH ConsultantFerraraItaly
  3. 3.Ferrari S.p.A.MaranelloItaly

Personalised recommendations