Roll Mode Change Due to Vehicle Speed and Its Effect on Yaw Natural Frequency

  • Hideki SakaiEmail author
Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)


This paper classifies roll resonance into two kinds, and points out symbolic solutions of yaw natural frequency at each roll resonance. Firstly, this paper consider change of roll natural frequency ωx due to change of vehicle speed V. This paper points out that ωx is a roll mode around the roll axis on the low speed side, and a roll mode around the center of gravity on the high speed side. Furthermore, we define V of this boundary as Vb; Vb is a V where ωx and yaw resonance frequency ωn coincide. In addition, Vb of passenger cars is estimated to be about 90 [km/h]. Furthermore, this paper considers an influence of ωx change on ωn. As the reference for this consideration, we use the yaw resonance frequency ωn0 of well-known planar 2 DOF model. In the domain of V < Vb, this paper points out that ωn is about 1.3 times ωn0 and derives a symbolic solution of this ωn. On the other hand, this paper also points out that ωn is almost equal to w0 in the region of V > Vb. Strictly speaking, this ωn is slightly larger than ωn0, which corresponds to the symbolic solution that the author pointed out in the past.


Roll Yaw Natural frequency Roll axis 


  1. 1.
    Sakai, H.: Prediction of yaw natural frequency taking roll motion into account. In: Proceedings of the 25th IAVSD Symposium on Dynamics of Vehicles on Roads and Tracks, vol. 1, pp. 116–126 (2018)Google Scholar
  2. 2.
    Fujioka, T.: Unicycle model on the cross-sectional plane and its dynamic character -fundamental analysis of roll motion by use of Segel’s model. Proc. JSAE 91(10), 19–24 (2010)Google Scholar
  3. 3.
    Ellis, R.: Vehicle Dynamics. Business Books, London (1969)Google Scholar
  4. 4.
    Sakai, H.: A study on change of roll natural frequency. Trans. of JSAE 46(2), 385–391 (2015)Google Scholar

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Authors and Affiliations

  1. 1.Kindai UniversityHigashihiroshimaJapan

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