Recreation of service loads using strain gauges of speed shifting lever

  • S. H. GawandeEmail author
  • A. A. Keste
  • S. G. Savadatti
Technical Paper


Every structure components on the vehicle undergo varying sizes of loads during the course of their estimated life. The conventional method of load application used in finite element analysis (FEA) considers either the factor of safety or often scale up/down the existing loading condition according to the modified design. This kind of assumptions makes the design either redundant or fragile. In this scenario, it is very much necessary for developing ‘optimal’ loading methodology in design. This paper suggests the methodology to determine the moderate FEA loads using experimental test strains. This methodology uses the experimental test strain data to determine FEA loads also. In turn, it eliminates the complicated instrumentation like accommodating the load cells and their calibration. This paper discusses the FEA load prediction on speed shifting lever.


Finite element analysis Strain gauges Service loads Speed shifting lever 



This work is not supported fully or partially by any funding organization or agency.

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interests regarding the publication of this paper.


  1. 1.
    Rathanraj KJ, Srividya A, Mannikar AV (2009) Extrapolation of service load data. SAE paper no. 2009-01-1619Google Scholar
  2. 2.
    da Luz DK, Gertz LC, Cervieri A, AFA Rodrigues (2010) Project of load cell for dynamometer. SAE paper no. 2010-36-0285Google Scholar
  3. 3.
    Potts GR, Knuth EF (2001) Dynamic force measurement system (DFMS) for tires. SAE paper no. 2001-01-0790Google Scholar
  4. 4.
    Conle FA, Chernenkoff RA, Zhang Y, Chu C, Barrie W (2002) Using superposition to calculate critical location stress, strain and life in vehicular transmission shafts of complex geometry subjected to bending and torsion. SAE paper no. 2002-01-1302Google Scholar
  5. 5.
    Backer M, Langthaler T, Olbrich M, Oppermann H (2005) The hybrid road approach for durability loads prediction. SAE paper no. 2005-01-0628Google Scholar
  6. 6.
    Gordon T, Mitra M (2013) Dynamic load estimation for heavy trucks on bridge structures. SAE paper no. 2013-01-0626Google Scholar
  7. 7.
    Baseski I, Norman K, Stahara RD (2015) Suspension and mass parameter measurements of wheeled vehicles. SAE paper no. 2015-01-2751Google Scholar
  8. 8.
    Cloix A, Wojtowicki JL (2016) Relevance of inverse method to characterize structure borne noise sources: application on an industrial case and comparison with a direct method. SAE paper no. 2016-01-1796Google Scholar
  9. 9.
    Fukagawa T, Shimokawa S, Itakura E, Nakatani H, Kitahama K (2016) Modeling of transient aerodynamic forces based on crosswind test. SAE paper no. 2016-01-1577Google Scholar
  10. 10.
    Taheri S, Wei T (2015) A new semi-empirical method for estimating tire combined slip forces and moments during handling maneuvers. SAE paper no. 2015-01-9112Google Scholar
  11. 11.
    Guo M, Zhang W, Zhang D, Bhandarkar R (2015) A technique for cargo box tailgate CAE fatigue life predictions loaded with inertial forces and moments. SAE paper no. 2015-01-0532Google Scholar
  12. 12.
    Kim J, Kim S (2013) Estimation of lateral tire force from objective measurement data for handling analysis. SAE paper no. 2013-01-0060Google Scholar
  13. 13.
    Sawa N, Nimiya Y, Kubota Y, Itsubo T, Honma K (2010) Fatigue life prediction on rough road using full vehicle co-simulation model with suspension control. SAE paper no. 2010-01-0952Google Scholar
  14. 14.
    Gobbi M, Guarneri P, Mastinu G, Rocca G, Castignani L (2010) A method for vibration and harshness analysis based on indoor testing of automotive suspension systems. SAE paper no. 2010-01-0639Google Scholar
  15. 15.
    Tsujiuchi N, Koizumi T, Matsubara M, Moriguchi K, Shima I (2009) Prediction of spindle force using measured road forces on rolling tire. SAE paper no. 2009-01-2107Google Scholar
  16. 16.
    Gobbi M, Guarneri P, Mastinu G, Rocca G (2008) Test rig for characterization of automotive suspension systems. SAE paper no. 2008-01-0692Google Scholar
  17. 17.
    Pexa M, Muller M, Hloch S (2017) Dynamic measuring of performance parameters for vehicles engines. Measurements 3(6):1778–1785Google Scholar
  18. 18.
    Sert E, Boyraz P (2017) Optimization of suspension system and sensitivity analysis for improvement of stability in a midsize heavy vehicle. Eng Sci Technol Int J 20(3):997–1012CrossRefGoogle Scholar
  19. 19.
    Trzciński G, Moskalik T, Wojtan R (2017) Total weight and axle loads of truck units in the transport of timber depending on the timber cargo. Forests-09-00164, 2017,9,164, MDPI, pp 1–13Google Scholar
  20. 20.
    Jacob B, La Beaumelle VF (2010) Improving truck safety: potential of weigh-in-motion technology. IATSS Res 34:9–15CrossRefGoogle Scholar
  21. 21.
    Aeran A, Siriwardane SC, Mikkelsen O, Langen I (2017) A new nonlinear fatigue damage model based only on S-N curve parameters. Int J Fatigue 103:327–341CrossRefGoogle Scholar

Copyright information

© The Brazilian Society of Mechanical Sciences and Engineering 2019

Authors and Affiliations

  • S. H. Gawande
    • 1
    Email author
  • A. A. Keste
    • 1
  • S. G. Savadatti
    • 1
  1. 1.Department of Mechanical Engineering, M. E. S. College of Engineering, PuneS. P. Pune UniversityPuneIndia

Personalised recommendations