Abstract
Experimental testing for system backlash size relies on speed or displacement measurements of an isolated test apparatus but lack reference to engineered lash tolerances and expected values. These methods are prone to error when the measurement speed is not accounted for and hysteresis impacts the measurement. This study measures backlash on an experimental apparatus to update control model parameters. The results are also confirmed by comparing with analytical part tolerances based on CAE modeling. This is done by comparing three different test methods; output displacement only on a fixed-free apparatus, input torque with measured displacement on a fixed-free apparatus, and in-situ testing with torque and estimated displacement from rotating speed. The torque and displacement techniques recognize the influence of hysteresis and propose signal processing techniques to improve accuracy of the results. This signal processing technique was verified with an analytical model like those tested in the study. The three techniques used were all able to measure results within 31% of the CAE predictions when accounting for manufacturing tolerance. The signal processing method to account for hysteresis was analytically shown to have error less than 8.7% and 4.8% using an input frequency of <1 Hz with a sinusoidal and sawtooth forcing function respectively. The in-situ results were within 24% agreement of CAE projections without the need for a controlled laboratory test environment. These results showed that hysteresis should be accounted for when possible with an updated signal processing technique. The analytical model used to confirm backlash estimates with hysteresis also showed the need for controlled input forcing functions to improve the estimate accuracy. The study also confirms that experimental lash measurements can be collected from in-situ data when torque and displacement estimates are available.
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Abbreviations
- BLFH:
-
Bisecting Linear Fit Hysteresis
- CAD:
-
Computer Aided Design
- DOF:
-
Degree(s) of Freedom
- EKF:
-
Extended Kalman Filter
- FOM:
-
Full Order Model
- LPF:
-
Low Pass Filter
- LVDT:
-
Linear Variable Displacement Transducer
- POFs:
-
Polymer Optical Fibers
- ROM:
-
Reduced Order Model
- SALI:
-
Shifted Average Linear Intercept
- SDOF:
-
Single Degree of Freedom
- c n :
-
Negative Contact Damping (N Degree /s)
- c p :
-
Positive Contact Damping (N Degree /s)
- G :
-
Shear Modulus (Pa)
- I :
-
Polar Moment of Inertia (m4)
- J :
-
Mass Moment of Inertia (kg m2)
- k n :
-
Negative Contact Stiffness (N/ Degree)
- k p :
-
Positive Contact Stiffness (N/ Degree)
- L :
-
Length of Shaft (m)
- T :
-
Applied Contact Torque
- θ :
-
Angular Displacement (Degrees)
- θ 0 :
-
Initial Angular Displacement (Degrees)
- \(\dot{\theta}\) :
-
Angular Velocity (Degrees /s)
- \(\ddot{\theta}\) :
-
Angular Acceleration (Degrees /s2).
- δ lash :
-
System Lash (Degrees).
- δ measured :
-
Measured Lash (Degrees).
- τ :
-
Applied Torque (Nm).
References
Dogan SN, Ryborz J, Bertsche B (2006) Design of low-Noise Manual Automotive Transmissions. Proceedings of the Institution of Mechanical Engineers 220(2):79–95. https://doi.org/10.1243/14644193JMBD10
Liang M, Wang Y, Zhao T (2019) Optimization on nonlinear dynamics of gear rattle in automotive transmission system. Shock Vib 2019:12. https://doi.org/10.1155/2019/4056204
King RJ, Mull HR, Schlegel RG (1964) How to reduce gear noise (transmission gear noise reduction due to clashing gear teeth tolerances, tooth deflections, backlash and vibrations). Mach Des 36:134–142
Itoh M (2004) Suppression of transient vibration for geared mechanical system with backlash using model-based control. JSME International Journal, Series C: Mechanical Systems Machine Elements & Manufacturing 47(1):327–334
Baumann J, Torkzadeh DD, Ramstein A, Kiencke U 2004 Schleg T Model-Based Predictive Anti-Jerk Control. In: IFAC, Salerno, Elsevier, p 6
Hao D, Zhao C, Huang Y (2018) A reduced-order model for active suppression control of vehicle longitudinal low-frequency vibration. Shock Vib 2018:22. https://doi.org/10.1155/2018/5731347
Stokes A (1992) Gear handbook: design and calculations. Butterworth Heineman, Oxford
Shtipelman BA (1938) Design and manufacture of hypoid gears. Wiley, New York
Schjelderup HC (1967) A material hysteresis model for transient dynamic analysis. J Spacecr Rocket 4:541. https://doi.org/10.2514/3.28904
Liu F (2017) Dynamic analysis of drag torque for spur gear pairs considering the double-sided films. Proceedings of the Institution of Mechanical Engineers 231(12):2253–2262. https://doi.org/10.1177/0954406216631370
Wang L-s, Z-y H, Zheng K, G-w L (2014) Simulation and experiment on transmission gear rattle considering drag torque. Journal of Zhejiang University Engineering Science 48(5):911–916. https://doi.org/10.3785/j.issn.1008-973X.2014.05.023
Malonga Makosi CA, Rinderknecht S, Binz R, Uphaus F, Kirschbaum F (2017) Implementation of an open-loop controller to design the longitudinal vehicle dynamics in passenger cars
Lagerberg A, Egardt B (2007) Backlash estimation with application to automotive powertrains. IEEE Trans Control Syst Technol 15 (3). https://doi.org/10.1109/TCST.2007.894643
Dub M, Berka O, Lopot F, Starý F, Dynybyl V (2016) Torsional characteristics measurement of a gearbox. Appl Mech Mater 827:87–90. https://doi.org/10.4028/www.scientific.net/AMM.827.87
Nordin M, Bodin P, Gutman P-O (2001) New models and identification methods for backlash and gear play. Adaptive Control of Nonsmooth Dynamic Systems Springer, London
Stein JL, Wang C-H (1996) Automatic detection of clearance in mechanical systems: experimental VALIDATION. Mech Syst Signal Process 10(4):395–412. https://doi.org/10.1006/mssp.1996.0028
Peters K (2010) Polymer optical fiber sensors—a review. Smart Mater Struct 20(1):013002. https://doi.org/10.1088/0964-1726/20/1/013002
Tian XG, Tao XM (2001) Torsion measurement using fiber Bragg grating sensors. Exp Mech 41(3):248–253. https://doi.org/10.1007/BF02323141
Müller MS, Hoffmann L, Christopher Buck T, Walter Koch A (2009) Fiber Bragg grating-based force-torque sensor with six degrees of freedom. International Journal of Optomechatronics 3(3):201–214. https://doi.org/10.1080/15599610903144146
Fu S, Huang Y, Li X Experimental Study of Torque Measurement Based On FBG. In: Zhang B, Mu J, Wang W, Liang Q, Pi Y (eds) The Proceedings of the Second International Conference on Communications, Signal Processing, and Systems, Cham, 2014 2014. Springer International Publishing, pp 255–261
Xiong L, Guo Y, Jiang G, Zhou X, Jiang L, Liu H (2021) Six-dimensional force/torque sensor based on Fiber Bragg gratings with low coupling. IEEE Trans Ind Electron 68(5):4079–4089. https://doi.org/10.1109/TIE.2020.2982107
Leal-Junior AG, Frizera A, Marques C, Sánchez MRA, WMd S, AAG S, Segatto MV, Pontes MJ (2018) Polymer optical Fiber for angle and torque measurements of a series elastic Actuator’s spring. J Lightwave Technol 36(9):1698–1705. https://doi.org/10.1109/JLT.2017.2789192
Sánchez MRA, Leal-Junior AG, Segatto MEV, Marques CAF, dos Santos WM, Siqueira AAG, Frizera A (2018) Fiber Bragg grating-based sensor for torque and angle measurement in a series elastic actuator's spring. Appl Opt 57(27):7883–7890
Leal-Junior AG, Theodosiou A, Min R, Casas J, Díaz CR, Santos WMD, Pontes MJ, Siqueira AAG, Marques C, Kalli K, Frizera A (2019) Quasi-distributed torque and displacement sensing on a series elastic Actuator’s spring using FBG arrays inscribed in CYTOP fibers. IEEE Sensors J 19(11):4054–4061. https://doi.org/10.1109/JSEN.2019.2898722
Acknowledgements
The authors of this paper would like to thank their colleagues at Ford Motor Company for their continued financial support and technical expertise. We would like to individually recognize our colleagues Max Gibbs, Natalie Remisoski, Kalyan Addepalli, for their technical guidance, along with Cote Taylor for data collection in the development of this manuscript. The authors also would like to declare no conflict of interest in this manuscript relative to competitive vehicles and declare all processes and techniques to be applicable to most/all rotating machinery with lash coupling elements.
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Jon Furlich was the primary author whom collected data, post processed all data, wrote and edited the manuscript. Jason Blough, Darrell Robinette, and Natalie Remisoski mentored the data processing and manuscript editing. Cote Taylor collected and compiled test data for the manuscript.
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Furlich, J., Robinette, D., Blough, J. et al. Torque and Displacement Measurement with Enhanced Signal Processing for System Lash Estimation of a MDOF Rotating System. Exp Tech 46, 931–944 (2022). https://doi.org/10.1007/s40799-021-00524-7
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DOI: https://doi.org/10.1007/s40799-021-00524-7
Keywords
- Lash
- Experimental verification
- CAE Validation
- Rotating dynamics
- Automotive drivetrain