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Sensitivity Analysis of Simulated Postimpact Vehicle Motion Using Design of Experiments (DOE)
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 03, 2018 by SAE International in United States
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An important component of the process of the reconstruction of a vehicle crash involves the modeling of the motion of the vehicle(s) before and after a collision. Depending on the conditions, this motion might be modeled using a vehicle dynamics simulation program. In the simulated dynamics of vehicle motion, the tire forces are the predominant means by which the path of the vehicle is determined, with aerodynamic loads being the other force acting on the vehicle. Recent literature on this topic investigated the effect of the steer angle of the front wheels on the postimpact trajectory of a light vehicle for a large initial angular velocity. This paper looks more broadly at the modeling of light vehicle postimpact motion using vehicle dynamics simulation but for a wider range of factors.
Design of experiments (DOE) is used to rank the effect of various physical factors of vehicle postimpact motion. The response variable used in the DOE analysis uses the rest position of the vehicle (characterized by the x and y coordinates of the CG and the vehicle heading, θ) for a given combination of factor changes. The results of the study show that in the four different designs that were conducted, a trend in the response was consistent. The single factor that consistently appeared in the various DOE analyses (with various factor combinations) was the tire-to-roadway frictional drag coefficient. Various other factors and 2-factor combinations were also found to be significant. Some of the significant factors are not intuitively obvious, such as aerodynamic drag.
CitationBrach, R. and Capser, S., "Sensitivity Analysis of Simulated Postimpact Vehicle Motion Using Design of Experiments (DOE)," SAE Technical Paper 2018-01-0526, 2018, https://doi.org/10.4271/2018-01-0526.
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- Rose, N., Carter, N., and Beauchamp, G. , “Post-Impact Dynamics for Vehicle with High Yaw Velocity,” SAE Technical Paper 2016-01-1470, 2016, doi:10.4271/2016-01-1470.
- Brach, Raymond M. , “Design of Experiments and Parametric Sensitivity of Planar Impact Mechanics,” Presented at the 16th Annual EVU Congress, November 8-9 2007, Krakow, Poland.
- Brach, Raymond M. and Matthew Brach, R. , “Tire Models Used in Accident Reconstruction Vehicle Motion Simulation,” Presented at the 17th Annual EVU Congress, November 6-8 2008, Nice, France.
- Brach, R.M. and Matthew Brach, R. , “Tire Models for Vehicle Dynamic Simulation and Accident Reconstruction,” SAE Technical Paper 2009-01-0102 , 2009, doi:10.4271/2009-01-0102.
- Marimuthu, R., Jang, B., and Hong, S. , “A Study On SUV Parameters Sensitivity on Rollover Propensity,” SAE Technical Paper 2006-01-0795, 2006, doi: 10.4271/2006-01-0795.
- Kazemi, R. and Soltani, K. , “The Effects of Important Parameters on Vehicle Rollover with Sensitivity Analysis,” SAE Technical Paper 2003-01-0170, 2003, doi:10.4271/2003-01-0170.
- Heinrichs, B., Mac Giolla Ri, B., and Hunter, R. , “Sensitivity of Collision Simulation Results to Initial Assumptions,” SAE Int. J. Passenger Cars 5(2):807-832, 2012, doi:10.4271/2012-01-0604.
- Montgomery, Douglas C. “Design and Analysis of Experiments,” Eighth Edition, John Wiley & Sons, ISBN 978-1-118-14692-7, 2013.
- Guttman, I., S. Wilks and J. Hunter , Introductory Engineering Statistics, Third Edition, John Wiley & Sons, ISBN 0-471-07859-X, 1982.
- Biles, W. E. , “Experimental Design in Computer Simulation,” Proceedings of the Winter Simulation Conference, 1979, San Diego, CA, USA.
- Biles, W. E. , “Experimental Design in Computer Simulation,” Proceedings of the Winter Simulation Conference 1984, Dallas, TX, USA.
- Montevechi, J. A. B., Miranda, R. and Friend, J. D. , “Sensitivity Analysis in Discrete-Event Simulation Using Design of Experiments,” Chapter 3 of the book Discrete Event Simulations - Development and Applications, Eldin Wee Chuan Lim, Editor, ISBN 978-953-51-0741-5, InTech, September 9, 2012 (online publication).
- Brach, R.M. and Dunn, P.F. , “Uncertainty Analysis for Forensic Science,” Second Edition (Lawyers and Judges Publishers, 2009).
- Brach, R.M. , “Vehicle Dynamics Model for Simulation on a Microcomputer,” International Journal of Vehicle Design 12(4), 1991.
- Brach, R.M. and Brach, R.M. , “Modeling Combined Braking and Steering Tire Forces,” SAE Technical Paper 2000-01-0357, 2000, doi:10.4271/2000-01-0357.
- Cliff, W., Lawrence, J., Heinrichs, B., and Fricker, T. , “Yaw Testing of an Instrumented Vehicle with and without Braking,” SAE Technical Paper 2004-01-1187, 2004, doi:10.4271/2004-01-1187.
- Brach, Raymond M. and Matthew Brach, R., Vehicle Accident Analysis and Reconstruction Methods, Second Edition, Document R-397, SAE International, Warrendale, PA, 2011.
- Allen, R., Klyde, D., Rosenthal, T., and Smith, D. , “Estimation of Passenger Vehicle Inertial Properties and their Effect on Stability and Handling,” SAE Technical Paper 2003-01-0966, 2003, doi:10.4271/2003-01-0966.
- Daniel, C. , “Using Half-Normal Plots in Interpreting Factorial Two-Level Experiments,” Technometrics 1 (4, November), 1959.
- Expert Autostats , http://www.4n6xprt.com/4n6as.htm
- Fang, K.T., Li, R., and Sudjianto, A. , “Design and Modeling of Computer Experiments,” (Boca Raton, FL, Chapman & Hall/CRC, Taylor & Francis Group, 2006).