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Parameters Estimation of a Tire Model Based on Julien’s Theory
Technical Paper
2017-36-0177
ISSN: 0148-7191,
e-ISSN: 2688-3627
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Abstract
This paper uses an inverse problem approach to estimate parameters of a tire model based on Julien’s Theory (JT). The modeling process of an all-wheel drive (AWD) vehicle is presented in this work, as well as JT and Pacejka’s Magic Formula (MF) tire models. Numerical simulations of the longitudinal vehicle dynamics, considering MF, provide pseudo-experimental data to the inverse problem. Particle Swarm Optimization (PSO), Random Restricted Window (R2W) and Differential Evolution (DE) are used to estimate the parameters of the JT tire model. Accuracy, computational time, efficiency and efficacy of the models are compared regarding the behavior of the performance responses of the vehicle. Throughout this process, Julien’s Theory is validated for use in future studies of vehicle dynamics.
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de Oliveira, A., Campos, C., Peralta, A., Neto, R. et al., "Parameters Estimation of a Tire Model Based on Julien’s Theory," SAE Technical Paper 2017-36-0177, 2017, https://doi.org/10.4271/2017-36-0177.Data Sets - Support Documents
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References
- Wong, Jo Yung. Theory of ground vehicles. John Wiley & Sons, 2008, ISBN 0-471-35461-9.
- Gruber, Patrick, and Sharp Robin S.. "Special issue on the 4th International Tyre Colloquium." Vehicle System Dynamics 54.4 (2016): 445-447, doi:10.1080/00423114.2016.1166599.
- Li, Bin, Yang Xiaobo, and Yang James. "Tire model application and parameter identification-A literature review." SAE International Journal of Passenger Cars-Mechanical Systems 7.2014-01-0872 (2014): 231-243, doi:10.4271/2014-01-0872.
- Gallrein, A., and Bäcker M.. "CDTire: a tire model for comfort and durability applications." Vehicle System Dynamics 45.S1 (2007): 69-77, doi:10.1080/00423110801931771.
- Bosch, Hans-Rudolf B., Hamersma Herman A., and Els P. Schalk. "Parameterisation, validation and implementation of an all-terrain SUV FTire tyre model." Journal of Terramechanics 67 (2016): 11-23, doi:10.1016.2016.06.001.
- Kuiper, E., and Van Oosten J. J. M.. "The PAC2002 advanced handling tire model." Vehicle system dynamics 45.S1 (2007): 153-167, doi:10.1080/00423110701773893.
- Jonson, Axel, and Olsson Eric. "A Methodology for Identification of Magic Formula Tire Model Parameters from In-Vehicle Measurements," Master’s Thesis, Department of Applied Mechanics, Gothenburg, Sweden, 2016.
- Alagappan, A. Vijay, Narasimha Rao KV, and Krishna Kumar R.. "A comparison of various algorithms to extract Magic Formula tyre model coefficients for vehicle dynamics simulations." Vehicle System Dynamics 53.2 (2015): 154-178, doi:10.1080/00423114.2014.984727.
- Talebitooti, R., and Torabi M.. "Identification of tire force characteristics using a Hybrid method." Applied Soft Computing 40 (2016): 70-85, doi:10.1016/j.asoc.2015.09.053.
- da Costa Neto, Ricardo Teixeira. "Modelagem e Integração dos Mecanismos de Suspensão e Direção de Veículos Terrestres Através do Fluxo de Potência," Ph.D. thesis, PUC-Rio, 2008.
- Colaço, Marcelo J., Orlande Helcio RB, and Dulikravich George S.. "Inverse and optimization problems in heat transfer." Journal of the Brazilian Society of Mechanical Sciences and Engineering 28.1 (2006): 1-24, doi:10.1590/S1678-58782006000100001.
- Poli, Riccardo, Kennedy James, and Blackwell Tim. "Particle swarm optimization." Swarm intelligence 1.1 (2007): 33-57, doi: 10.1007/s11721-007-0002-0.
- Alfi, Alireza, and Fateh Mohammad Mehdi. "Identification of nonlinear systems using modified particle swarm optimisation: a hydraulic suspension system." Vehicle System Dynamics 49.6 (2011): 871-887, doi:10.1080/00423114.2010.497842.
- Mr Kulkarni, Ninad K., et al. "Particle Swarm Optimization Applications to Mechanical Engineering-A Review." Materials Today: Proceedings 2.4-5 (2015): 2631-2639, doi:10.1016/j.matpr.2015.07.223.
- Drehmer, Luis Roberto Centeno, Paucar Casas Walter Jesus, and Gomes Herbert Martins. "Parameters optimisation of a vehicle suspension system using a particle swarm optimisation algorithm." Vehicle System Dynamics 53.4 (2015): 449-474, doi:10.1080/00423114.2014.1002503.
- Mohamed, Ali Wagdy. "Solving stochastic programming problems using new approach to Differential Evolution algorithm." Egyptian Informatics Journal (2016), doi:10.1016/j.eij.2016.09.002.
- Erdbrink, Christiaan D. "Identifying self-excited vibrations with evolutionary computing." Procedia Computer Science 29 (2014): 637-647, doi:10.1016/j.procs.2014.05.057.
- Ekinci, Yunus Levent, et al. "Model parameter estimations from residual gravity anomalies due to simple-shaped sources using Differential Evolution Algorithm." Journal of Applied Geophysics 129 (2016): 133-147, doi:10.1016/j.jappgeo.2016.03.040.
- Peñuñuri, F., et al. "A study of the Classical Differential Evolution control parameters." Swarm and Evolutionary Computation 26 (2016): 86-96, doi:10.1016/j.swevo.2015.08.003.
- Câmara, Leôncio Diógenes T., and Neto AJ Silva. "Inverse stochastic characterization of adsorption systems by a random restricted window (R2W) method." International Conference on Engineering Optimization (ENGOPT), ENGOPT. 2008.
- Bihain, Anderson Luís Jeske, Tavares Câmara Leôncio Diógenes, and Neto A. J. Silva. "Avaliação da rotina inversa R2W na estimação de parâmetros de transferência de massa no processo de adsorção de glicose e frutose." TEMA (São Carlos) 13.3 (2012): 277-289, doi:10.5540/TEMA.2012.013.03.277.
- Caldeira, Aldélio Bueno, da Costa Neto Ricardo Teixeira, and de Carvalho Michelle Soraia. "Inverse Stochastic Identification of Vehicle Suspension Damping Coefficients," 5th International Conference on Engineering Optimization, Brazil, 2016.