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Vehicle System Dynamics
International Journal of Vehicle Mechanics and Mobility
Volume 44, 2006 - Issue 9
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Original Articles

An easy procedure to determine Magic Formula parameters: a comparative study between the starting value optimization technique and the IMMa optimization algorithm

A. Ortiz Department of Mechanical Engineering, University of Málaga, Campus El Ejido, 29013, Málaga, SpainCorrespondence[email protected]
,
J. A. Cabrera Department of Mechanical Engineering, University of Málaga, Campus El Ejido, 29013, Málaga, Spain
,
A. J. Guerra Department of Mechanical Engineering, University of Málaga, Campus El Ejido, 29013, Málaga, Spain
&
A. Simon Department of Mechanical Engineering, University of Málaga, Campus El Ejido, 29013, Málaga, Spain
Pages 689-718 | Published online: 17 Feb 2007

Citations (22)

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Hyunsoo Cha, Jayu Kim, Kyongsu Yi & Jaeyong Park. (2023) Investigation into high-performance tire characteristics at the limits of handling. Vehicle System Dynamics 0:0, pages 1-20.
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Aleksandr Sakhnevych. (2022) Multiphysical MF-based tyre modelling and parametrisation for vehicle setup and control strategies optimisation. Vehicle System Dynamics 60:10, pages 3462-3483.
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A. Vijay Alagappan, K.V. Narasimha Rao & R. Krishna Kumar. (2015) A comparison of various algorithms to extract Magic Formula tyre model coefficients for vehicle dynamics simulations. Vehicle System Dynamics 53:2, pages 154-178.
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A. Ortiz, J. A. Cabrera, A. Guerra & A. Simon. (2009) The IMMa optimisation algorithm without control input parameters. Vehicle System Dynamics 47:2, pages 243-264.
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Articles from other publishers (18)

Milena Žunjić, Miroslav Demić, Branislav Rakićević & Branislav Đorđević. (2022) Contribution to the investigation of the influence of tire non-uniformity on the lateral tire characteristics. Journal of Applied Engineering Science 20:2, pages 562-570.
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Shilin Feng, Youqun Zhao, Huifan Deng, Qiuwei Wang & Tingting Chen. (2021) Parameter Identification of Magic Formula Tire Model Based on Fibonacci Tree Optimization Algorithm. Journal of Shanghai Jiaotong University (Science) 26:5, pages 647-657.
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Juqi Hu, Subhash Rakheja & Youmin Zhang. (2021) Tire–road friction coefficient estimation based on designed braking pressure pulse. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 235:7, pages 1876-1891.
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Wojciech Paszkowiak & Tomasz Bartkowiak. (2021) Dynamic model of a logistic train with different steering systems and tire models. Latin American Journal of Solids and Structures 18:1.
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Rui He, Corina Sandu & Javier E. Osorio. (2019) Systematic tests for study of tire tractive performance on soft soil: Part II – Parameterization of terramechanics model and tire model. Journal of Terramechanics 85, pages 77-88.
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Alberto López, José Luis Olazagoitia, Francisco Marzal & María Rosario Rubio. (2018) Optimal parameter estimation in semi-empirical tire models. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233:1, pages 73-87.
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Juan Cabrera, Juan Castillo, Javier Pérez, Juan Velasco, Antonio Guerra & Pedro Hernández. (2018) A Procedure for Determining Tire-Road Friction Characteristics Using a Modification of the Magic Formula Based on Experimental Results. Sensors 18:3, pages 896.
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Flavio Farroni, Raffaele Lamberti, Nicolò Mancinelli & Francesco Timpone. (2018) TRIP-ID: A tool for a smart and interactive identification of Magic Formula tyre model parameters from experimental data acquired on track or test rig. Mechanical Systems and Signal Processing 102, pages 1-22.
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Kay Massow & Ilja Radusch. (2018) A Rapid Prototyping Environment for Cooperative Advanced Driver Assistance Systems. Journal of Advanced Transportation 2018, pages 1-32.
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Zhun Cheng & Zhixiong Lu. (2017) Nonlinear Research and Efficient Parameter Identification of Magic Formula Tire Model. Mathematical Problems in Engineering 2017, pages 1-9.
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Andrius Ružinskas & Henrikas Sivilevičius. (2017) Magic Formula Tyre Model Application for a Tyre-Ice Interaction. Procedia Engineering 187, pages 335-341.
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Kay-Uwe Henning & Oliver Sawodny. (2016) Vehicle dynamics modelling and validation for online applications and controller synthesis. Mechatronics 39, pages 113-126.
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R. Talebitooti & M. Torabi. (2016) Identification of tire force characteristics using a Hybrid method. Applied Soft Computing 40, pages 70-85.
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Shahyar Taheri & Terence Wei. (2015) A New Semi-Empirical Method for Estimating Tire Combined Slip Forces and Moments during Handling Maneuvers. SAE International Journal of Passenger Cars - Mechanical Systems 8:2, pages 797-815.
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Alberto López, José Luis Olazagoitia, Cristina Moriano & Antonio Ortiz. (2014) Nonlinear optimization of a new polynomial tyre model. Nonlinear Dynamics 78:4, pages 2941-2958.
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Robert Tafner, Markus Reichhartinger & Martin Horn. (2014) Estimation of tire parameters via second-order sliding mode observers with unknown inputs. Estimation of tire parameters via second-order sliding mode observers with unknown inputs.
Abel A. Castro, Sergio L. Braga & Mauro S. Neto. Estimation of Dynamic Parameters of Ground Vehicles based on Genetic Algorithms. Estimation of Dynamic Parameters of Ground Vehicles based on Genetic Algorithms.
J. A. Cabrera, Antonio Ortiz, B. Estebanez, F. Nadal & A. Simon. (2009) A coevolutionary algorithm for tyre model parameters identification. Structural and Multidisciplinary Optimization 41:5, pages 749-763.
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