Design and Validation of an ABS and TCS Control Strategy Applied in an Automotive Simulator Using Model-Based Design Methodology

Authors

Keywords:

Automotive Control Systems, Automotive Simulator, ABS, TCS, Model-Based Design

Abstract

Automotive simulation tools have been employed in various areas of knowledge, especially in the production chain of the automotive industry. The main benefit of these tools consists of reducing the time and product development loops, which directly implies a reduced production cost and improved quality. Thus, the present study aims to use the VI-CarRealTime software widely used in the automotive industry to design and validate ABS and TCS automotive control systems using the ModelBased Design methodology. The simulation results show that the controllers meet the operating requirements well, showing a high correlation when compared to models of a complete vehicle for application in automotive simulators.

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Author Biographies

Igor Sales Bezerra Souza, Universidade de Brasília

Igor Sales Bezerra Souza received a B.S. degree (2023) in Automotive engineering from the University of Brasília, Brazil. He is currently working toward the M.S. degree with the University of Brasilia, Brasilia, Brazil. He is a Tire researcher at Automotive Research Center (ARC) from University of Brasília since 2021. His main research interests include tires, vehicle dynamics and vehicle control systems.

Lucas Torres, University of Brasília

Lucas Torres received the B.Sc. degree in automotive engineering from the University of Brasília, Brasília, Brazil, in 2022. He is currently working toward the M.S. degree with the University of Brasilia, Brasilia, Brazil. His current research interests include vehicle dynamics and electronic stability control systems.

André Murilo, University of Lavras

André Murilo holds a degree in Mechatronic Engineering from the Pontifical Catholic University of Minas Gerais (2001), a Master’s degree (2006), and a Ph.D. (2009) in Automatic Control from Grenoble INP, France. He is currently associate professor at the Federal University of Lavras, Department of Automatics. He has experience in the areas of Model Predictive Control, Automotive Control Systems, Nonlinear Systems, Robotics, Mechatronics, and Industrial Automation.

Rafael Rodrigues da Silva , University of Brasília

Rafael Rodrigues da Silva received from the University of Brasilia his B.S.degree in Automotive Enginer(2015) and his Master's degree in Mechatronics System (2017). He worked as an Engineer during 5 years in the automotive industry (OEM). He is currently an Assistant professor at the University of Brasilia. He has experience in the areas of ADAS, Automotive Electronics, Automotive Networks, Automotive Systems and Automotive Driving Simulators.

References

A. Ulsoy, H. Peng, and M. Cakmakci, Automotive Control Systems,

, DOI: 10.1017/CBO9780511844577.

W. F. Milliken and D. L. Milliken, Race Car Vehicle Dynamics, 1st ed.

Commonwealth Drive Warrendale, PA 15096-0001 U.S.A.: SAE

International, 1995.

T. Kelemenova, M. Kelemen, Mikov ´ a, V. Maxim, E. Prada, T. Lipt ´ ak, ´

and F. Menda, “Model based design and hil simulations,” American

Journal of Mechanical Engineering, vol. 1, pp. 276–281, 11 2013, DOI:

12691/ajme-1-7-25.

A. Forrai, Embedded Control System Design: A Model Based Approach,

ser. SpringerLink : Bucher. Springer Berlin Heidelberg, 2012, DOI: ¨

1007/978-3-642-28595-0.

V. grade GmbH, VI - CarRealTime 2021.3 Documentation, 2021.

Z. Wei and G. Xuexun, “An abs control strategy for commercial vehicle,”

IEEE ASME Transactions on Mechatronics, vol. 20, no. 1, pp. 384 –

, February 2015, DOI: 10.1109/TMECH.2014.2322629.

T. Sardarmehni, H. Rahmani, and M. Menhaj, “Robust control of wheel

slip in anti-lock brake system of automobiles,” Nonlinear Dyn, vol. 76,

pp. 125–139, november 2013, DOI: 10.1007/s11071-013-1115-1.

Y. Ma, J. Zhao, H. Zhao, C. Lu, and H. Chen, “Mpc-based slip ratio

control for electric vehicle considering road roughness,” IEEE Access,

April 2019, DOI: 10.1109/ACCESS.2019.2910891.

G. Liu and L. Jin, “A study of coordinated vehicle traction control

system based on optimal slip ratio algorithm,” Mathematical Problems

in Engineering, vol. 2016, June 2016, DOI: 10.1155/2016/3413624.

S. Rajendran, S. Spurgeon, G. Tsampardoukas, and R. Hampson, “Estimation of road frictional force and wheel slip for effective antilock

braking system (abs) control,” Int J Robust Nonlinear Control, vol. 29,

no. 1, pp. 736 – 765, September 2018, DOI: 10.1002/rnc.4366.

S. Saha and S. M. Amrr, “Design of slip-based traction control

system for ev and validation using co-simulation between adams

and matlab/simulink,” Simulation, vol. 96, no. 6, pp. 537–549, 2020.

[Online]. Available: https://doi.org/10.1177/0037549719897834

A. Shaout and S. Pattela, “Model based approach for automotive

embedded systems,” in 2021 22nd International Arab Conference on

Information Technology (ACIT), 2021, pp. 1–7.

B. R. Mudhivarthi, V. Saini, A. Dodia, P. Shah, and R. Sekhar, “Model

based design in automotive open system architecture,” in 2023 7th

International Conference on Intelligent Computing and Control Systems

(ICICCS), 2023, pp. 1211–1216.

A. S. Roque, D. F. Pohren, E. P. Freitas, and C. Pereira, “An approach

to address safety as non-functional requirements in distributed vehicular

control systems,” Journal of Control, Automation and Electrical Systems,

vol. 30, no. 5, pp. 700 – 715, 2019.

M. F. Abdullah, G. A. A. Qasem, M. F. Ramadhan, H. S.

Lim, C. P. Lee, and N. Alsakkaf, “Adaptive control techniques

for improving anti-lock braking system performance in diverse

friction scenarios,” International Journal of Electrical and Computer

Engineering, vol. 15, no. 1, pp. 260–279, 2025. [Online]. Available:

https://ijece.iaescore.com/index.php/IJECE/article/view/36455

Y. Zhang, Y. Wang, Y. Zhang, and Y. Wang, “A wheel slip

ratio constraint control for antilock braking system with external

interferences and state constraints,” Measurement and Control,

vol. 55, no. 9-10, pp. 1202–1210, 2022. [Online]. Available:

https://doi.org/10.1177/00202940221126177

S. Biju, A. Chammam, S. Askar, P. Rodrigues, and M. Jalalnezhad,

“Prediction-based controller radial neural network for the traction

control system,” Journal of Vibration and Control, 2024. [Online].

Available: https://doi.org/10.1177/10775463241296911

S. S. Vaezzadeh, M. M. Rahman, A. G. Chafjiri, and R. K.

Bradley, “A discrete event simulation model of compressive creep

for ldpe,” Results in Engineering, 2025. [Online]. Available: https:

//doi.org/10.1016/j.rineng.2025.103921

H. B. Pacejka, Tyre and Vehicle Dynamics, 2nd ed. Linacre House,

Jordan Hill, Oxford OX2 8DP: Butterworth-Heinemann, 2006, DOI:

1016/C2010-0-68548-8.

Adams, “Using the PAC2002 Tire Model,” online,

accessed 2/22/7, Feb 2022. [Online]. Available: https:

//help.hexagonmi.com/bundle/adams 2021.2/page/adams help/Adams

Car Package/tire/tire models pac2002/tire.models.pac2002.xhtml

Published

2025-06-12

How to Cite

Sales Bezerra Souza, I., Torres, L. ., Murilo, A., & Rodrigues da Silva , R. . (2025). Design and Validation of an ABS and TCS Control Strategy Applied in an Automotive Simulator Using Model-Based Design Methodology. IEEE Latin America Transactions, 23(7), 565–571. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/9517