Skip to main content

Thermo-mechanical coupled analysis based design of ventilated brake disc using genetic algorithm and particle swarm optimization

JMST Advances volume 3, pages 41–54 (2021)Cite this article

Abstract

The brake discs are subjected to thermal load due to sliding by the brake pad and fluctuating loads because of the braking load. This combined loading problem requires simulation using coupled thermo-mechanical analysis for design evaluation. This work presents a combined thermal and mechanical finite element analysis and evolutionary optimization-based novel approach for estimating the optimal design parameters of the ventilated brake disc. Five parameters controlling the design: Inboard plate thickness, outboard plate thickness, vane height, effective offset, and center hole radius were considered, and simulation runs were planned. 27 brake disc designs with design parameters as recommended by the Taguchi method (L27) were modeled using SOLIDWORKS, and the FEA simulation runs were carried out using ANSYS thermal & structural analysis tool. The fatigue life results were analyzed using a 3D surface plot for the effect of the design parameters on the response, contour plots for the determination of maximum response, and statistical regression analysis for model interpretation and predictive modeling. Finally, the two most accurate and widely used evolutionary optimization algorithms: genetic algorithm (GA) and particle swarm optimization (PSO) were applied to determine the optimal design parameters for the ventilated brake disc. The brake disc of design parameters predicted by GA and (PSO), gives 12.74% higher fatigue life compared to parametric analysis. These results have shown that the developed approach can be utilized effectively and reliably for solving, design ventilated brake disc problem in the industry.

Graphical abstract

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

References

  1. S. Yim, Y.H. Jo, Integrated chassis control with AFS, ARS and ESC under lateral force constraint on AFS. JMST Adv. 1, 13–21 (2019)

    Article  Google Scholar 

  2. S. Aguib, Mathematical modeling and finite element analysis of the mechanical behavior of hybrid structures in complex materials. JMST Adv. 2, 1–8 (2020)

    Article  Google Scholar 

  3. Y. Chen, D. Vasiukov, L. Gélébart, C.H. Park, Fast Fourier transform solver for damage modeling of composite materials. JMST Adv. 1, 49–55 (2019)

    Article  Google Scholar 

  4. A. Belhocine, O.I. Abdullah, Design and thermomechanical finite element analysis of frictional contact mechanism on automotive disc brake assembly. J. Fail. Anal. Prev. 20, 270–301 (2020)

    Article  Google Scholar 

  5. A. Khan, N. Kim, J.K. Shin, H.S. Kim, B.D. Youn, Damage assessment of smart composite structures via machine learning: a review. JMST Adv. 1, 107–124 (2019)

    Article  Google Scholar 

  6. A. Belhocine, M. Bouchetara, Thermal analysis of a solid brake disc. Appl. Therm. Eng. 32, 59–67 (2012)

    Article  Google Scholar 

  7. A. Belhocine, A. Afzal, A predictive tool to evaluate braking system performance using a fully coupled thermo-mechanical finite element model. Int. J. Interact. Des. Manuf. (IJIDeM) 14, 225–253 (2020)

    Article  Google Scholar 

  8. M. Pevec, I. Potrc, G. Bombek, D. Vranesevic, Prediction of the cooling factors of a vehicle brake disc and its influence on the results of a thermal numerical simulation. Int. J. Automot. Technol. 13, 725–733 (2012)

    Article  Google Scholar 

  9. A. Belhocine, A.R.A. Bakar, O.I. Abdullah, Structural and contact analysis of disc brake assembly during single stop braking event. Trans. Indian Inst. Met. 68, 403–410 (2015)

    Article  Google Scholar 

  10. L. Zhang, D. Meng, Z. Yu, Theoretical modeling and FEM analysis of the thermo-mechanical dynamics of ventilated disc brakes. SAE Technical Paper, Tech. Rep. 2010

  11. Q. Jian, Y. Shui, Numerical and experimental analysis of transient temperature field of ventilated disc brake under the condition of hard braking. Int. J. Therm. Sci. 122, 115–123 (2017)

    Article  Google Scholar 

  12. M. Duzgun, Investigation of thermo-structural behaviors of different ventilation applications on brake discs. J. Mech. Sci. Technol. 26, 235–240 (2012)

    Article  Google Scholar 

  13. P. Hwang, X. Wu, Investigation of temperature and thermal stress in ventilated disc brake based on 3D thermo-mechanical coupling model. J. Mech. Sci. Technol. 24, 81–84 (2010)

    Article  Google Scholar 

  14. T. Mahmoudi, A. Parvizi, E. Poursaeidi, A. Rahi, Thermo-mechanical analysis of functionally graded wheel-mounted brake disk. J. Mech. Sci. Technol. 29, 4197–4204 (2015)

    Article  Google Scholar 

  15. S.P. Jung, T.W. Park, J.B. Chai, W.S. Chung, Thermo-mechanical finite element analysis of hot judder phenomenon of a ventilated disc brake system. Int. J. Precis. Eng. Manuf. 12, 821–828 (2011)

    Article  Google Scholar 

  16. M.-J. Han, C.-H. Lee, T.-W. Park, S.-P. Lee, Low and high cycle fatigue of automotive brake discs using coupled thermo-mechanical finite element analysis under thermal loading. J. Mech. Sci. Technol. 32, 5777–5784 (2018)

    Article  Google Scholar 

  17. L. Zhang, Q. Yang, D. Weichert, N. Tan, Simulation and analysis of thermal fatigue based on imperfection model of brake discs. Proc. Appl. Math. Mech. (PAMM) 9, 533–534 (2009)

    Article  Google Scholar 

  18. E. Kakander, R. Roy, J. Mehnen, A simulation based approach to model design influence on the fatigue life of a vented brake disc. Proc. CIRP 59, 41–46 (2017)

    Article  Google Scholar 

  19. H. Lü, Yu. Dejie, Optimization design of a disc brake system with hybrid uncertainties. Adv. Eng. Softw. 98, 112–122 (2016)

    Article  Google Scholar 

  20. H. Lü, Yu. Dejie, Brake squeal reduction of vehicle disc brake system with interval parameters by uncertain optimization. J. Sound Vib. 333, 7313–7325 (2014)

    Article  Google Scholar 

  21. H.M. Abbas, M.M. Bayoumi, Volterra-system identification using adaptive real-coded genetic algorithm. IEEE Trans. Syst. Man Cybern. A Syst. Hum. 36, 671–684 (2006)

    Article  Google Scholar 

  22. M. Bagheri, A.A. Jafari, M. Sadeghifar, A genetic algorithm optimization of ring-stiffened cylindrical shells for axial and radial buckling loads. Arch. Appl. Mech. 81, 1639–1649 (2011)

    Article  Google Scholar 

  23. R. Brighenti, A. Carpinteri, S. Vantadori, A genetic algorithm applied to optimisation of patch repairs for cracked plates. Comput. Methods Appl. Mech. Eng. 196, 466–475 (2006)

    Article  Google Scholar 

  24. Y. Alperen, C. Sertac, Multi objective optimization of a micro-channel heat sink through genetic algorithm. Int. J. Heat Mass Transf. 146, 118847 (2020)

    Article  Google Scholar 

  25. M.G. Sahab, V.V. Toropov, and A.H. Gandomi, Metaheuristic Applications in Structures and Infrastructures (Elsevier, 2013), pp. 25–47

  26. S. Klancnik, M. Brezocnik, J. Balic, I. Karabegovic, Programming of CNC milling machines using particle swarm optimization. Mater. Manuf. Process. 28, 811–815 (2013)

    Article  Google Scholar 

  27. X.Y. Kou, G.T. Parks, S.T. Tan, Optimal design of functionally graded materials using a procedural model and particle swarm optimization. Comput. Aided Des. 44, 300–310 (2012)

    Article  Google Scholar 

  28. T.P. Latchoumi, K. Balamurugan, K. Dinesh, T.P. Ezhilarasi, Particle swarm optimization approach for waterjet cavitation peening. Measurement 141, 184–189 (2019)

    Article  Google Scholar 

  29. P.J. Pawar, R.V. Rao, J.P. Davim, Multiobjective optimization of grinding process parameters using particle swarm optimization algorithm. Mater. Manuf. Process. 25, 424–431 (2010)

    Article  Google Scholar 

  30. V. Balasubramanian, A.K. Lakshminarayanan, R. Varahamoorthy, S. Babu, Understanding the parameters controlling plasma transferred arc hardfacing using response surface methodology. Mater. Manuf. Process. 23, 674–682 (2008)

    Article  Google Scholar 

  31. K. Kalita, I. Shivakoti, R.K. Ghadai, Optimizing process parameters for laser beam micro-marking using genetic algorithm and particle swarm optimization. Mater. Manuf. Process. 32, 1101–1108 (2017)

    Article  Google Scholar 

  32. R.K. Ghadai, K. Kalita, S.C. Mondal, B.P. Swain, PECVD process parameter optimization: towards increased hardness of diamond-like carbon thin films. Mater. Manuf. Process. 33, 1905–1913 (2018)

    Article  Google Scholar 

  33. V.K. Garlapati, P.R. Vundavilli, R. Banerjee, Evaluation of lipase production by genetic algorithm and particle swarm optimization and their comparative study. Appl. Biochem. Biotechnol. 162, 1350–1361 (2010)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, University of Sciences and the Technology of Oran, L.P. 1505 El-Mnaouer, USTO, 31000, Oran, Algeria

    Ali Belhocine

  2. Gujarat Technological University, Ahmedabad, India

    Dinesh Shinde

  3. Hitech iSolutions LLP, Ahmedabad, India

    Rahul Patil

Authors
  1. Ali Belhocine
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dinesh Shinde
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rahul Patil
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ali Belhocine.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Belhocine, A., Shinde, D. & Patil, R. Thermo-mechanical coupled analysis based design of ventilated brake disc using genetic algorithm and particle swarm optimization. JMST Adv. 3, 41–54 (2021). https://doi.org/10.1007/s42791-021-00040-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42791-021-00040-0

Keywords

  • Ventilated brake disc
  • Coupled thermo-mechanical analysis
  • Fatigue life
  • Parametric analysis
  • Genetic algorithm
  • Particle swarm optimization