Application of metaheuristic algorithms for optimisation of brake force distribution in agricultural trailers

Kamiński, Zbigniew

doi:10.12913/22998624/200594

Artykuł - szczegóły

Tytuł artykułu

Application of metaheuristic algorithms for optimisation of brake force distribution in agricultural trailers

Autorzy

Kamiński Zbigniew

Treść / Zawartość

Pełne teksty:

Pobierz

Identyfikatory

DOI

10.12913/22998624/200594

Warianty tytułu

Języki publikacji

Abstrakty

According to EU Regulation 2015/68 on the approval of agricultural vehicles, high-speed trailers of categories R3 and R4 must meet the brake force distribution requirements between the axles. Five metaheuristic algorithms (MIDACO, Cuckoo Search, Firefly Algorithm, Simulated Annealing, and Harmony Search) implemented in open-source MATLAB code were used to optimize the linear brake force distribution found in trailers with braking force regulators. The optimization results obtained for a two-axle and a three-axle trailer with two variants of tandem axles (bogie and two leaf springs) are very close to the results obtained by the Quasi-Monte Carlo method. Although metaheuristic methods do not always guarantee that an exact optimum solution will be found, they can be successfully applied to the selection of brake force distribution in the initial stages of brake system design. They have the advantage of flexibility, simplicity, less mathematical complexity, and avoidance of local optima. The brake force distribution optimization results can be used to establish the parameters of the wheel braking mechanisms of agricultural trailer axles.

Słowa kluczowe

agricultural trailer brake force distribution optimization meta-heuristic method

Wydawca

Lublin University of Technology
Polish Society of Ecological Engineering (PTIE), Branch of PTIE in Lublin

Czasopismo

Advances in Science and Technology. Research Journal

Rocznik

2025

Tom

Vol. 19, no. 5

Strony

96--112

Opis fizyczny

Bibliogr. 50 poz., fig., tab.

Twórcy

autor

Kamiński Zbigniew

z.kaminski@pb.edu.pl

Department of Machine Design and Exploitation, Faculty of Mechanical Engineering, The Bialystok University of Technology, ul. Wiejska 45C, 15-351 Bialystok, Poland

https://orcid.org/0000-0003-2693-5077

Bibliografia

1. Commission Delegated Regulation (EU) 2015/68 of 15 October 2014 supplementing Regulation (EU) No 167/2013 of the European Parliament and of the Council with regard to vehicle braking requirements for the approval of agricultural and forestry vehicles.
2. Glišović J., Lukić J., Šušteršič V., Ćatić D. 2015. Development of tractors and trailers in accordance with the requirements of legal regulations. In: Proc. of 9th International Quality Conference, Kragujeac, Serbia 2015, 193–202.
3. Caban A., Kidawski A., Włodarczyk A. Synchronization of the braking of heavy tractor-trailer and tractor-semitrailer units: operational problems. The Archives of Automotive Engineering – Archiwum Motoryzacji 2017; 77(3): 17-29. DOI: https://doi. org/10.14669/AM.VOL.77.ART2
4. Zhang N., Wu J., Li T., Zhao Z., Yin G. Influence of braking on dynamic stability of car-trailer cominations. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 2021; 235(2-3): 455-464. https://doi. org/10.1177/09544070209598
5. Mital A., Desai A., Subramanian A., Mital A. Product development: A structured approach to consumer product development, design, and manufacture. 2nd ed. Elsevier Science, 2014.
6. Tang G., Zhao H., Wu J., Zhang, Y. Optimization of braking force distribution for three-axle truck. SAE Technical Paper 2013-01-0414, 2013. https://doi.org/10.4271/2013-01-0414
7. Limpert R. An investigation of the brake force distribution on tractor-semitrailer combinations. SAE Technical Paper 710044 1971. https://doi. org/10.4271/710044
8. Zheng H., Liu C., Wang L. A braking force distribution strategy in integrated braking system based on wear control and hitch force control. SAE Technical Paper 2018-01-0827, 2018. https://doi. org/10.4271/2018-01-0827
9. Beyer C., Schramm H., Wrede, J. Electronic braking system EBS - status and advanced functions. SAE Technical Paper 982781, 1998. https://doi. org/10.4271/982781
10. Nakazawa M., Isobe O., Takahashi S., Watanabe Y. Braking force distribution control for improved vehicle dynamics and brake performance. Vehicle System Dynamics 1995; 24 (4-5): 413-426. https:// doi.org/10.1080/00423119508969101
11. Wabco. Pneumatic braking system. Agriculture and forestry. Product catalogue 2017. https://www.wabco- customercentre.com/catalog/docs/8150100823.pdf
12. Forrer P. Brake systems in agricultural and forestry vehicles. https://www.laumetris.lt/UserFiles/im- age/downloads/Dual_and_Single_Line_Hydrau-lic_Brakes_Paul_Forrer_EN.pdf
13. Miatluk M, Kamiński Z. Układy hamulcowe pojazdów. Obliczenia. Wydawnictwo Politechniki Białostockiej, 2005.
14. Sun, B., Wang, P., Gao, S., Yu, J., Wang, Z. Development of braking force distribution strategy for dualmotor-drive electric vehicle. Journal of Engineering and Technological Sciences 2018; 50(2): 179-201. https://doi.org/10.5614/j.eng.technol.sci.2018.50.2.3
15. Li X., Zhang X., Wang Y. Regenerative braking control strategies with fixed ratio and variable ratio braking forces optimization distribution for electric vehicles during downhill process. International Journal of Automotive Technology 2022; 23: 667- 681. https://doi.org/10.1007/s12239-022-0061-7
16. Limpert, R. Brake design and safety (3rd ed). SAE International, 2011. https://doi.org/10.4271/R-398
17. Harwood D.W. Review of Truck Characteristics as Factors in Roadway Design. The National Academies Press, 2003. https://doi.org/10.17226/23379
18. Stegherr H., Heider M. Hähner, J. Classifying metaheuristics: towards a unified multi-level classifica- tion system. Natural Computing 2022; 21(2): 155- 171. https://doi.org/10.1007/s11047-020-09824-0
19. Tomar V, Bansal M, Singh P. Metaheuristic algorithms for optimization: a brief review. Engineering Proceedings 2023; 59(1): 238. https://doi. org/10.3390/engproc2023059238
20. Hamadneh T., Batiha B., Werner F., Eguchi K., Montazeri Z., Dehghani M. A completely different and innovative bio-inspired metaheuristic approach for effectively solving complex optimization problems across various domains. Preprints 2024; 2024091803. https://doi.org/10.20944/pre-prints202409.1803.v1
21. Rahimi I., Gandomi A.H., Chen F. et al. A Review on constraint handling techniques for population-based algorithms: from single-objective to multi-objective optimization. Archives of Computational Methods in Engineering 2023; 30(3): 2181–2209. https://doi.org/10.1007/s11831-022-09859-9
22. Oztas G.Z., Erdem S. A penalty-based algorithm proposal for engineering optimization problems. Neural Computing and Application 2023; 35(10): 7635– 7658. https://doi.org/10.1007/s00521-022-08058-8
23. Kasem M. A. M., Maalawi K. Efficient algorithms and models for mechanical and structural design optimization. Journal of Mechanical Engineering and Sciences 2021; 15(3): 8405–8417. https://doi. org/10.15282/jmes.15.3.2021.17.0661
24. Haataja M., Leinonen, T. On the distribution of braking forces in road braking. SAE Technical Paper 2000-01-3413 2000. https://doi. org/10.4271/2000-01-3413
25. Liu Z., Zheng H., Xu W. A model-based mass estimation and optimal braking force distribution algorithm of tractor and semi-trailer combination. SAE Technical Paper 2013-01-0418 2013. https:// doi.org/10.4271/2013-01-0418
26. Zhang N., Wu J., Li T., Zhao Z., Yin G. Influence of braking on dynamic stability of car-trailer combinations. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 2021; 235(2-3): 455-464. doi:10.1177/0954407020959895
27. Radlinski R.W., Wiliams S.F. NHTSA heavy duty vehicle brake research program: Report no. 1 - stopping capability of air braked vehicles. National Highway Traffic Safety Administration, 1985.
28. BPW. Mechanical load-dependent brake force regulator. The unique solution for the requirements imposed by regulation EU 2015/68. https://bpwagrar.comen/mlb/
29. Schlueter M., Gerdts M., Rueckmann J.J. A numerical study of MIDACO on 100 MINLP benchmarks. Optimization 2012; 61(7): 873-900, https://doi.org/ 10.1080/02331934.2012.668545
30. Schlueter M., Gerdts M. The oracle penalty method. Journal of Global Optimization 2010; 47(2): 293-325. https://doi.org/10.1007/ s10898-009-9477-0
31. MIDACO-SOLVER. Numerical high-performance optimization Software. http://www.midaco-solver.com/
32. Yang X.S., Deb S. Engineering optimisation by Cuckoo Search. International Journal of Mathematical Modelling and Numerical Optimisation 2010; 1(4): 330-343. https://doi.org/10.1504/IJMMNO.2010.035430
33. Yang, X.-S. Nature-inspired optimization algorithms (2nd ed.). Elsevier, 2020.
34. Yang X.-S. Nature-inspired metaheuristic algorithm. Luniver Press, 2010.
35. Kirkpatrick S., Gelatt C.D., Vecchi, M.P. Optimization by simulated annealing. Science 1983; 220(4598): 671-680. http://dx.doi.org/10.1126/ science.2204598.671
36. Yang X.-S. Cuckoo Search (CS) algorithm (https://www.mathworks.com/matlabcentral/ fileexchange/29809-cuckoo-search-cs-algorithm). MATLAB Central File Exchange, 2024.
37. Yang X.-S. Firefly Algorithm (https://www.math- works.com/matlabcentral/fileexchange/29693-firefly-algorithm). MATLAB Central File Exchange, 2024.
38. Yang X.-S. Simulated annealing for constrained optimization (https://www.mathworks.com/matlab- central/fileexchange/29739-simulated-annealing-for-constrained-optimization). MATLAB Central File Exchange, 2024.
39. Geem, Z.W., Kim J.H., Loganathan G.V. A new heuristic optimization algorithm: Harmony search. Simulation 2001; 76 (2): 60–68. https://doi. org/10.1177/003754970107600201
40. Fesanghary M. Harmony Search Algorithm (https://www.mathworks.com/matlabcentral/ fileexchange/28850-harmony-search-algorithm), MATLAB Central File Exchange, 2024.
41. Kroese D.P., Taimre T., Botev Z.I. Handbook of Monte Carlo methods. John Wiley and Sons, 2011.
42. Kamiński Z. Calculation of the optimal braking force distribution in three-axle trailers with tan-dem suspension. Acta Mechanica et Automatica 2022; 16(3): 189-199. https://doi.org/10.2478/ ama-2022-0023
43. Burkhardt, J. Various software. MATLAB source codes. The Hammersley Quasi Monte Carlo (QMC) Sequence 2020. https://people.sc.fsu. edu/~jburkardt/m_src/hammersley/hammersley.html
44. Hammersley J. M. Monte Carlo methods for solving multivariable problems. Annals of the New York Academy of Sciences 1960; 86(3): 844-874. https:// doi.org/10.1111/j.1749-6632.1960.tb42846.x
45. Bryant D., Day A. Braking of Road Vehicles. Elsevier, 2022. https://doi.org/10.1016/C2019-0-04185-4
46. Revised standards for agricultural vehicles. RSA Guide. Road Safety Authority, 2015.
47. ISO 8855: 2011. Road vehicles - Vehicle dynamics and road-holding ability-Vocabulary.
48. BPW agricultural catalogue. Growing together. Customised solutions, 2020.
49. https://www.bpw.de/fileadmin/data/downloads/ BPW_Agricultural_Catalogue_2020_en.pdf
50. Colaert Essieux. General catalogue, 2023. https:// www.adraxles.com/gallery/catalogue-colaert-es- sieux-2023-v22-11-18-lr.pdf

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-afaccd58-8095-4121-9d8c-7236758e50a5