Comparative Study between the Gravitational Search Algorithm and Fire Hawk Algorithm in an Off-Road Seat Suspension Optimization

Document Type : Original Article

Authors

1 Faculty of Mechanical Engineering, Arak University of Technology, Arak, Iran.

2 Department of Agricultural Engineering, Markazi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension, Organization (AREEO), Arak, Iran.

10.22084/best.2025.31229.1009

Abstract

Long-term driving of Off-Road Vehicles increases the risk of damage to some organs of humans, such as the spinal column or digestive system. Whereas seat suspensions are used in heavy-duty off-road vehicles, adjusting the parameters of them is crucial. Recently, non-gradient optimization methods have been focused on by researchers to tune these parameters, such as spring constant, damper coefficient, and seat pan mass. Current work represents the application of two Meta-Heuristic techniques (Gravitational Search (GSA)and Fire Hawk Optimization Algorithms (FHOA)) to minimize transmitted vibration from the cabin floor to the seat pan. According to the GSA, the amplitude of seat displacement is around 2×10-5 (m). Moreover, the first peak is reached at 0.95×10-5 at 8Hz. In addition, according to the FHOA, the magnitude of output via FHOA optimum parameters is 0.8× 10-5, in the time domain. On the other hand,
in the frequency domain, the first peak is gotten 4.2×10-6. So, it shows that the performance of passive seat suspension, which is adjusted with GSA, is more enhanced in comparison to FHOA. In conclusion, the outcomes of optimization via simulation show that GSA has a better performance compared to FHOA, and the seat suspension tuned by that can diminish the vibration with notable diminishment.

Keywords

References

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Biosystems Engineering and Sustainable Technologies
Volume 1, Issue 2
December 2025
Pages 21-29

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