Off-Road Vehicle Seat Suspension Optimisation, Part II: Comparative Study between Meta-Heuristic Optimisation Algorithms. Issue 4 (December 2014)

• Record Type: Journal Article
• Authors: Gohari, Mohammad; Tahmasebi, Mona
• Is Part Of: Journal of low frequency noise, vibration, and active control. Volume 33:Issue 4(2014)
• Page Start: 443
• Page End: 454
• Publication Date: 2014-12
• Subjects: Vibration -- Periodicals; Noise -- Periodicals; Sound -- Periodicals; Damping (Mechanics) -- Periodicals; Damping (Mechanics); Noise; Sound; Vibration; Periodicals; 620.205
• DOI: 10.1260/0263-0923.33.4.443
• Languages: English
• ISSNs: 1461-3484

Abstract

Clinical observations show that a significant number of low back pain, spine disorders and head injuries are related to exposure to vibration of vehicles. Implementation of seat to suspensions reduces the effects of vibration in vehicle operators in long terms. This paper discusses three evolutionary algorithms in off-road seat suspension design. Genetic algorithm (GA), particle swarm optimisation (PSO) and harmony search (HS) algorithm were used to minimise transmitted vibration to the driver's spine which was modelled by artificial neural network biodynamic model based on experimental data, as was discussed in part I. The reliability of results was studied by simulation of vibration in vertical direction. The suspension was tuned based on harmony search depicting lower values of seat to spine vibration transmissibility and mobility. Thus, the transmitted vibration to spine and risk of spine problem may be alleviated by using this tuned seat suspension.