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Multi-variable Optimization of Vehicle Seat Suspension Considering Human Body Model Using Spring-Damper Isolators and Genetic Algorithm

Mafi Shourestani, Farid | 2018

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 52184 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Moradi, Hamed; Vossoughi, Gholamreza
  7. Abstract:
  8. In recent years, the seat suspension system in commercial vehicles, industry, agriculture, transportation and … have been focused by researchers. Designing the spring-damper isolators for vehicle’s seat can be an achievable and suitable strategy to increase the comfort and decrease the risk of injuries in vehicles. In this research, the effect of vibrations due to road roughness has been examined by dynamic modeling of a vehicle in combination with the human body model. Thus by using spring-damper isolators and genetic algorithm, we try to optimize the performance of the system. Designing parameters includes the stiffness and viscosity of seat isolator and our target functions include the acceleration of human organs (like head) and the displacement of them. To achieve this goal, first full vehicle model was simulated in ADAMS considering longitudinal and transversal rotation. Likewise in this simulation in the software, the contact between tires and ground and non-linear curves for damper is considerd. And then the human body was modeled in 4 degree of freedom and then integrated with the car model in MATLAB, both software were executed co-simulationally. Finally the Duffing suspension system with end-stop buffers were added to the introduced system. In order to decrease the genetic algorithm runtime, the Design Of Experiment(DOE) methods were used to estimate optimization functions. Though the effective design parameters were identified by Placket-Burman method and target functions were identified by Response Surface Method. Then multi-objective optimization was performed by genetic algorithm and the optimized surface was found. To compare the optimization results with passice condition, a set of parameters were found by TOPSIS method amongst optimized surface. The result of this study is the optimal design of the vehicle seat suspension system that leads to 50% reduction in RMS head displacement and 54% in RMS head acceleration. Though by comparing the Crest factors for human organs, significant reduction was not observed. In some cases, this parameter was ascending which shows sharper optimized plots
  9. Keywords:
  10. Genetic Algorithm ; Seat Suspension System ; Dynamic Modeling ; Optimization ; Vehicles

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