Modeling the Dynamics of a Passenger Car Using Experimental Data on Nonlinear Passive Shock Absorbers
This study explores the dynamic response of passenger cars equipped with nonlinear passive shock absorbers, emphasizing the nonlinear damping characteristics over traditional linear models in simulating real-world driving conditions. To capture the nonlinear damping behavior, experimental data from...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitas Muhammadiyah Magelang
2025-03-01
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| Series: | Automotive Experiences |
| Subjects: | |
| Online Access: | https://journal.unimma.ac.id/index.php/AutomotiveExperiences/article/view/12792 |
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| Summary: | This study explores the dynamic response of passenger cars equipped with nonlinear passive shock absorbers, emphasizing the nonlinear damping characteristics over traditional linear models in simulating real-world driving conditions. To capture the nonlinear damping behavior, experimental data from a shock absorber testing apparatus was utilized to derive an empirical formula. The damping force was modeled using a seventh-order polynomial equation, accurately representing the force-velocity relationship. This nonlinear damping model was integrated into a half-car suspension model, which was subjected to simulations involving two road profiles: a bump and an irregular sinusoidal road profile. Simulations demonstrated that the nonlinear model outperformed its linear counterpart, particularly in vibration control. It achieved significant reductions in body displacement, body acceleration, and suspension deflection, with notable improvements at resonance speeds. Root Mean Square (RMS) analysis further corroborated the nonlinear model's superior damping performance, showing lower displacement and acceleration values compared to the linear model. The findings indicate the effectiveness of nonlinear damping models in enhancing ride comfort and vehicle stability, providing a more realistic and effective framework for vehicle dynamic analysis compared to conventional linear approaches.
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| ISSN: | 2615-6202 2615-6636 |