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ORIGINAL PAPER
Comparing the Performance of Using a Smart Damper in a Semi-Active Suspension Instead of a Traditional Damper Using MATLAB/Simulink
1
Department of Mechanical Engineering, College of Engineering, University of Baghdad, Iraq, Baghdad , Iraq
Submission date: 2024-04-29
Final revision date: 2024-05-25
Acceptance date: 2024-06-12
Publication date: 2024-09-12
Corresponding author
Lamyaa Mahdi Ali
Department of Mechanical Engineering, College of Engineering, University of Baghdad, Iraq, Baghdad , Iraq - Baghdada, /, Baghdad, Iraq
Department of Mechanical Engineering, College of Engineering, University of Baghdad, Iraq, Baghdad , Iraq - Baghdada, /, Baghdad, Iraq
International Journal of Applied Mechanics and Engineering 2024;29(3):1-16
KEYWORDS
TOPICS
ABSTRACT
Given the importance of comfort and safety in various driving circumstances, the suspension system emerges as the most crucial component. Two different suspension systems, passive (PSS) and semi-active (SASS), are compared for effectiveness in this research. MATLAB/Simulink is used for simulation, employing a representative two-degree-of-freedom car model to evaluate and compare the performance results of these systems. The differential equations of motion for the two systems are modeled and simulated using software, which illuminates how they would behave under the same parameters and circumstances. Additionally, a Magnetorheological damper (MR) model with a ¼ vehicle system is used to evaluate its behavior on various types of roads, including those with steps, bumps, and random inputs. This study utilizes the Bingham plastic model to compare the simulation results of SASS and PSS systems. After comparing the numerical and graphical results from the two systems, it is observed that SASSs with controllers perform better than PSSs in terms of suspension adjustment and response time. The SASS is superior to the PSS in suppressing oscillations by 55.12%, 77.47%, and 86.78% for step input, bump, and random inputs, respectively. Additionally, the SASS is faster in eliminating oscillations compared to the PSS by 54% and 51.7% for step input and bump inputs, respectively.
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