Preview Control of a Semi-Active Suspension System Supplemented by an Active Aerodynamic Surface

This research presents a harmonized optimal preview control strategy for a semi-active suspension system (SASS) with a controlled damper varied between the upper and lower bounds of the damping coefficient and an active aerodynamic surface (AAS) control. The preview control algorithm is based on a simplified bilinear 2-DOF quarter-car model to address the tradeoff between passenger ride comfort and road holding capabilities. While the active suspension with the actuator requires a significant amount of energy to provide control force, the semi-active suspension system with a variable damping coefficient mechanism consumes minimal energy to adapt quickly to the real-time operating conditions. Moreover, the dynamic performance of semi-active suspension with the preview controller in conjunction with the active aerodynamic surface is significantly improved. MATLAB<sup>®</sup> (R2025b)-based numerical simulations for different road excitations were carried out for the evaluation of the proposed system. Both time-domain and frequency-domain results demonstrate enhanced vehicle dynamic performances in response to road bumps, asphalt road excitations, and harmonic input signals. The simulation performance results indicate that the proposed system extraordinarily reduced the variation in the mean-squared value of the car body vertical acceleration. At the same time, the system enhanced the wheel-road holding metric by decreasing the variation in the gripping force on the ground surface, while maintaining the necessary suspension rattle space constraints within the prescribed limit.

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Publication Details

Journal
Sensors
Published
2025-11-12
DOI
https://doi.org/10.3390/s25226922
Primary Topic
Vibration Control and Rheological Fluids
Type
article
Field-Weighted Citation Impact
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article

Preview Control of a Semi-Active Suspension System Supplemented by an Active Aerodynamic Surface

Iljoong Youn, Syed Babar Abbas
Sensors
Vibration Control and Rheological Fluids
article

Preview Control of a Semi-Active Suspension System Supplemented by an Active Aerodynamic Surface

Iljoong Youn, Syed Babar Abbas
article en

Abstract

This research presents a harmonized optimal preview control strategy for a semi-active suspension system (SASS) with a controlled damper varied between the upper and lower bounds of the damping coefficient and an active aerodynamic surface (AAS) control. The preview control algorithm is based on a simplified bilinear 2-DOF quarter-car model to address the tradeoff between passenger ride comfort and road holding capabilities. While the active suspension with the actuator requires a significant amount of energy to provide control force, the semi-active suspension system with a variable damping coefficient mechanism consumes minimal energy to adapt quickly to the real-time operating conditions. Moreover, the dynamic performance of semi-active suspension with the preview controller in conjunction with the active aerodynamic surface is significantly improved. MATLAB<sup>®</sup> (R2025b)-based numerical simulations for different road excitations were carried out for the evaluation of the proposed system. Both time-domain and frequency-domain results demonstrate enhanced vehicle dynamic performances in response to road bumps, asphalt road excitations, and harmonic input signals. The simulation performance results indicate that the proposed system extraordinarily reduced the variation in the mean-squared value of the car body vertical acceleration. At the same time, the system enhanced the wheel-road holding metric by decreasing the variation in the gripping force on the ground surface, while maintaining the necessary suspension rattle space constraints within the prescribed limit.

SensorsVol. 25(22)
Gyeongsang National University (KR)
Openalex Percentile: Top 64%
Vibration Control and Rheological Fluids
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Preview Control of a Semi-Active Suspension System Supplemented by an Active Aerodynamic Surface — Iljoong Youn, Syed Babar Abbas · Sensors (2025) | TGRS Research Map | TGRS