Performance analysis of semi-active suspension in an electric vehicle with acceleration-driven damping

In order to enhance ride comfort performance of an electric vehicle (EV) semi-active suspension system (SASs), a 5-degree-of-freedom dynamic model of an EV is proposed to analyze their effectiveness on ride comfort. A SASs with Acceleration-Driven Damping (ADD) is proposed for enhance ride comfort performance of EV SASs. The Firefly Algorithm (FA) is used to optimize the ride performance of the SASs. The root mean square (RMS) values of vertical driver’s seat acceleration (aws), vertical body vehicle acceleration (awb), and pitching body vehicle acceleration (awphi) are selected based on the ISO 2631:1997(E) standard. The achieved results indicate that the aws, awb and awphi values with the proposed SASs respectively reduce by 12.07%, 6.85%, and 21.47% compared to the original passive suspension systems (PSSs) when vehicle moves on ISO road class B at a speed of 20 m/s and full load. In addition, the ride effectiveness is verified under various vehicle velocities.

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Publication Details

Journal
Journal of Military Science and Technology
Published
2025-04-15
DOI
https://doi.org/10.54939/1859-1043.j.mst.102.2025.164-172
Primary Topic
Vibration Control and Rheological Fluids
Type
article
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article

Performance analysis of semi-active suspension in an electric vehicle with acceleration-driven damping

Bùi Văn Cường, Le Van Quynh, Hoang Anh Tan, Nguyen Tien Dung
Journal of Military Science and Technology
Vibration Control and Rheological Fluids
article

Performance analysis of semi-active suspension in an electric vehicle with acceleration-driven damping

Bùi Văn Cường, Le Van Quynh, Hoang Anh Tan, Nguyen Tien Dung
article en

Abstract

In order to enhance ride comfort performance of an electric vehicle (EV) semi-active suspension system (SASs), a 5-degree-of-freedom dynamic model of an EV is proposed to analyze their effectiveness on ride comfort. A SASs with Acceleration-Driven Damping (ADD) is proposed for enhance ride comfort performance of EV SASs. The Firefly Algorithm (FA) is used to optimize the ride performance of the SASs. The root mean square (RMS) values of vertical driver’s seat acceleration (aws), vertical body vehicle acceleration (awb), and pitching body vehicle acceleration (awphi) are selected based on the ISO 2631:1997(E) standard. The achieved results indicate that the aws, awb and awphi values with the proposed SASs respectively reduce by 12.07%, 6.85%, and 21.47% compared to the original passive suspension systems (PSSs) when vehicle moves on ISO road class B at a speed of 20 m/s and full load. In addition, the ride effectiveness is verified under various vehicle velocities.

Journal of Military Science and TechnologyVol. 102
Thai Nguyen University (VN), Hanoi University of Science and Technology (VN)
Openalex Percentile: Top 92%
Vibration Control and Rheological Fluids
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