TY - GEN
T1 - Active suspension of highway truck seat using genetic algorithms
AU - Hassanin, Hany S.
AU - Rabeih, Al Adl M.
AU - El-Demerdash, Samir M.
AU - Younes, Younes K.
PY - 2008/12/1
Y1 - 2008/12/1
N2 - Heavy trucks are becoming more common in use for international transportations, with longer highways and long driving hours contributing corresponding increases in driver's fatigue that is related to accidents. In this paper a detailed procedure is proposed to improve a highway truck seat. A dynamic model of an on-highway truck seat is simulated using Simulink toolbox in MATLAB. The seat suspension including the cushion is mounted on the cab floor of a half truck model and excited by a rapid excitation of step input. The seat suspension system controller is designed to improve the ride quality of the driver. Genetic Algorithms (GA) is used to obtain the coefficients of the control parameters. In addition, model outputs comparison of the proposed design to a conventional passive seat suspension using the maximum overshoot and the root mean square (RMS) values of both, the driver acceleration and the seat suspension working space. The results showed that an active suspension using genetic algorithms has successfully managed to improve all the dynamic performance parameters of the truck seat with minimum actuator force. Copyright © 2008 SAE International.
AB - Heavy trucks are becoming more common in use for international transportations, with longer highways and long driving hours contributing corresponding increases in driver's fatigue that is related to accidents. In this paper a detailed procedure is proposed to improve a highway truck seat. A dynamic model of an on-highway truck seat is simulated using Simulink toolbox in MATLAB. The seat suspension including the cushion is mounted on the cab floor of a half truck model and excited by a rapid excitation of step input. The seat suspension system controller is designed to improve the ride quality of the driver. Genetic Algorithms (GA) is used to obtain the coefficients of the control parameters. In addition, model outputs comparison of the proposed design to a conventional passive seat suspension using the maximum overshoot and the root mean square (RMS) values of both, the driver acceleration and the seat suspension working space. The results showed that an active suspension using genetic algorithms has successfully managed to improve all the dynamic performance parameters of the truck seat with minimum actuator force. Copyright © 2008 SAE International.
UR - http://www.scopus.com/inward/record.url?scp=84877560844&partnerID=8YFLogxK
U2 - 10.4271/2008-01-1458
DO - 10.4271/2008-01-1458
M3 - Conference contribution
BT - SAE Technical Papers
ER -