DocumentCode
1798039
Title
Cloud aided semi-active suspension control
Author
Zhaojian Li ; Kolmanovsky, Ilya ; Atkins, Ella ; Jianbo Lu ; Filev, Dimitar ; Michelini, John
Author_Institution
Dept. of Aerosp. Eng., Univ. of Michigan, Ann Arbor, MI, USA
fYear
2014
fDate
9-12 Dec. 2014
Firstpage
76
Lastpage
83
Abstract
This paper considers the problem of vehicle suspension control from the perspective of a Vehicle-to-Cloud-to-Vehicle (V2C2V) distributed implementation. A simplified variant of the problem is examined based on the linear quarter-car model of semi-active suspension dynamics. Road disturbance is modeled as a combination of a known road profile, an unmeasured stochastic road profile and potholes. Suspension response when the vehicle hits the pothole is modeled as an impulsive change in wheel velocity with magnitude linked to physical characteristics of the pothole and of the vehicle. The problem of selecting the optimal damping mode from a finite set of damping modes is considered, based on road profile data. The information flow and V2C2V implementation are defined based on partitioning the computations and data between the vehicle and the cloud. A simulation example is presented.
Keywords
cloud computing; mechanical engineering computing; road vehicles; suspensions (mechanical components); vehicle dynamics; V2C2V; cloud aided semiactive suspension control; linear quarter-car model; optimal damping mode; potholes; road disturbance; semiactive suspension dynamics; unmeasured stochastic road profile; vehicle suspension control; Damping; Roads; Stochastic processes; Suspensions; Tires; Vehicles; Wheels;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence in Vehicles and Transportation Systems (CIVTS), 2014 IEEE Symposium on
Conference_Location
Orlando, FL
Type
conf
DOI
10.1109/CIVTS.2014.7009481
Filename
7009481
Link To Document