DocumentCode :
1673714
Title :
Model predictive control for drivability enhancement with input dead-segment
Author :
Yoon, Yongsoon ; An, Youngse ; Park, Youngjoo ; Kim, H. Jin
Author_Institution :
Gasoline Syst. R&D Center, Continental Automotive Syst., Icheon, South Korea
fYear :
2010
Firstpage :
916
Lastpage :
921
Abstract :
Optimization between comfortability and an accelerating power which drivers desire is a significant issue in powertrain control. When torque demand of the drivers changes drastically, like tip-in/out, the drivers experience severe vibrations called jerking. Although torque reduction up to a certain extent alleviates the vibration of drive shaft, an excessive reduction deteriorates a power of acceleration. In this paper, optimal suppression of unpleasant vibration in a drive shaft will be presented via a model predictive control (MPC). As output variables to be tracked in MPC scheme, torsion angle and its rate are considered with analysis of dynamical characteristics. The proposed approach takes into account inherent input dead-segment of internal combustion engines. Simulation results show that the suggested MPC approach for active torque control suppresses the vibration of driveline efficiently while avoiding a critical loss of accelerating power.
Keywords :
automotive components; internal combustion engines; power transmission (mechanical); predictive control; torque control; vibration control; active torque control; automotive engine; drivability enhancement; drive shaft; driveline control; internal combustion engines; jerking; model predictive control; powertrain control; torque demand; torque reduction; vibration suppression; Driver circuits; Engines; Kalman filters; Predictive models; Shafts; Torque; Wheels; Driveline control; Input dead-segment; Kalman filter; Model predictive control; Varying sampling time;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Automation and Systems (ICCAS), 2010 International Conference on
Conference_Location :
Gyeonggi-do
Print_ISBN :
978-1-4244-7453-0
Electronic_ISBN :
978-89-93215-02-1
Type :
conf
Filename :
5669808
Link To Document :
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