In this paper, a multiple model predictive controller (MPC) is proposed for the management of passenger car start up through dry clutch in automated manual transmission. Based on a high-order dynamic model of powertrain system, the feedback controllers are designed by using the crankshaft angular speed and the clutch disk angular speed as measured variables. Moreover, the MPC is developed to comply with constrains both on the input and on the output. The aim of the controller is to ensure a comfortable lockup and to avoid the stall of the engine as well as to reduce the engagement time. Numerical results show the good performance of the MPC with constrains in overcoming critical operating conditions. Comparisons with similar state-of-the-art works are also shown.
Multiple Constrained MPC Design for Automotive Dry Clutch Engagement
PISATURO, MARIO;SENATORE, ADOLFO
2015
Abstract
In this paper, a multiple model predictive controller (MPC) is proposed for the management of passenger car start up through dry clutch in automated manual transmission. Based on a high-order dynamic model of powertrain system, the feedback controllers are designed by using the crankshaft angular speed and the clutch disk angular speed as measured variables. Moreover, the MPC is developed to comply with constrains both on the input and on the output. The aim of the controller is to ensure a comfortable lockup and to avoid the stall of the engine as well as to reduce the engagement time. Numerical results show the good performance of the MPC with constrains in overcoming critical operating conditions. Comparisons with similar state-of-the-art works are also shown.File | Dimensione | Formato | |
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Descrizione: 1083-4435 © 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission; Link editore: https://ieeexplore.ieee.org/document/6869006
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