Model Predictive Control for Real-Time Simulation of a Network-Controlled Vehicle Drivetrain

This paper proposes a real-time implementation of a networked predictive controller designed to damp driveline oscillations, which is crucial in improving drive ability and passenger comfort, while compensating the time-varying delays that appear due to sending the control commands and the measurements from the sensors through Controller Area Network (CAN). Firstly, the designed real-time structure integrated with CAN test-bench is described and then the model of the drive train is derived. Secondly, considering that the CAN-induced time-varying delays are bounded, a method to model the physical plant (vehicle drive train) including the delays is proposed. Then, a predictive control strategy, which makes use of the previously developed model, is designed in order to damp the driveline oscillations. The proposed control scheme is tested using the designed test-bench and the experiments based on realistic scenarios show that the proposed controller can outperform classical controllers, e.g., PI.

[1]  Jon Rigelsford,et al.  Automotive Control Systems: For Engine, Driveline and Vehicle , 2004 .

[2]  Jonas Fredriksson,et al.  Powertrain Control for Active Damping of Driveline Oscillations , 2002 .

[3]  Peter J. Fleming,et al.  Automotive drive by wire controller design by multi-objective techniques , 2005 .

[4]  Aidan O'Dwyer,et al.  Handbook of PI and PID controller tuning rules , 2003 .

[5]  Reinhard German,et al.  Delay Bounds for CAN Communication in Automotive Applications , 2008, MMB.

[6]  P. Chevrel,et al.  Active control of future vehicles drivelines , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[7]  P. Chevrel,et al.  Active damping of automotive powertrain oscillations by a partial torque compensator , 2007, 2007 American Control Conference.

[8]  Philippe Chevrel,et al.  Active damping of automotive powertrain oscillations by a partial torque compensator , 2008 .

[9]  Marko Bacic,et al.  Model predictive control , 2003 .

[10]  Philippe Chevrel,et al.  A Hinfinity-based control design methodology dedicated to active control of vehicle longitudinal oscillations , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[11]  M. Kanat Camlibel,et al.  Hybrid optimal control of dry clutch engagement , 2007, Int. J. Control.

[12]  Alberto Bemporad,et al.  Model Predictive Powertrain Control: An Application to Idle Speed Regulation , 2010 .

[13]  M. Grotjahn,et al.  Modelling and identification of car driveline dynamics for anti-jerk controller design , 2006, 2006 IEEE International Conference on Mechatronics.

[14]  Manfred Morari,et al.  A hybrid approach to modelling, control and state estimation of mechanical systems with backlash , 2007, Int. J. Control.

[15]  Corneliu Lazar,et al.  Networked Predictive Control Strategy for an Electro-Hydraulic Actuated Wet Clutch , 2010 .

[16]  Philippe Chevrel,et al.  An H-infinity-based control design methodology dedicated to the active control of vehicle longitudinal oscillations , 2003, IEEE Trans. Control. Syst. Technol..