Model based predictive engine torque control for improved drivability

Elasticity of the various driveline components and backlash originating from gear reduction mechanisms and fasteners may cause torsional vibrations resulting in unintended shunt and shuffle behaviours, when a vehicle is subjected to an acceleration change request. As a result of recent improvements to engine control structures and computational capability developments during the last few decades, the idea of using generated brake torque control has been considered a state of the art research topic among academic researchers and original equipment manufacturers (OEMs). In order to improve transient vehicle response to an acceleration change manoeuvre, a novel engine generated brake torque based model predictive control (MPC) algorithm with an additional anti-shuffle control element has been developed to manipulate the pedal map oriented torque demand signal in an automotive powertrain application. A four mass powertrain model was built and model validation considering longitudinal vehicle dynamics was performed with vehicle level tests using a tip-in followed by a tip out acceleration pedal signal input manoeuvre. Comparison of simulation results and vehicle test data shows that the proposed model is capable of capturing the vehicle acceleration profile revealing unintended error states for the specified input signals. MPC structures based on three mass vehicle models (derived from the four mass model via subtracting tyre dynamics due to high order nonlinearities at the tyre model) was developed in a “MATLAB/Simulink” environment to obtain a smooth and responsive acceleration profile. The MPC controller delivers signal states with the expected performance metrics without error states such as excessive jerks and shuffles. An additional engine to wheel speed difference based proportional controller is employed in order to further reduce powertrain oscillations without compromising from overall system response speed resulting in a comfortable drive.