Design of a speed tracking controller for heavy-duty vehicles with an all-speed governor based on a model predictive control strategy

摘要

In this article, a model predictive control strategy is presented for an all-speed governor of heavy-duty vehicles that satisfies the requirements of fast tracking and fuel economy. The control-oriented torque-based engine model is used for the design of a model predictive control-based speed tracking control algorithm. Two methods for improving the speed tracking and fuel economy synthesis are presented, which include engine load estimation and variable weighting factor. The engine speed and fuel mass are used to estimate the real-time engine torque. The variable weighting factor based on the driver's intention is used to adjust the control algorithm in MATLAB/Simulink. The simulation results show that the tracking performance and fuel economy of the model predictive controller are better than that of a proportional-integral-derivative controller.