Engagement control of automated clutch is essential during launching process for a vehicle equipped with an automated manual transmission (AMT), and instantaneous changes in the driver's launching intention make it more complicated to control the clutch. This paper studies the identification of the driver's launching intentions, which may change anytime, and proposes a clutch engagement control method for vehicle launching. First, a launching-intention-aware machine (LIAM) based on artificial neural network (ANN) is designed for real-time tracking and identifying the driver's launching intentions. Second, the optimal engagement strategy for different launching intentions is deduced based on the linear quadratic regulator (LQR), which figures out a compromise between friction loss, vehicle shock, engine speed, clutch speed, and desired vehicle speed. Third, the relationship between transmitted torque and clutch position is obtained by experiments, and a sliding-mode controller (SMC) is designed for clutch engagement. Finally, the clutch engagement control strategy is validated by a joint simulation model and an experiment bench. The results show that the control strategy reflects the driver's launching intentions correctly and improves the performance of vehicle launching.

Issue Section:
Research Papers
Keywords:
Adaptive, Mechatronics, Modeling and simulation, Motion controls, Vehicular dynamics, Optimal control, Dynamic systems
Topics:
Control equipment, Engines, Simulation, Torque, Vehicles, Design, Friction, Particle filtering (numerical methods), Sheet molding compound (Plastics), Sliding mode control, Surface mount components, Simulation models, Simulation results

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