Model Predictive Controller Development for controlling Actuators of Automated Manual Transmission

Abstract

Automotive transmission technology is evolving rapidly to match up with the growing need of increased power transfer efficiency, tractive demands and powertrain electrification. In this, Automated Manual Transmission (AMT) systems have made their way to the global market as popular choice by automotive industry. AMT applications have grown substantially in Hybrid Electric Vehicles, where hybrid controller decides optimum gear ratio and the gearshift needs to be automated. Advanced model-based predictive techniques for AMT supervisory controllers have allowed complex clutch control, gear shift control and optimal gear-ratio selection. However, the AMT’s lower level actuator control is usually done with the help of simple linear controllers like PID. This work aims to evaluate the performance of the AMT system when using a Model Predictive Controller (MPC) for controlling generic AMT actuators. This generic AMT and its control system are modeled and implemented within a HEV vehicle closed loop system model. For gearshift control problem, MPC controller is developed and implemented as actuator controller within the AMT control system framework. A simple PID based actuator controller is also developed to serve as benchmark. The comparative performance of the developed MPC and PID based controllers are evaluated by simulating them during gear-shift operation under a realistic drive cycle. Finally, suitability of MPC for the AMT actuator controller is illustrated through the obtained results.