Predictive powertrain control

Abstract

The main purpose of this study is to design predictive powertrain controller that finds optimal gear and optimal pedal position to minimize the fuel consumption based on the given road data. Model predictive control (MPC) method is used as the controller. Dynamic programming (DP) method is selected as the optimization solver of the algorithm due to the discrete structure of the gear states. Within the scope of this thesis, it is also aimed to develop a truck model with automated manual transmission (AMT) gearbox that can be controlled via MATLAB. The simulation environment is AVL Cruise and MATLAB/ Simulink. AVL Cruise is a powertrain simulation program that allows users to model a variety of powertrains using a specific library of modules. It is used to create the plant model and test it out with various drive cycles. The plant model is evaluated using MATLAB/ Simulink via interface block in the AVL Cruise program and transmission control algorithm which is developed in MATLAB based on the model predictive control method.