Supervisory control of parallel hybrid electric vehicles using matlab/ simulink

Abstract

Due to the limitation of fossil fuels and the high consumption rate of this energy for transportation, inclination of vehicle industry toward other sources of energy is inevitable. Electric vehicles and hybrid vehicles could be a good solution. Thanks to the state of art electric motors, power electronics, embedded power train controller, energy storage systems like batteries and ultra capacitors, the performance of the vehicle could become more and more energy efficient. Since the integrating of all these components in a drive train configuration could be a challenge for the manufacturer, computer simulation and modeling before prototyping could be really beneficial in terms of cost, safety and design performance. The main objective of this study is to establish a systematic approach to parallel hybrid electric vehicle modeling and simulation as well as implementation of the supervisory control in order to improve system efficiency and reduce fuel consumption. This thesis offers an overview of the various applied control strategies in hybrid electric vehicles, specifically to the parallel hybrid electric vehicle. Several control strategies are described in literature as well as important of supervisory control strategy in hybrid electric vehicle and the difference in terms of energy management is discussed. Different hybrid power-train configuration are presented and explained in this thesis. Hybrid electric vehicle driveline components including electric motor, vehicle dynamic, internal combustion engine and electric energy storage are illustrated. In addition, some of the principles of modeling and simulation are discussed and different methods of modeling are presented. A detailed parallel hybrid vehicle modeling and simulation in Matlab environment using Simscape toolbox is presented. A rulebased supervisory control strategy using Simulink/Stateflow is applied to control hybrid vehicle in order to operate parallel hybrid driveline component in their optimal region and consequently to achieve high-performance low-emission hybrid drive-train. Simulation results for the major components of hybrid driveline are presented to demonstrate the effectiveness of this supervisory control strategy.