Adaptive control of a hybrid electric vehicle

Abstract

Hybrid Electric Vehicle (HEV) is a type of hybrid and electric vehicle which makes use of efficiency-improving technologies such as regenerative braking. These vehicles aim to reduce carbon emissions and wastage of energy and are increasingly popular in the world. While there is significant research on the energy management system within the vehicle, it is important that efforts to enhance driving safety though control systems are not neglected.

Vehicle stability and safety is tightly linked to a vehicle and the driver’s adaptability to changing road environments such as road surfaces and wind disturbances. These external undesirable disturbances may cause deviations in the yaw rate which may result in skidding or slipping and thus, jeopardizing the safety of the driver and the passengers. Despite having manual control over the vehicle, it is important to have an intelligent automatic control system to enhance the safety and vehicle handling quality.

This project focuses on the analysis of directional response of a HEV using different control schemes. Three different controllers, namely a Proportional-Integral-Derivative (PID) controller, a Fuzzy Logic controller (FLC) and a Model Reference Adaptive Control (MRAC) were implemented. A linear model of a HEV is derived and used for the simulation studies in this case.

The results of simulation on all three control methods were analyzed and compared to determine the most suitable scheme for maintaining vehicle stability. In addition, the control schemes were tested on a different HEV model to determine its tracking capability and robustness.