An Extended-Range Electric Vehicle Control Strategy for Reducing Petroleum Energy Use and Well-to-Wheel Greenhouse Gas Emissions

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2008 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Laboratory (ANL) and sponsored by General Motors (GM) and the U.S. Department of Energy (DoE). Following GM's vehicle development process, HEVT established goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in, range-extended hybrid electric vehicle. The challenge involves designing a crossover SUV powertrain to reduce fuel consumption, petroleum energy use and well-to-wheels (WTW) greenhouse gas (GHG) emissions. In order to interface with and control the vehicle, the team added a National Instruments (NI) CompactRIO (cRIO) to act as a hybrid vehicle supervisory controller (HVSC).

In spite of component issues, the controller validation and verification process resulted in a robust control strategy that ensured vehicle operation in all dynamic testing events at the Year 2 (May 2010) competition and earned Virginia Tech 2^nd place overall. The result of this design process is an Extended-Range Electric Vehicle (E-REV) that uses grid electric energy and E85 fuel for propulsion, known to the design team as the Virginia Tech Range-Extended Crossover (VT_REX). The hybrid vehicle supervisory control strategy designed and implemented by the team uses an easy-to-follow state machine architecture to map and execute high-level decisions. This paper will detail the high-level control strategy decision making structure, and how this control strategy, implemented in the VT_REX vehicle, allows the team to achieve its goal of reducing petroleum energy use by at least 80% and GHG emissions by at least 30%. Real-world vehicle testing data is presented in support of the research.