Intelligent Transportation Systems (ITS) is a broad category of research relating to new technologies that can improve systems in vehicles, such as safety or energy management. The studies in this thesis discuss how energy management systems can be improved with theories and information from ITS research areas. New types of vehicles are entering the marketplace now that include electric vehicles (EV’s), hybrid electric vehicles (HEV’s), and plug-in hybrid electric vehicles (PHEV’s). HEV’s and PHEV’s are a particular challenge to control engineers because of the flexibility of their powertrains. These vehicles contain two power sources, their internal combustion engine and their battery-powered electric motor. The powersplit control problem will be discussed and how optimal control theory can be implemented to optimize the powersplit resulting in lower fuel consumption.
Chapter 2 discusses the areas of ITS that are relevant to the PHEV control problem. These include sourcing geographic data such as road grade and computing the length and geometry of a route to be traversed. Chapter 3 covers the Challenge X vehicle simulator and the dynamic equations that form the vehicle model. The Challenge X vehicle was designed for the 2004 Challenge X competition sponsored by General Motors where student teams competed to convert a small SUV into a hybrid electric vehicle. This simulator was modified from its original form to reflect a prototype plug-in hybrid electric vehicle. This included modifying the battery model to include more capacity and change the cell chemistry to lithium ion from nickel-metal hydride. Chapter 4 includes the details of the powersplit control algorithm implemented, called the Adaptive Equivalent Consumption Minimization Strategy(A-ECMS). A new formulation called the finite horizon adaptive ECMS is introduced and its performance analyzed under varying road load conditions and compared with the global optimal solution from Dynamic Programming.