Energy-optimal control of connected plug-in hybrid electric vehicles using traffic situation predictions in urban driving

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Toyota Motor Manufacturing Canada (TMMC) and other Canadian automobile manufacturers are under increasing pressure to produce cleaner and more fuel-efficient vehicles that also demonstrate improved drivability and safety. Meeting these broad and ambitious standards within a single vehicle is a major challenge for automobile companies which will require significant technological advances in vehicle control systems. ****The main purpose of this research proposal is to improve the performances of energy management system (EMS) and adaptive cruise controller (ACC) in terms of energy efficiency for hybrid electric vehicles and plug-in hybrids (HEV/PHEVs) by making them adaptable to individual traffic situations in urban driving. For HEV/PHEVs, EMS and ACC systems have significant effects on the vehicle's fuel economy and energy efficiency. These controllers can be significantly improved by using predictive control algorithms which require predictions of traffic participant motions in the near future. New advancements in vehicle communications and sensing systems can be used to obtain the required traffic situation predictions. We will use these predicted traffic participants motions information for development and industry-grade evaluation of novel energy-optimal EMS and ecological ACC (Eco-ACC) systems for HEV/PHEVs. In addition to the uncertainties of traffic situations as stochastic processes, the measurement uncertainties and inaccuracies associated with vehicle communications and sensing will be taken into account in the development of the proposed controllers through a systematic control design framework for systems with incomplete data.****The resulting EMS and Eco-ACC control technologies, while initially designed for the Toyota Prius PHEV will be transferable to a broad range of Toyota vehicles, such as Lexus HEV and RAV4 HEV produced by TMMC.******