Intelligent Control of Connected and Automated Vehicles and Powertrains for Cold Climates

点击翻译按钮获取中文摘要

Connected and automated vehicles (CAVs) will become major parts of the Canadian transportation industry. By 2022, the majority of vehicles sold in the US and Canada will have embedded connectivity. In addition, major automotive companies have launched large-scale programs for deploying CAVs on the road over the next 10 years. CAVs reduce traffic congestion, improve mobility, and decrease vehicular energy consumption and greenhouse gas emissions. Currently in Canada, end users of the transportation industry consume about 30% of Canada's total energy, causing 24% of Canada's greenhouse gas emissions. The availability of V2X (vehicle to vehicle, infrastructure) data, along with vehicle automation, provides a great opportunity for Canadians to save energy and reduce their GHG emissions. The long-term vision of the proposed research is to enable energy-optimal CAVs for cold climate operations via advanced control methods and understanding major dynamics that affect vehicle energy consumption and emissions. The short-term objectives of this program include utilizing V2X data to design optimal and integrated control strategies that includes vehicle powertrain, heating, ventilation, air conditioning (HVAC), vehicle dynamics, and powertrain thermal management. The goal of the proposed research is to provide fundamental contributions towards reducing vehicle fuel consumption up to 34% and substantially reducing greenhouse gas emissions for operation in cold climates. This program centers on CAVs ranging from partial automation (L2) to high automation (L4). The long-term objectives include i) developing cold climate CAV control strategies by leveraging vehicle full autonomy and complete penetration of connectivity data, and ii) developing Artificial Intelligence methods based on peer-learning for integrated powertrain and thermal energy management. Despite the fact that over 85% of Canada's population live in regions with long cold winters, and energy consumption and emissions from vehicles increase drastically in cold climates, very little research has been done in the area of vehicle powertrain and HVAC controls for CAV operation in cold climates. This Discovery program will address the challenges of CAV powertrain and HVAC control, with both conventional and electrified powertrains. The research methodology will include experimental powertrain and vehicle studies, dynamical analysis, advanced predictive control techniques, and methods of machine learning for robust vehicle controls. The program will provide training to 14 highly qualified personnel and include outreach to high school students. The experimental work will be conducted in Edmonton (>1.3M metropolitan population) with average 180 days with the minimum temperature of the day = 0oC. The results will lead to a unique data bank of powertrain, HVAC, and emissions information for CAVs operating in cold climates. This unique data bank will be shared with the public and the research community.