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

适用于寒冷气候的互联自动化车辆和动力系统的智能控制

• 批准号: RGPIN-2020-04403
• 负责人: Shahbakhti, Mahdi
• 金额: $ 2.84万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=760281
• 关键词: Intelligent; Control; Connected; Automated; Vehicles

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.

联网自动驾驶汽车 (CAV) 将成为加拿大交通运输行业的主要组成部分，到 2022 年，在美国和加拿大销售的大多数车辆将配备嵌入式连接。此外，主要汽车公司还启动了部署 CAV 的大规模计划。未来 10 年，CAV 将减少交通拥堵，改善机动性，并减少车辆能源消耗和温室气体排放。目前，在加拿大，交通行业的最终用户消耗的能源约占加拿大总能源的 30%。造成加拿大 24% 的温室气体排放。 V2X（车辆到车辆、基础设施）数据的可用性以及车辆自动化为加拿大人节省能源和减少温室气体排放提供了绝佳的机会。研究旨在通过先进的控制方法并了解影响车辆能源消耗和排放的主要动态，使 CAV 能够在寒冷气候下运行。该项目的短期目标包括利用 V2X 数据设计包括车辆在内的最佳综合控制策略。动力总成，供暖、通风、空调 (HVAC)、车辆动力学和动力总成热管理 拟议研究的目标是为将车辆燃料消耗降低高达 34% 并大幅减少寒冷气候下运行的温室气体排放做出根本性贡献。该计划以从部分自动化 (L2) 到高度自动化 (L4) 的 CAV 为中心，长期目标包括 i) 通过利用车辆完全自主性和连接数据的完全渗透来开发寒冷气候 CAV 控制策略，以及 ii) 开发人工智能。智力基于同行学习的综合动力总成和热能管理方法 尽管加拿大超过 85% 的人口生活在冬季漫长的寒冷地区，并且车辆的能源消耗和排放在寒冷气候下急剧增加，但相关研究却很少。该发现计划将在寒冷气候下 CAV 运行的车辆动力系统和 HVAC 控制领域进行，以解决传统动力系统和电动动力系统中 CAV 动力系统和 HVAC 控制的挑战。研究方法将包括实验动力系统。该项目将提供高素质的人员，包括在埃德蒙顿（> 130 万大城市）开展实验工作。人口），平均 180 天，当天最低温度 = 0oC。 结果将产生一个独特的数据库，其中包含在寒冷气候下运行的 CAV 的动力总成、HVAC 和排放信息。将与公众和研究界分享。