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

利用城市驾驶中的交通状况预测对联网插电式混合动力电动汽车进行能量优化控制

• 批准号: 522964-2017
• 负责人: LashgarianAzad, Nasser
• 金额: $ 5.5万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=691963
• 关键词: Energy; optimal; control; connected; plug

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.

加拿大丰田汽车制造公司（TMMC）和其他加拿大汽车制造商正面临越来越大的压力，要求生产更清洁、更省油的汽车，同时提高驾驶性能和安全性。在一辆车内满足这些广泛而雄心勃勃的标准是汽车公司面临的重大挑战，这将需要在车辆控制系统方面取得重大技术进步。本研究的主要目的是提高能源管理系统（EMS）和自适应巡航控制器（ACC）的性能，在能源效率方面的混合动力电动汽车和插电式混合动力汽车（HEV/PHEV），使他们适应个人的交通情况下，在城市驾驶。对于混合动力/插电式混合动力汽车，EMS和ACC系统对汽车的燃油经济性和能源效率有着重要的影响。这些控制器可以显着改善，通过使用预测控制算法，需要预测的交通参与者的运动在不久的将来。车辆通信和传感系统的新进展可用于获得所需的交通状况预测。我们将使用这些预测的交通参与者的运动信息的开发和行业级评估的新能源优化EMS和生态ACC（生态ACC）系统的HEV/PHEV。除了作为随机过程的交通状况的不确定性之外，在通过针对具有不完整数据的系统的系统控制设计框架开发所提议的控制器时，还将考虑与车辆通信和传感相关的测量不确定性和不准确性。由此产生的EMS和Eco-ACC控制技术，虽然最初设计的丰田普锐斯PHEV将转移到广泛的丰田汽车，如雷克萨斯混合动力汽车和RAV4混合动力汽车由TMMC生产。