Vehicle-Infrastructure Integration Enabled Plug-In Hybrid Electric Vehicles for Energy Management

该项目的重点是通过增加插电式混合动力汽车（phev）的数量，与车辆基础设施集成（VII）系统相结合，创造解决方案，以减少美国对化石燃料的依赖。这些VII系统可以作为探测器，提供任何VII监控公路的详细交通数据，这些数据可以被基础设施代理利用，除了从其他来源接收数据外，还可以为这些车辆提供实时行程信息。PHEV-VII车辆利用这些数据来预测其行驶路径上的加速曲线，用于开发能量管理控制策略。本研究的目的是基于插电式混合动力汽车的行程预测信息，推导出一种简单灵活的插电式混合动力汽车的能量管理控制策略，以优化燃料消耗和总能耗，使总行程成本最小化。研究团队将通过加权多目标成本函数创建交通改道策略，该策略允许利用最大道路容量来最小化新的插电式混合动力车队的每日总能源需求、行驶时间和每日总成本。该项目致力于基础研究，开发一种完善的数学、计算和技术策略，利用实时提供的预测行程信息创建插电式混合动力汽车的能源管理框架。该项目包括：(1)开发一个框架，将插电式混合动力汽车与自动驾驶汽车全面集成，作为灵活的车载能源管理策略的一部分，该策略使用即时优化方法；（ii）通过交通改道策略为插电式混合动力汽车提供稳健和响应性的性能；（三）建立能源管理、交通运营和数据通信的综合建模、仿真和评估框架。该项目还包括根据平均行驶距离、燃料和电力以及成本，确定大幅减少每日燃料消耗所需的插电式混合动力车的比例。这项研究有望减少美国对石油和其他产生温室气体的燃料的依赖，减少污染，节约能源，最大限度地降低长期生活成本，并改善驾驶条件。该项目为验证和实施插电式混合动力汽车的综合能源管理提供了机会，并结合了VII监控的高速公路的交通数据。它还将解决成本限制、应用于大量系统（可能是数百万辆汽车）以及实现与当今消费者期望一致的稳健性的需求等重要挑战。在最根本的层面上，本研究的影响在于设计一种插电式混合动力系统，同时兼顾车内能量管理和行程可预测性。研究人员认为，通过该项目开发的重要基础知识将作为未来工作的开端，将在数年而不是数十年内产生非常接近可执行行动计划的结果。该项目将包括研究生（由pi共同指导）和本科生（通过克莱姆森大学的创造性探究计划），这是一个多学期的承诺，由一名教师或一组教师指导，在一个同伴小组中工作。参与这项工作的学生将学习批判性思维技能，并对在线道路交通管理方法有深入的了解。他们还将从事汽车工程研究，旨在最大限度地减少化石燃料的使用，最大限度地利用替代燃料，最大限度地提高行程可预测性，并整合这些学科，以实现能源可持续性和行程可靠性目标。

The focus of this project is to create solutions to reduce US dependence on fossil fuels via anticipated increases in the number of Plug-in Hybrid Electric Vehicles (PHEVs) for integration with a Vehicle Infrastructure Integration (VII) system. Such VII systems can act as probes, providing detailed traffic data of any VII monitored highway, which can be utilized by infrastructure agents, in addition to receiving data from other sources, to provide real-time trip information to these vehicles. PHEV-VII vehicles utilize these data to predict acceleration profiles in their driving path for use in developing an energy management control strategy. The objective of this research is to derive a simple and flexible energy management control strategy for PHEVs based on its predicted trip information to optimize fuel consumption and the total energy used, to minimize the total cost of a trip. The research team will create a traffic rerouting strategy, through a weighted multi-objective cost function, which allows utilizing maximum road capacity to minimize the daily total energy requirements, travel times and the daily total cost for this new PHEV vehicle fleet. The project pursues fundamental research to develop a sound mathematical, computational, and technological strategy to create an energy management framework of PHEVs using predicted trip information provided in real-time. The project involves (i) developing a framework for a comprehensive integration of PHEVs with VII that is part of a flexible in-vehicle energy management strategy, which uses an instantaneous optimization method; (ii) providing a robust and responsive performance of PHEVs through traffic rerouting strategies; and (iii) creating an integrated modeling, simulation and evaluation framework of energy management, traffic operations and data communications. This project also involves determining the percentage of PHEVs needed to substantially reduce daily fuel consumption as a function of average distance traveled, fuel and electricity and costs. This research is expected to potentially reduce US reliance on petroleum and other greenhouse gas-producing fuels, reduce pollution, save energy, minimize the long term cost-of-living expenses, and improve driving conditions. This project provides an opportunity to validate and implement integrated energy management of PHEVs with traffic data from VII monitored highways in a real-world setting. It will also address the important challenges of cost constraints, the application to a large number of systems (potentially millions of vehicles), and the need to achieve a degree of robustness consistent with today's consumer expectations. At the most fundamental level, the impact of this research lies in the design of a PHEV system with simultaneous objectives related to in-vehicle energy management and trip predictability. The investigators submit that the significant fundamental knowledge developed through this project will serve as a beginning of future work that will yield results very close to implementable action plans, within years, not decades. The project will involve both graduate students who will be co-advised by the PIs, and undergraduate students via Clemson University's Creative Inquiry initiative, a multisemester commitment to work in a peer group, mentored by a faculty member or a group of faculty members. Students involved in this effort will learn critical thinking skills as well as gain a deep understanding of the methods of on-line roadway traffic management. They will also engage in automotive engineering research with the aim of minimizing the usage of fossil fuel and maximizing the use of alternative fuels, maximizing trip predictability and integrating these disciplines to attain energy sustainability and trip reliability goals.