Vehicle-Infrastructure Integration Enabled Plug-In Hybrid Electric Vehicles for Energy Management
车辆与基础设施集成支持插电式混合动力电动汽车的能源管理
基本信息
- 批准号:0928744
- 负责人:
- 金额:$ 47.04万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2009
- 资助国家:美国
- 起止时间:2009-08-15 至 2013-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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.
该项目的重点是通过增加插电式混合动力电动汽车(PHEV)的数量来减少美国对化石燃料的依赖,以便与车辆基础设施集成(VII)系统集成。这样的VII系统可以充当探测器,提供任何VII监控的高速公路的详细交通数据,除了从其他来源接收数据之外,基础设施代理还可以利用这些数据来向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中的加速度曲线,以用于开发能量管理控制策略。本研究的目的是推导出一个简单而灵活的能源管理控制策略的基础上,其预测的行程信息,以优化燃料消耗和总能源使用,以最大限度地减少总成本的行程。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大限度地减少新PHEV车队的每日总能源需求,旅行时间和每日总成本。该项目致力于基础研究,以开发合理的数学,计算和技术策略,使用实时提供的预测行程信息创建PHEV的能源管理框架。该项目涉及(i)开发一个框架,用于PHEV与VII的全面集成,这是灵活的车载能源管理策略的一部分,使用瞬时优化方法;(ii)通过交通改道策略提供PHEV的稳健和响应性能;以及(iii)创建一个集成的建模,仿真和评估框架,用于能源管理,交通运营和数据通信。该项目还涉及确定大幅度减少每日燃料消耗所需的插电式混合动力汽车的百分比,作为平均行驶距离、燃料和电力以及成本的函数。这项研究有望减少美国对石油和其他温室气体产生燃料的依赖,减少污染,节约能源,最大限度地减少长期生活费用,并改善驾驶条件。该项目提供了一个机会,以验证和实施一体化的能源管理的PHEV与交通数据从VII监测高速公路在现实世界的设置。它还将解决成本约束、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鲁棒性的需求等重要挑战。 在最基本的层面上,本研究的影响在于PHEV系统的设计,同时具有与车载能量管理和行程可预测性相关的目标。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,在几年内而不是几十年内产生非常接近可实施行动计划的结果。该项目将涉及两个研究生谁将共同建议的PI,和本科生通过克莱姆森大学的创造性调查倡议,一个多学期的承诺,在一个同龄人小组工作,由一名教师或一组教师的指导。参与这项工作的学生将学习批判性思维技能,并深入了解在线道路交通管理的方法。他们还将从事汽车工程研究,目的是最大限度地减少化石燃料的使用,最大限度地使用替代燃料,最大限度地提高旅行的可预测性,并整合这些学科,以实现能源可持续性和旅行可靠性目标。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Mashrur Chowdhury其他文献
Data-Driven Defenses Against Adversarial Attacks for Autonomous Vehicles
数据驱动的自动驾驶汽车对抗性攻击防御
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Omar A. Azim;Lex Baker;Reek Majumder;Abyad Enan;S. Khan;Mashrur Chowdhury - 通讯作者:
Mashrur Chowdhury
Analysis of cost estimation disclosure in environmental impact statements for surface transportation projects
- DOI:
10.1007/s11116-010-9313-x - 发表时间:
2010-12-28 - 期刊:
- 影响因子:3.300
- 作者:
Joseph Sturm;Mashrur Chowdhury;Anne Dunning;Jennifer Ogle - 通讯作者:
Jennifer Ogle
WIP: A First Look At Employing Large Multimodal Models Against Autonomous Vehicle Attacks
WIP:首次尝试使用大型多模式模型来应对自动驾驶汽车攻击
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
Mohammed Aldeen;Pedram MohajerAnsari;Jin Ma;Mashrur Chowdhury;Long Cheng;Mert D. Pes´e - 通讯作者:
Mert D. Pes´e
Impact of Minimum Driveway Spacing Policies on Safety Performance: An Integrated Traffic Micro-Simulation and Automated Conflict Analysis
- DOI:
10.1260/2046-0430.3.3.249 - 发表时间:
2014-09-01 - 期刊:
- 影响因子:
- 作者:
Chu C. Minh;Nathan Huynh;Mashrur Chowdhury;Jennifer H. Ogle;Wayne A. Sarasua;William J. Davis - 通讯作者:
William J. Davis
Comparison of Models with and without Roadway Features to Estimate Annual Average Daily Traffic at Non-Coverage Locations
比较具有和不具有道路特征的模型来估计非覆盖位置的年平均每日交通量
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Jing Wang;Ryan DeVine;Nathan Huynh;Weimin Jin;G. Comert;Mashrur Chowdhury - 通讯作者:
Mashrur Chowdhury
Mashrur Chowdhury的其他文献
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{{ truncateString('Mashrur Chowdhury', 18)}}的其他基金
Planning Grant: Engineering Research Center for Computer And Network RESIliency and Security for Transportation (CAN-RESIST)
规划资助:计算机和网络弹性与交通安全工程研究中心(CAN-RESIST)
- 批准号:
1937000 - 财政年份:2019
- 资助金额:
$ 47.04万 - 项目类别:
Standard Grant
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