PFI-TT: Virtual Torque measurements for heavy duty engine applications

PFI-TT：重型发动机应用的虚拟扭矩测量

• 批准号: 2213959
• 负责人: Muralidhar Ghantasala
• 金额: $ 24.99万
• 依托单位: Western Michigan University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2213959&HistoricalAwards=false
• 关键词: PFI; TT; Virtual; Torque; measurements

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to provide an accurate and reliable virtual torque sensing (VTS) technology integrated with truck engines that can help improve fuel efficiency and reduce emissions while facilitating a more comfortable gear shift. Improved accuracy of real time engine torque may result in a more appropriate gear selection in transmissions thereby delivering reduced fuel consumption and better knowledge about powertrain operation. As exhaust temperature and emission levels depend on both instantaneous and historical engine speed/torque demands, improved accuracy in real time torque measurement helps to address a significant source of harmful emissions. The proposed device is being designed for heavy and medium truck engines fitted in transportation trucks, off-highway vehicles, military trucks, and other vehicles in the transportation sector. This project also seeks to extend the application of this technique to compressed and liquified- natural gas-fueled and hybrid vehicles. Improved accuracy in real time torque measurement will enable engineers to develop more robust analytical models and methods that will help reduce transmission calibration time, while providing opportunities for engine prognostics by identifying unusual variations in engine parameters.The proposed project aims to develop VTS technology providing real-time analyses of engine torque to facilitate optimal gear shifting and provide engine prognostics for vehicles. The three major objectives of this project are: 1) build a minimum viable product with tested and proven features for different engines, 2) perform real-world, on-road fuel efficiency truck testing using VTS enabled improvements, and 3) develop a commercialization path for marketing and obtaining sensor certifications. Historically, the automotive industry has struggled to obtain and utilize inexpensive, accurate, onboard sensors for engine control applications. Better coordination between a vehicle’s engine and transmission may enable smoother gear shifts and improved fuel economy and vehicle performance. A simple, accurate, and cost-effective torque sensor may improve the efficiency and reliability of engine and transmission control. The VTS accuracy relies upon the ability to extract accurate torque values from harmonic information contained within the engine flywheel speed. In this project, artificial intelligence with a machine learning capability will be utilized for accurate and reliable torque analysis. However, the long-term goal of this project is to expand utilization of instantaneous torque measurement methods to better assist engineers in developing advanced control methods for the rapidly developing vehicle mobility network.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这一创新技术转化伙伴关系(PFI-TT)项目的更广泛影响/商业潜力是提供与卡车发动机集成的准确可靠的虚拟扭矩传感(VTS)技术，有助于提高燃油效率和减少排放，同时促进更舒适的换挡。实时发动机扭矩精度的提高可能会导致变速器中更合适的齿轮选择，从而降低油耗并更好地了解动力总成操作。由于排气温度和排放水平取决于发动机的瞬时和历史转速/扭矩需求，因此提高了实时扭矩测量的准确性，有助于解决有害排放的一个重要来源。拟议的装置正在为安装在运输卡车、非公路车辆、军用卡车和交通部门其他车辆上的重型和中型卡车发动机而设计。该项目还寻求将这项技术的应用扩展到压缩和液化天然气燃料以及混合动力汽车。实时扭矩测量精度的提高将使工程师能够开发更强大的分析模型和方法，帮助减少变速器校准时间，同时通过识别发动机参数的异常变化为发动机预测提供机会。拟议的项目旨在开发VTS技术，提供发动机扭矩的实时分析，以促进最佳换挡，并为车辆提供发动机预测。该项目的三个主要目标是：1)制造最低限度可行的产品，具有针对不同发动机的经过测试和验证的功能；2)使用支持VTS的改进进行真实世界的道路燃油效率卡车测试；3)开发用于营销和获得传感器认证的商业化途径。从历史上看，汽车行业一直在努力获得和利用廉价、准确的车载传感器来进行发动机控制应用。车辆发动机和变速器之间更好的协调可能会使换档更加顺畅，并提高燃油经济性和车辆性能。一种简单、准确、经济的扭矩传感器可以提高发动机和变速器控制的效率和可靠性。VTS的准确性依赖于从发动机飞轮速度内包含的谐波信息中提取准确扭矩值的能力。在这个项目中，将利用具有机器学习能力的人工智能来进行准确可靠的扭矩分析。然而，该项目的长期目标是扩大瞬时扭矩测量方法的使用，以更好地帮助工程师为快速发展的车辆移动网络开发先进的控制方法。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。