I2I Phase I: Testing of real-time aerodynamics sensor system under realistic conditions

I2I第一阶段：在真实条件下测试实时空气动力学传感器系统

• 批准号: 567659-2021
• 负责人: Rival, David
• 金额: $ 9.11万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Idea to Innovation
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=728675
• 关键词: I2I; Phase; Testing; real; time

This project is focused on the development of a real-time aerodynamic drag monitoring/feedback system for heavy-duty vehicles (HDVs) that will result in reduced fuel consumption and greenhouse gas emissions. The system consists of a network of wireless pressure sensors, placed on the HDV's cab surface, and network algorithms that, together with a pre-trained data-driven algorithm, estimate the aerodynamic state of the HDV. This system will enable the driver (or an autonomous driving systems) to optimize the HDV's position relative to other vehicles and reduce the aerodynamic drag. In order to develop a minimum viable product we are undertaking a series of lab and field experiments to determine the optimal position of the pressure sensors and optimize our algorithms, which map the pressure measurements to the actual drag. In parallel, an existing prototype of a wireless pressure sensor will be optimized in terms of size and production costs and a mobile app, which communicates with the HDV's driver in a safe and efficient manner, will be programmed. Final reporting on the development will be undertaken at the end of the project to ensure smooth transition into the next level of product development.

该项目的重点是为重型车辆（HDVS）实时空气动力学阻力监控/反馈系统的开发，这将导致燃油消耗减少和温室气体排放。该系统由放置在HDV驾驶室表面上的无线压力传感器网络和网络算法组成，该算法与预训练的数据驱动算法一起估计了HDV的空气动力学状态。该系统将使驾驶员（或自动驾驶系统）能够相对于其他车辆优化HDV的位置并减少空气动力阻力。为了开发最低可行的产品，我们正在进行一系列实验室和现场实验，以确定压力传感器的最佳位置并优化我们的算法，该算法将压力测量结果映射到实际阻力。同时，将根据规模和生产成本和移动应用程序进行优化的无线压力传感器的现有原型，并以安全有效的方式与HDV的驱动程序进行交流。关于该开发的最终报告将在项目结束时进行，以确保平稳过渡到新的产品开发水平。