SBIR Phase I: Sensor and Control System Development and Integration for Semi-Truck Fuel Savings Device

SBIR第一阶段：半卡车节油装置传感器和控制系统开发与集成

• 批准号: 1940360
• 负责人: Sandra Manosalvas-Kjono
• 金额: $ 22.5万
• 依托单位: AEROMUTABLE CORPORATION
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-15 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1940360&HistoricalAwards=false
• 关键词: SBIR; Phase; Sensor; Control; System

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to reduce fuel consumption and improve safety in the trucking industry while increasing profitability. Over 70% of US freight tonnage is moved by the trucking industry, but at highway speeds, aerodynamic drag uses over 65% of the total vehicle energy. This project will develop a network of sensors and an artificial intelligence (AI-)control system. This will be integrate with an experimental device that modifies the aerodynamic behavior of semi-trucks using air injection, enabling continuously optimized aerodynamic performance. This project will create a sensor system able to describe the micro-climate of a semi truck in real time, and an AI-control system to determine the trailer’s best aerodynamic profile based on current operating conditions. This system would create an energy savings for all US fleets of up to 3B+ gallons of unburned diesel for an annual total addressable market of $20B.This SBIR Phase I project proposes development of an aerodynamic add-on prototype for trucks to save fuel by dynamically changing the trailer’s aerodynamic profile. To capture the operating conditions around the trailer in real time, this project will develop a sensor system to accurately measure the environment surrounding the vehicle. This project will explore relationships among environmental measurements, optimize the number and location of sensors, conduct the relevant systems engineering studies, and build a prototype.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.

这个小型企业创新研究（SBIR）项目的更广泛的影响/商业潜力是减少燃料消耗，提高卡车运输行业的安全性，同时提高盈利能力。超过70%的美国货运吨位是由卡车运输业运输的，但在高速公路上，空气动力阻力消耗了超过65%的车辆总能量。该项目将开发一个传感器网络和一个人工智能（AI）控制系统。 这将与一个实验装置相结合，该装置使用空气喷射来改变半卡车的空气动力学行为，从而实现持续优化的空气动力学性能。该项目将创建一个能够真实的描述半挂卡车微气候的传感器系统，以及一个基于当前操作条件确定拖车最佳空气动力学轮廓的AI控制系统。该系统将为所有美国车队节省高达30亿加仑的未燃柴油，每年可达200亿美元的市场。SBIR第一阶段项目提出开发一种用于卡车的空气动力学附加原型，通过动态改变拖车的空气动力学轮廓来节省燃料。为了真实的捕捉拖车周围的运行状况，本项目将开发一种传感器系统，以精确测量车辆周围的环境。该项目将探索环境测量之间的关系，优化传感器的数量和位置，进行相关的系统工程研究，并建立一个原型。该奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。