NSF/USDOT - ICSST: Development of an Information Technology Based Advanced Monitoring and Inspection System for Air Brakes in Commercial Vehicles Systems for Air Brakes

Darbha Swaroop德州工程实验站基于资讯科技的商用车空气制动系统先进监测及检查系统发展本计划的主要研究目标是为商用车空气制动系统设计新颖的故障检测算法，以期将其应用于自动维修及执行检查的发展，以及实时车载监测系统的发展。这项建议的动机是考虑到预防性和主动车辆安全，因为目前还没有这种用于卡车空气制动器的诊断和监测系统。pi打算开发用于诊断目的的空气制动系统的数学模型，并采用故障检测和隔离（FDI）的分析冗余方法。利用空气制动模型，通过测量踏板位置和车轮速度来预测制动压力；制动压力的实测值与预测值之间的差值将用于评估制动性能的退化。空气制动系统模型将进行实验验证，诊断算法将在PI开发的试验台上实施，该试验台得到了位于俄亥俄州Elyria的Bendix CVS公司和德克萨斯州交通研究所SWUTC项目的支持。在这个项目中开发的工具将适用于各种工业机械。研究生和本科生将参与FDI算法的开发和实施。最后，将测试平台、模型和诊断算法整合到相关的本科和研究生课程中。

Darbha Swaroop Texas Engineering Experiment StationNSF/USDOT: Development of an information technology based advanced monitoring and inspection system for air brakes in commercial vehicles systems for air brakesThe principal research goal of this project is to design novel fault detection algorithms for air brake systems in commercial vehicles with a view towards applying them in the development of automatic maintenance and enforcement inspections and in the development of real-time, on-board monitoring systems. This proposal is motivated by considerations of preventive and active vehicle safety, since no such diagnostic and monitoring system currently exists for air brakes in trucks. The PIs intend to develop a mathematical model of an air brake system for diagnostic purposes and adopt the analytical redundancy approach for Fault Detection and Isolation (FDI). Using the air brake model, brake pressure will be predicted from the measurements of the pedal position and wheel speed; the difference between the measured and predicted values of brake pressure will be used to assess the degradation in braking performance. The air brake system model will be experimentally validated and the diagnostic algorithms will be implemented on the test bench developed by the PI with the support of Bendix CVS Inc., at Elyria, OH and the SWUTC program of the Texas Transportation Institute. The tools developed in this project will be applicable to a wide variety of industrial machinery.Graduate and undergraduate students will be engaged in the development and implementation of FDI algorithms. Finally, the test bench, models and the diagnostic algorithms will be integrated into relevant undergraduate and graduate courses.