详情

原文传递 Computer Controlled Poor Driveability on Demand Training Vehicle.

题名：	Computer Controlled Poor Driveability on Demand Training Vehicle.
作者：	Rengarajan, S.; Gankov, S.; Fritz, J.; Toucheck, K.
关键词：	Driveability, Reconfigurable IO Modules (RIO), Gasoline direct injection, National Instruments (NI), Compact RIO (cRIO), Graphical User Interface (GUI), On Board Diagnostic (OBD), Engine Control Module (ECM)
摘要：	Southwest Research Institute (SwRI) modified a 2014 Ford Fusion vehicle to perform driveability events on-demand in accordance with procedures detailed in Coordinating Research Council (CRC) Cold-Start and Warmup E85 Cold Ambient Temperature Driveability Program. Four driveability events at three different severity levels as shown in Table 1 were enabled by intercepting the accelerator pedal and ignition timing signals of the stock vehicle’s engine control module. Real-time software enabling the driveability events was written in LabVIEW language and deployed on a National Instruments (NI) Compact RIO (cRIO) 9035 controller. A Graphical User Interface (GUI) was deployed on a Microsoft Surface tablet to communicate with the controller. Driveability raters recommended by CRC helped calibrate and validate the system on-site at SwRI and at an external test track over a period of 2 weeks. The raters were pleased with the overall system performance. The primary project objectives were met successfully. In addition to the required scope of work, SwRI performed a repeatability study to draw statistically significant conclusions. Data was collected over 2266 events and a correlation study was performed comparing triggered driveability events versus events reported by the raters. The study revealed accuracy at an event level was about 95%. This means, for example, if a hesitation event was triggered, the raters would identify it as a hesitation 95% of the time. Differences in average sensitivity of raters contributed to lower severity accuracies. Quantification of various driveability events performed as part of this project would enable building a “gold” standard for training future raters. Results from the testing and conclusions are detailed in this report.
报告类型：	科技报告