Data Acquisition System for Electric Vehicle's Driving Motor Test Bench Based on VC++

Song, Qiang; Chenguang, Lv

doi:10.1016/j.phpro.2012.05.277

Cited by 5 publications

(1 citation statement)

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“…This dosing is regulated by controlling the amount of air and fuel that enters, so it is necessary to apply accurate and reliable control systems [7], which mostly require sensors whose prices mean high costs [8]. In addition to this, for the visualization of physical phenomena, thanks to advances in computational technology and industrial instrumentation, it is generally used a data acquisition system or also known DAQ [9], basically given by a physical input signal captured by a sensor, a DAQ hardware, which receives the signal, which may be this current, voltage, resistance or other electrical attribute that varies with time. Finally, a computer with a programmable software that allows to store and visualize the measured engineering variable.…”

Section: Introductionmentioning

confidence: 99%

Implementation of a fuel measurement system based on the gravimetric principle for applications in engine test bench

Duarte¹,

Valencia²,

Gutiérrez³

et al. 2018

ces

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This paper documents the implementation process of a fuel measurement system based on the gravimetric principle for applications in Engine Test Bench. To do this, the design of the measurement hardware consists of a gravimetric scale with serial output, feed pump, and a valve; which interact with each other thanks to the programming developed in the Arduino UNO® environment, it is possible to guarantee protection against possible disturbances that may affect the data measured by the scale by means of an acrylic structure. For the visualization and interaction with the information collected by the meter, an executable application 3782 Jorge Duarte et al. is made using the LabView ™ computational tool. Finally, a series of runs are carried out to guarantee compatibility with the existing testbench in the laboratory and to demonstrate the functionality of the system.

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Section: Introductionmentioning

confidence: 99%