Dataset Information

Development and implementation of virtual instrumentation based on LabView applied to compression ignition engines operated with diesel-biodiesel blends.

ABSTRACT: This work shows the implementation and development of a set of virtual instruments focused on recording the physical parameters of a compression ignition engine that operates with diesel-biodiesel, 95% diesel and 5% soybean biodiesel. The components of the engine are constituted by several individual virtual instruments (VI) with the objective of registering parameters such as temperature (VITM), revolutions per minute (VIMRPM), fuel consumption (VIMFC), emission of gases such as oxygen (VIMO) and rust nitric (VIMNO). As a result of the research, the software development, hardware of each of the VIs is presented using the virtual programming platform Labview 2015®, the calibration of the O₂ sensors, NO and the result of the operation of the engine at 850 rpm constant an ambient temperature of 25??, a relative humidity of 40% and an operating temperature at the engine head of 65??, obtain a fuel consumption of 0.0616?l/min and an average emission of O₂ 10% and for the NO 540?ppm. •Implementation of virtual instrument focused on evaluate the physical parameters of CI engine operate with diesel-biodiesel.•The engine runs at 850?RPM under controlled conditions of 25?? and a 40% RH with B5 mixture.•Engine emissions are constant and stable at 10% Vol. O₂ and 540?ppm of NO.

SUBMITTER: Perez A

PROVIDER: S-EPMC6909051 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development and implementation of virtual instrumentation based on LabView applied to compression ignition engines operated with diesel-biodiesel blends.

Pérez Armando A Montero Gisela G Ramos Irigoyen Rogelio R Garcia Conrado C Coronado Marcos M Rodriguez Jose J

MethodsX 20191004

This work shows the implementation and development of a set of virtual instruments focused on recording the physical parameters of a compression ignition engine that operates with diesel-biodiesel, 95% diesel and 5% soybean biodiesel. The components of the engine are constituted by several individual virtual instruments (VI) with the objective of registering parameters such as temperature (VITM), revolutions per minute (VIMRPM), fuel consumption (VIMFC), emission of gases such as oxygen (VIMO) a ...[more]

PMID: 31871913

Similar Datasets

Project description:Diesel exhaust emissions have been reported for a number of engine operating strategies, after-treatment technologies, and fuels. However, information is limited regarding emissions of many pollutants during idling and when biodiesel fuels are used. This study investigates regulated and unregulated emissions from both light-duty passenger car (1.7 L) and medium-duty (6.4 L) diesel engines at idle and load and compares a biodiesel blend (B20) to conventional ultralow sulfur diesel (ULSD) fuel. Exhaust aftertreatment devices included a diesel oxidation catalyst (DOC) and a diesel particle filter (DPF). For the 1.7 L engine under load without a DOC, B20 reduced brake-specific emissions of particulate matter (PM), elemental carbon (EC), nonmethane hydrocarbons (NMHCs), and most volatile organic compounds (VOCs) compared to ULSD; however, formaldehyde brake-specific emissions increased. With a DOC and high load, B20 increased brake-specific emissions of NMHC, nitrogen oxides (NOx), formaldehyde, naphthalene, and several other VOCs. For the 6.4 L engine under load, B20 reduced brake-specific emissions of PM2.5, EC, formaldehyde, and most VOCs; however, NOx brake-specific emissions increased. When idling, the effects of fuel type were different: B20 increased NMHC, PM2.5, EC, formaldehyde, benzene, and other VOC emission rates from both engines, and changes were sometimes large, e.g., PM2.5 increased by 60% for the 6.4 L/2004 calibration engine, and benzene by 40% for the 1.7 L engine with the DOC, possibly reflecting incomplete combustion and unburned fuel. Diesel exhaust emissions depended on the fuel type and engine load (idle versus loaded). The higher emissions found when using B20 are especially important given the recent attention to exposures from idling vehicles and the health significance of PM2.5. The emission profiles demonstrate the effects of fuel type, engine calibration, and emission control system, and they can be used as source profiles for apportionment, inventory, and exposure purposes.

Project description:Homogeneous Charge Compression Ignition (HCCI) combustion is a potential candidate for dealing with the stringent regulations on vehicle emissions while still providing very good energy efficiency. Despite the promising results obtained in preliminary studies, the lack of autoignition control has delayed its launch in the engine industry. In the development of the HCCI concept, the availability of reliable computer models has proved extremely valuable, due to their flexibility and lower cost compared with experiments using real engines. In order to obtain the best formulation of a fuel surrogate formulated with n-heptane, toluene and cyclohexane that efficiently estimate the autoignition behaviour, regression adjustments are made to the Root-Mean-Square Errors (RMSE) of experimental Starts of Combustion (SOC) from the modeled SOC. The canonical form of the Scheffé polynomials is widely used to fit the data from mixture experiments, however the experimenter might have only partial knowledge. In this paper we present the adaptation of the robust methodology for possibly misspecified blending model and an algorithm to obtain tailor-made optimal designs for mixture experiments, instead of using standard designs which are indiscriminately employed, to make good estimations of the parameters blending model. We maximize the determinant of the mean squared error matrix of the least square estimator over a realistic neighbourhood of the fitted regression mixture model. The maximized determinant is then minimized over the class of possible designs, yielding an optimal design. Thus, the computed desings are robust to the exact form of the true blending model. Standard mixture designs, as the simplex lattice, are around 25% efficient for estimation purposes compared with the designs obtained in this work when deviances from the considered model occur during the experiments. Once an optimal-robust design was selected (based on the level of certainty about model adequacy), we computed the optimal mixture that best reproduces the combustion property to be imitated. Optimal mixtures obtained when the considered model is inadequate agree with the results achieved in empirical studies, which validates the methodology proposed in this work.

Dataset Information

Development and implementation of virtual instrumentation based on LabView applied to compression ignition engines operated with diesel-biodiesel blends.

Publications

Development and implementation of virtual instrumentation based on LabView applied to compression ignition engines operated with diesel-biodiesel blends.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets