Revista Científica Interdisciplinaria Investigación y Saberes
2023, Vol. 13, No. 3 e-ISSN: 1390-8146
Published by: Universidad Técnica Luis Vargas Torres
How to cite this article (APA):
Lara, O., Hicaiza, O., Beltran, C., Lozada, J. (2023)
Development of Octave programming to calculate the forces in the structural elements
of a scissor lift table, Revista Científica Interdisciplinaria Investigación y Saberes, 13(3)
95-113.
Estimation of CO2 emissions in cabs with 1600 cc cylinder under
efficient driving parameters in the city of Cuenca, using the ive model
IVE
Estimación de emisiones de CO2 en taxis con cilindradas de 1 600 cc bajo parámetros
de conducción eficiente en la ciudad de Cuenca, utilizando el modelo IVE
Orlando Alfonso Lara Medina
MSc. Instituto Superior Tecnológico Simón Bolívar, Guayaquil Ecuador , o_lara@istsb.edu.ec,
https://orcid.org/0000-0003-1854-8536
Oscar Fabricio Hicaiza Yugcha
MSc. Instituto Superior Tecnológico Simón Bolívar, Guayaquil Ecuador , o_chicaiza@istsb.edu.ec,
https://orcid.org/0000-0002-4170-2186
Carlos Vinicio Beltran Herrera
MSc. Instituto Superior Tecnológico Simón Bolívar, Guayaquil Ecuador , c_beltran@istsb.edu.ec,
https://orcid.org/0009-0006-2274-4504
Jonathan Samuel Lozada Pilco
MSc. Instituto Superior Tecnológico Simón Bolívar, Guayaquil Ecuador , j_lozada@istsb.edu.ec,
https://orcid.org/0000-0002-2407-0201
Global warming is currently considered to be the main problem on a
global scale, which is mainly generated by the concentration of
anthropogenic greenhouse gases in the atmosphere. Transportation
is responsible for approximately 25% of global CO2 emissions. Based
on this reality, the literature proposes several strategies to try to
mitigate the generation of these gases in the transportation sector.
The results were obtained through a sample of cabs and will be
instrumented with GPS and data logger equipment to obtain the
parameters that feed the model.
Keywords:
Newton of motion, program, arithmetic
Abstract
Received 2023-04-09
Revised 2023-05-11
Published 2023-09-07
Corresponding Author
Oscar Fabricio Hicaiza Yugcha
o_lara@istsb.edu.ec
Pages: 95-113
https://creativecommons.org/lice
nses/by-nc-sa/4.0/
Distributed under
Copyright: © The Author(s)
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
Revista Científica Interdisciplinaria Investigación y Saberes , / 2023/ , Vol. 13, No. 3
96
Resumen
En la actualidad el calentamiento global es considerado como la
principal problemática de escala global, que principalmente es
generada por la concentración de gases de efecto invernadero de
origen antropogénico en la atmosfera. El transporte es responsable
de aproximadamente el 25 % de las emisiones de CO2 globales. A
partir de esta realidad la literatura plantea varias estrategias para
tratar de mitigar la generación de estos gases en el sector de
transporte. Los resultados se obtuvieron mediante una muestra de
taxis y se instrumentarán con equipos GPS y data logger para obtener
los parámetros que alimenten el modelo.
Palabras clave
Newton del movimiento, programa, aritmética
Introduction
James Cook in 2013 published in the scientific journal Environmental
Research Letters an article entitled "Quantifying the consensus on
anthropogenic global warming in the scientific literature" where he
analyzed the existing literature on climate change the consensus on
the anthropogenic influence on this phenomenon, coming to
determine that of 12 000 publications 97.1% point to the fact that
climate change is a direct consequence of human activity and its
greenhouse gas (GHG) emissions and in particular carbon dioxide
(CO2) (Justin D. et al., 2016)..
In 2015, around 1.1 billion vehicles were in circulation worldwide and
it is expected that by 2 025 this figure will increase to 2 billion (Justin
D. et al., 2016, p. 204).. According to the international organization of
automobile manufacturers the growth rate of the vehicle fleet
worldwide is 4 %, as a consequence of that in 2017 reached the figure
of 100 million vehicles produced in one year (OICA, 2015). In Ecuador,
the rates are higher since there is a growth rate of 15.5 % per year
and in 2017 it reached over 2 million registered vehicles (Baldeón,
2016).. This has resulted in Ecuador's transportation sector being the
sector with the highest energy demand with about 45 million barrels
of oil equivalent. (Renobable, 2019)..
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
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For this reason, there is a need for strategies and policies that
contribute to the mitigation of fossil fuel use in transportation and
therefore to the reduction of GHGs. There are several strategies such
as modal shift in transportation, eco-driving or carpooling and also
several policies such as green taxes, vehicle traffic taxes or incentives
for electric vehicles that have shown good results. (L. I. Rizzi and C.
De La Maza, 2017)..
To generate a baseline of CO2 emissions, direct (directly at the
tailpipe) and indirect (simulation) measurement techniques can be
used. Direct measurements can be done through laboratories or on-
board measurement systems (PEMS), however, the problem with
these is the related costs. On the other hand, there are the indirect
methods that are responsible for estimating emissions from
parameters that feed mathematical models the main advantage of
these measurements is that they do not incur high costs in their
implementation. (Kumar, 2017)
With this background, some questions arise that must be addressed
in the importance of providing partial solutions to the great problem
of energy consumption and emissions from transportation, questions
such as.
What is the average CO2 emissions factor for a specific fleet, by what
percentage can fuel consumption and CO2 emissions be reduced
through the implementation of a strategy or policy?
With respect to indirect emission estimation methods, several studies
conclude that for countries complying with EURO 3 regulations, the
best option is the International Emissions Model (IVE), since it adapts
to these technologies, and also allows the information on driving
habits to be loaded directly into the program, through the VSP Bines
(Cossio, 2012).
There are several studies in countries such as China, India, Mexico,
Peru, Chile, among others, in which the IVE model has been used to
determine emission factors and emission inventories, as well as
databases for climate control and air quality control (Davis D. et al.,
2005). (Davis D. et al., 2005).
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
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Methodology
Study area
This research was conducted in the city of Cuenca located in the
center of the province of Azuay. Reporting the following data as:
latitude between 2º 53' 57", temperature of 16.1 C º and with an
altitude of 2 500 meters at sea level.
Materials used
The following materials were acquired to implement the cab fleet:
ELM 327 interface
Smart Phone with TORQUE PRO application
SOTFWARE IVE
Cab fleet
The method applied was based on the review of literature on CO2
emission factor estimation models. For this activity a literature review
was carried out in the databases of indexed journals of the
Universidad del Azuay, the search was concentrated in the SCOPUS
and DOAJ databases. Once the largest amount of literature was
reviewed, the most relevant articles in reference to the estimation of
CO2 emissions factors were selected. According to a preliminary
literature review, the methodology used by the IVE Model was
determined as one of the most appropriate for the quantification of
emission factors.
Methodology selection
Based on the evaluation of the different methodologies, one of them
was chosen to be applied to the local cab fleet. It is important to
highlight that the previous literature review and analysis work has
defined the IVE model as a relevant method for the determination of
the CO2 emissions factor. The methodology was analyzed in depth.
In this case, the IVE model was evaluated to understand how it works,
how it is used, the characterization of the variables demanded by the
model and the results delivered by the application. In order to define
the model for estimating emission factors, it was necessary to have
information on how the ECO-Driving efficient driving parameters
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
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were carried out. For this purpose, literature on the subject was
searched and the most relevant was analyzed in order to define the
driving method in the cab fleet, and in this activity the type of
strategies or techniques used for the implementation of efficient
driving in the established fleet was selected.
Figure 1
. Process flow diagram of the methodology.
In the flowchart presented in Figure 1. Details the sequence
performed in the process of the methodology developed in the
research of CO2 estimation in the cab fleet of 1600cc. With eco-
driving parameters.
2.4 Techniques for the application of efficient driving.
Several techniques were applied to obtain an efficient driving of the
vehicle. In this way, a decrease in fuel consumption and pollutant
emissions can be evidenced.
Starting the engine without depressing the accelerator pedal, on an
electronic throttle regulates the ignition conditions.
Shift gears as soon as possible, and be aware of the number of
revolutions at which you are going to change gears at low revolutions.
For gasoline engine vehicles, change gear before 2 500 revolutions
per minute.
When shifting gears, the manner of application of the accelerator
pedal must be carried out as necessary to continue the acceleration
process of the vehicle.
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
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Maintaining a uniform speed, when the vehicle is accelerated and has
sudden braking, energy is lost at the time of restarting the car, the
transformation of energy by propulsion results in higher fuel
consumption and increased pollutant emissions. (Larrazábal, 2004)
The sample of the cab fleet to be used for the data collection was
determined. For this purpose, models were established that comply
with the established displacement and have the capacity to support
the necessary instrumentation for the data collection. The number of
cabs expected to be used is 18 vehicles (9 of 1400 cc and 9 of 1600
cc) that circulated 24 hours a day.
Vehicle fleet instrumentation
The IVE model basically uses GPS parameters. For this purpose, each
cab was installed with a cell phone with the torque pro application
and the ELM 327, since in this way the information from the cell phone
can be stored for later processing. The advantage of having the ELM
is that apart from the latitude, longitude and altitude data, it also
provides information on fuel consumption, which is used to evaluate
autonomy and savings.
Definition of variables that will feed the IVE model requires
environmental parameters such as humidity and temperature, as well
as some variables such as fuel type and composition, all these
variables will be obtained from current regulations and local
government information. The IVE model also included information on
fleet technology and the type of maintenance of the fleet, for which
information was collected from each of the vehicles involved.
To develop the road tests with the instrumentation implemented in
each cab, the information will be collected during a period of two
consecutive months in order to obtain as much information as
possible. The logistics of storing the information for its later
processing was in charge of the teacher on a weekly basis.
In order to carry out the driving tests efficiently, a training workshop
was held. The drivers carried out this mode of driving in three days,
so that in the second month of data collection the same process
would be developed in order to collect the information from the first
month; however, the second month is characterized under the
parameters of efficient driving.
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
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Information processing
The emissions estimation procedure in the IVE model consists of
processing a series of correction factors that are adapted to estimate
pollutants in a wide variety of cars and types of technologies.
Determine the base emissions factor recorded in the fleet input data,
i.e. vehicle technology, air conditioning. Add pollution factor data by
technology. In addition, the locality input data must be adjusted.
Calculation by temperature, slope, vehicle maintenance, distance and
location. It is advisable to make adjustments for fuel quality also
important is the record of distribution of Soak driving patterns.
The emission factor data is multiplied by the curves factor by filtering
correction by the distance traveled by each vehicle for each
technology, this equation multiplies the base factors (B) by the series
of correction factors (K) to estimate the base emission factor (Q) for
each type of cab the correction factors can be recorded in several
categories also depends on the value of each of the correction factors
by the selected entries in the locality file in the model as indicated in
(1). (Center, 2008).
Q[t] = B[t] * K (1) [t] * K (2) [t] * ......K(x) [t] (1)
Driving patterns.
The important variables for determining driving patterns depend on
the speed, acceleration and deceleration of the cab fleet, thus
increasing the emissions generated by the vehicle.
The emissions caused by the vehicle is generated by a function of the
power and stress of the engine present these variations that can
increase CO2 emissions which is the importance of this study in
applying efficient driving parameters in the cab fleet prior training of
drivers. (Center, 2008, pp. 10-15)
The patterns depend on two important parameters, which are:
Vehicle Specific Power (VSP).
Engine stress.
These two parameters are obtained by determining the type of
vehicle, the variables such as altitude, speed per second, if the slope
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
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is added it can be presented or assumed as zero in the equation as
indicated in (2).
VSP = v[1.1 + 9.81 (atan(sin(slope)))+0.132]+0.000302v3 (2)
Where: Slope = (ht = o - ht = -1) vt =1 to o seconds
V = velocity (m/s)
a = acceleration (m/s2)
h = altitude (m)
Speed data can be collected on the fleet of cabs instrumented with
location unit (GPS). Speed information is organized by congestion
levels, type of roadway, time of day.
Soak starting patterns
Soak periods occur before a start occurs. In the IVE model, a start is
referred to as a cold start, which means that the engine is completely
cold. A cold start causes an increase in emissions because the engine
has to reach its warm-up point.
Once the data collection was completed using the ELM327 device,
we proceeded to the creation of a database. In the first instance, the
files (SCV) were classified according to the cab from which they come,
and then proceeded with a filter of empty cells or erroneous data,
which was done programmatically due to the large number of files.
A database was created and stored in PostgreSQL, which is a program
for advanced data support and supports a high level that optimizes
good storage performance and data processing, thus an application
was programmed in Matlab capable of importing, sorting the data,
transforming the units if necessary and saving them in a database
table. The database consists of approximately 20.5 million rows of
data, each row containing vehicle identification information, date and
time, GPS position, altitude and vehicle operating parameters. In this
study, CO2 emissions will be analyzed in two scenarios: first, a
scenario with favorable traffic conditions and second, a scenario in
which there is traffic, ordered from lowest to highest.
The average velocities of each hour of data checking that they
correspond to a normal distribution.
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
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The best scenario corresponds to the first quartile of the normal
distribution of the data sample there is an analysis of the 1,600 cc cab
fleet by efficient driving parameters that was performed at the second
month where the information process was carried out.
The worst case scenario corresponds to the third quartile of the
normal distribution of the data sample. They are represented in
quartiles so that the data results are close to the most realistic ones.
The speed and altitude data from the representative runs go through
an outlier filter and curve smoothing before being processed for VSP
bin calculation.
Figure 2 shows an example of the procedure where the filtering and
smoothing of the curve was performed by determining the speed and
time variables.
Figure 2.
Filtering and smoothing of the velocity/time curve.
Figure 3. Represents the filtering and smoothing variables of the
altitude and time curve, using information processed in the IVE
model.
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
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Figure 3.
Filtering and smoothing of the altitude/time curve.
2.9 Calculation of CO2 emissions through efficient driving
parameters.
To calculate CO2 emissions, the IVE model software was used: First
the VSP bins are calculated, with the help of a tool developed at the
University of Azuay, by entering information in the IVE model, the
vehicle fleet corresponds to the vehicle fleet technology 127, (this is
the most commonly used vehicle technology among cabs in the city),
which describes a light gasoline vehicle, multipoint injection, with
anti-pollution systems such as catalyst, EGR exhaust gas recirculation
and PCV Carter Positive Vent Valve.
A temperature of 16.1 °C and a relative humidity of 60 % were also
used, which correspond to the average record for the city. (EMOV,
2017)
For the fuel quality data, the stipulations of the Ecuadorian technical
standard NTE INEN 935 were considered; this standard establishes
the maximum limits for the different components of gasoline in
Ecuador. The sulfur content is set at 650 ppm, the benzene content is
1 %, it does not contain lead and the oxygen content is 2.7 %. (INEN,
2016)
Cabs 1600 cc efficient driving
A sample of 1,286 data on average speeds for each hour of travel was
evidenced, the distribution of data is shown in Figure 4.
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
Revista Científica Interdisciplinaria Investigación y Saberes , / 2023/ , Vol. 13, No. 3
105
Figure 4.
Distribution of average speeds of the 1600cc cab fleet by
efficient driving.
The best scenario corresponds to the data recorded on July 20, 2019
between 15:00 and 16:00, in the vehicle '''Taxi-16''' consists of 3120
recorded data.
The worst-case scenario corresponds to data recorded on July 22,
2019 between 8:00 to 9:00, in the vehicle '''Taxi-16''' and consists of
3600 of recorded data.
We proceeded to calculate the VSP bins vehicle specific power shown
in Figure 5. We obtained a distribution of 57% of bins of 1600cc cabs
through efficient driving parameters by averaging the best and worst
case scenarios obtained in the data recorded in the cab fleet.
Figure 5.
Distribution of VSP Bines of cab 1600 eco-driving cabs.
0
10
20
30
40
50
60
1 4 7 1013161922252831343740434649525558
VSP Bines [%]
Bines VSP Taxi 1600 eco-driving VSP
Bines
Best Scenario Worst Case Scenario
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
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106
CO2 emission factors
Analysis: Figure 6 shows an average CO2 emissions factor in the best
case scenario of approximately 220g, while the worst case scenario
shows an average of 290g equivalent, so the worst case scenario
increases the CO2 emissions factor.
Figure 6.
CO2 emission factors of 1600 cc cabs through efficient
driving.
Figure 7.
Comparison of CO2 emissions in normal cab driving and
eco-driving.
In the comparison of CO2 emissions in cabs with normal driving and
eco-driving, the following values were obtained as shown in Figure 7,
where the best scenario 207.47g and the worst scenario 323.19g
normal driving were analyzed, with the results in the best scenario
220.96 g, and the worst scenario 293.13g, these results were obtained
through efficient driving parameters, reflecting a high value in the
0
50
100
150
200
250
300
350
Mejor Escenario Peor Escenario
Emission factor [g/km].
Cab 1600 - Eco-driving
207,47
323,19
220,96
293,13
0
50
100
150
200
250
300
350
Mejor Escenario Peor Escenario Mejor Escenario Peor Escenario
NORMAL ECO
Taxis 1600
CO emission factor
2
cab 1600 cc
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
Revista Científica Interdisciplinaria Investigación y Saberes , / 2023/ , Vol. 13, No. 3
107
best scenario with eco-driving, this could be because the drivers did
not apply the efficient driving techniques.
In Table 1. Demonstrates the CO2 emissions factor in grams per
kilometers traveled, obtained in the best and worst scenario in normal
and eco-driving tests in the 1600cc cab fleet the selected value was
293.13g scenario with higher vehicle flow.
Table 1.
Results of CO2 g/km emissions factor estimation.
CO emission factor
2
[g/km].
Cabs 1600cc
NORMAL
ECO
Best
Scenario
Worst Case
Scenario
Best
Scenario
Worst Case
Scenario
207.47
323.19
220.96
293.13
Results
To analyze the CO2 emissions results it is necessary to import and sort
the data, transform the units if necessary and store them in a database
table. The database consists of approximately 20.5 million rows of
data, each row containing vehicle identification information, date and
time, GPS position, altitude and vehicle operating parameters.
Analysis: The results shown in Table 1. They reflect estimates of the
CO2 emissions factor in grams per kilometers traveled by the vehicle
fleet, obtaining the following scenarios through efficient driving in
1600 cc cabs, the best scenario having a value of 220.96g/km of CO2
emissions and in the worst scenario a result of 293.13g/km is obtained
with these results of the two scenarios can be determined averages of
daily, monthly and annual estimates of CO2 emissions estimates of
the vehicle fleet.
Figure 8 shows that the CO2 emissions factor levels increase
significantly between the other scenarios using different modes of
normal driving and efficient driving. In this way, the different
calculations were made to estimate the CO2 emissions factor,
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
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observing that in the emissions results there is no variation between
the driving modes. This problem was a consequence of collecting
data in several cabs with several drivers, where the way of driving is
not the same, in this case the driver did not correctly apply the eco-
driving techniques.
Figure 8.
CO2 g/hour emissions results.
Figure 9
. Average CO2 emissions estimates.
Figure 9 shows the result of CO2 emissions, taking into account the
worst scenario, giving an average in the first bar 73 517g/km in one
day, in the second bar in one month we have 1'764 408.10g/km in the
third bar obtaining an estimated value of 21'172 897.15g/km per year,
in the last bar presents an average of 21.17 tons of CO2 per year.
73517,004
1764408,096
21172897,15
0
5000000
10000000
15000000
20000000
25000000
Gramos/Dia Gramos/Hora Gramos/ Hora Taxis
CO emissions
2
[g/km].
Mass/Time
CO emissions
2
cabs 1600
cc
. eco-driving
73.517,00
1.764.408,10
21.172.897,15
21,17
0,00
5.000.000,00
10.000.000,00
15.000.000,00
20.000.000,00
25.000.000,00
Gramos/Dia Gramos/Mes Gramos/Año Tonelada/Año
CO emissions
2
[g/km].
Mass/Time
CO emissions
2
cabs 1600
cc.
eco-driving
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
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In these results, the average CO2 emissions were estimated by
obtaining the worst-case scenario value shown in Table 1. Applied to
the 1600cc cab fleet by eco-driving.
Table 2.
Average calculation of estimated CO2 emissions.
In Table 2, the calculation of CO2 emissions was made by averaging
73 517.00g in a day. Traveled in 250.8Km this value was calculated by
the average speed of travel in an hour of 20.9 km and multiplied by
an estimate of 12 hours that a cab works in the day. Obtaining an
average in the month of 1'764 408.10g. In which 6 019.2 km were
traveled. Having 21'172 897,15g. In a year where 72 230.4km were
traveled, thus reflecting a result of 21.17 tons in the year of CO2
emissions, taking as a reference the worst case scenario in 1600cc
cabs. Eco-driving.
Figure 10.
Comparison of CO2 emissions factor using the best and
worst case scenarios.
15.959.307
21.172.897
5%
15,96
21,17
5%
0
5.000.000
10.000.000
15.000.000
20.000.000
25.000.000
Gramos/Año Tonelada /Año Diferencias
Porcentuales[%]
CO2 emissions [g/km].
CO Emissions Factor Comparison
2
annual cabs 1600
cc
eco-driving
Best Scenario WorstScenario
Worst case scenario
Cabs 1600cc. Eco-driving
Total,
emissions
in one day
[g/km].
Total
emissions in
one month
[g/km].
Total,
emissions in
one year
[g/km].
Total
emissions
in one year
[t/km].
73 517,00
1'764 408,10
21'172 897,15
21,17
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
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110
The results obtained in Figure 10 analyze the comparison of the CO2
emissions factor per year, reflecting in the best scenario "less
vehicular traffic" 15'959,307g/km, giving a value of 15.96 tons. In the
worst scenario "more vehicular traffic" the amount of 21'172.897g/km
is obtained, thus having a result of 21.17t of CO2, per year, showing
a comparison of 5% between the two scenarios.
Table
3 presents the results of pollutant emissions such as carbon
dioxide and carbon monoxide, these two emissions are calculated in
grams. Particulate matter and nitrogen oxide are calculated in
milligrams, the values reflect the worst case scenario with more traffic
and the best case scenario with less vehicular flow.
Table 4.
Results of fuel consumption in eco-driving cabs.
Cab 1600 eco-driving
Fuel
consumption
Worst
Case
Scenario
Best
Scenario
Traveled
consumption
[l] [l
1.81
1.98
Distance [Km].
16.70
21.28
Consumption
[l/100 Km].
10.83
9.28
Table 4 shows the fuel consumption in 1600cc cabs with efficient
driving, the calculation was made in consumption per trip in liters,
using the distance in kilometers, in addition to the consumption in
liters per 100 Km. The worst case scenario was taken as a reference.
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
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Figure 11.
Calculation of fuel consumption of the cab fleet with eco-
driving.
Figure 11 shows the calculation of eco-country fuel consumption in
liters in the first bar that refers to the consumption in one day,
applying the worst scenario, showing the results 27.1616 liters, in the
second bar a monthly consumption of 651.8793 l. in the third bar
reflects a consumption of 7822.5523 l. per year. Making the
respective calculation to know the total cost of consumption per year
is $ 3 823.44cent, calculation made with the value of the liter of fuel
Eco country ($0.48cent).
Conclusions
The importance that influences the characteristics of the cab fleet on
emissions depends on the type of technology, engine capacity and
application of eco-driving techniques.
In the estimation of CO2 emissions, a baseline was obtained as a
result for the study of pollution of the city of Cuenca by greenhouse
effect emissions, analyzing the CO2 emissions in two scenarios which
correspond: first a scenario with lower vehicle traffic conditions and a
second scenario with more traffic, for this purpose, the average
speeds were recorded from lowest to highest, through each hour of
data determining a normal distribution, the best scenario corresponds
to the first quartile of the data sample and the worst scenario
corresponds to the third quartile of the normal distribution of the data
sample, for the worst scenario was obtained 293.13 g/km of CO2,
compared to the best scenario that obtained 220.95 g/km, with a
percentage difference of 5%.
27,16164
651,87936
7822,55232
3823,440
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
Dia Mes Año Costo X año
Fuel in liters [l] Fuel in liters [l] Fuel in
liters [l] Fuel in liters [l
Time Dollars
Fuel consumption per [Km] traveled
Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
Cuenca, using the IVE model
Revista Científica Interdisciplinaria Investigación y Saberes , / 2023/ , Vol. 13, No. 3
112
The CO2 emissions per year generated by the 1600cc efficient driving
cabs, for the best scenario "less vehicular traffic" 15'959 306.88g/km
in the worst scenario "more vehicular traffic" 21'172 897.15g/km
resulting in a percentage difference of 5% and in tons are 15.95t for
the best scenario and 21.17 t for the worst scenario.
The fuel consumption in the best scenario with favorable traffic is 9.28
l/100km and the worst scenario with more vehicular traffic is 10.83
l/100km, resulting in a percentage difference of 8%, i.e., in the worst
scenario there is higher fuel consumption due to more vehicular traffic
at the time of the trip.
Comparing the CO2 emissions factor in the best scenario 220.9 g/km,
with the technical data according to the Environmental Protection
Agency (EPA), of the Hyundai Accent 1.6, 4cil. With 6 speeds, manual
where it indicates that emit 172 g/km, obtaining a difference of 7%,
this is due to the geographical location of the city of Cuenca.
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Estimation of CO2 emissions in 1 600 cc cabs under efficient driving parameters in the city of
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