The Advantage of Using the Electric Vehicles
Yue-ying Yang 1,2,3, Di Liu2, Jun Meng3,Xu Li3, Ting-ting Shang3, Jian-xin Hu3
1
Northeast Forestry University Postdoctoral Programme, Harbin, China
Heilongjiang Acamedy of Agricultural Sciences Postdoctoral Programme, Harbin, China
3
Department of Information and Computation Science, Northeast Agricultural University, Harbin, China
(yangyueying2008@yahoo.com.cn)
2
Abstract - With the rapid development of the electricity,
the advantage of using the electric vehicles has become more
attractive than before. Firstly, to prove the emission of
carbon dioxide and the consumption of fossil fuels have been
reduced, we establish a time series prediction model. The
result indicates that the spread of electric vehicles not only
does good to the environment but also makes good impact on
the economy. Secondly, in order to provide a model of the
amount and type of electricity generation, by comparative
analysis, we searched out the perfect interval of various
kinds of energy sources, adequately satisfy the demands of
the government and all social circles. To insure safe, efficient
and effective transportation, the introduction of widespread
use of electric vehicles becomes a necessary trend. Hence, the
development of electric vehicles must go through a zigzag
road and be full of challenges.
Keywords - consumption of fossil fuels, electric vehicles,
energy, time series model
I. INTRODUCTION
With the development of society, the widespread use
of electric vehicles has become a necessary trend [1-2]. As
a new kind of transportation means it makes influences on
various aspects, aspects such as environment, society,
economy, and health [3-7]. Both the government and the
manufacturer should take these key factors into
consideration carefully when determining whether and
how to support the development and use of electric
vehicles [8-11]. Collect the data and establish models. On
the basic of the model(s) established above, we attempt to
estimate how much fossil fuels would be saved in the
world by widely used electric vehicles. Set up a model
about the amount and type of electricity generation which
should be added to meet your model, which, not only
benefit the environment, society, business, and individuals
in maximum limit but also calculate the amount and type
of electric vehicles being used [12-15]. Write a detailed
report to present your model and your analysis of the key
issues associated with the electric vehicles and the
electricity generation, including the strategies the
government apply to insure safe, efficient and effective
transportation. Also, you should think whether it is worth
bringing in electric vehicles or not, besides, discuss the
impact it makes on global energy needs in the face of
dwindling fossil fuel supplies.
II. METHODOLOGY
With electric vehicles' widespread use, more and
more other kinds of energy have been changed to electric
energy for electric vehicles, As a matter of fact, the
amount of fossil fuel which burns directly for vehicles
reduces..There will be pollution when the fossil fuel
transforms or burns. CO2 emission changes most
obviously, so we choose CO2 emission as the index to
represent for the environment. In the opinion of the
manufacturer, they do like to produce electric vehicles if
most consumers like to buy, because of the profit.
Questionnaire has been used to find out if consumer
groups are satisfied with electric vehicles, in order to
reflect the purchasing power.
Let's talk about the effect on fossil fuel consumption:
divide the map into North America, Europe, Eurasia,
Middle East, Africa, Asia Pacific, treat North America as
representatives, fossil fuel consumption during the period
of 2001–2006 can be forecasted by the annual fossil fuel
consumption during the period of 1980–2000. Compared
with practical consumption during the period of 2001–
2006, we can get whether the fossil fuel consumption has
been reduced, Time series forecasting has been
implemented.
All exponential smoothing methods are conveniently
written as recurrence relations: the next value is
calculated from the previous one. It is suitable for dealing
with some stochastic quantity over time whose trend is
stable. For single exponential smoothing, the formula is
very simple:
yˆ t  kyt 1  (1  k ) yˆ t 1
0  k 1
yt 1 is the actual value for the moment of ( t  1 ),

is the
predict value for the moment of t ,the parameter
k controls the amount of smoothing, however, there is
still no good a unified method to choose coefficient k ,
we constrain the coefficient to the range 0  k  1 by
convention. If k  1 , the graph is not smoothed at all;
if k  0 , the graph is absolutely smooth. A choice in the
range 0  k  0.3 allows the trend to change relatively
slowly, a choice in the range 0.6  k  1 allows the trend
to rise or descend. We have already discussed the effects
of different k values, compared with different k values
and choose the suitable one. To set up these calculations,
we need to specify the value for k and an initial value ŷ1 .
Make the mean of the values for years of 1980 and
1981 as the initial value to forecast the value for the year
of 2003, so yˆ1  79.2778 .
yt
III. RESULTS
A. Choose the coefficient
Forecast for fossil fuel consumption and made match
forecast graph with various k = 0.2, 0.5 and finally 0.8,
the value over observations 1980–2002. Thus, the forecast
is available at period 2003. The forecast graph is more
utopian when its trend approach reality graph, choose the
match k as coefficient, via yˆ t  kyt 1  (1  k ) yˆ t 1 , the
predicted value is shown in Table I.
TABLE I
Fossil fuels reality and forecast consumption comparison
S (1)  ky  (1  k ) S (1)
t
t 1
 t
 ( 2)
(1)
S

kS

(
1

k
)
S t(21)
 t
t


 y t T  at  bt T
Where St(1) is single exponential smoothing value for the
period t , S t( 2 ) is double exponential smoothing value for
the period t , yt is actual value for the period t , y is
predicted value for the period (t  T ) and k is coefficient.

t T
fossil fuels
reality
consumption
k=0.2
k=0.5
k=0.8
1980
80.11
79.27780
79.27780
79.27780
1981
77.92
79.31284
79.36540
79.41796
1982
74.17
79.27079
79.23400
79.16567
1983
72.97
79.36330
79.48366
79.61979
The initial values S0(1) , S 0( 2 ) can be got in the same way
to ŷ . Based on the equations, the predicted value is
1984
76.80
79.21024
79.04084
78.80238
shown in Table Ⅱ.
1985
76.69
78.51193
77.37976
76.33542
1986
76.50
77.57841
75.61205
74.34256
1987
79.38
77.19493
75.63652
75.39731
1988
82.94
77.03439
76.01437
76.19324
1989
84.75
76.92560
76.25241
76.43101
1990
84.14
77.20922
77.29805
77.96115
1991
83.77
78.03927
79.32875
80.67980
1992
85.69
79.16142
81.48940
83.05599
1993
87.16
80.14018
82.77232
83.85539
1994
89.03
80.88993
83.33060
83.88219
1995
90.02
81.71893
84.18278
84.80440
1996
92.81
82.66331
85.31180
86.11354
1997
94.37
83.76147
86.73297
87.74601
1998
95.18
84.89254
88.07489
89.08266
1999
96.61
86.24183
89.85693
91.12770
2000
99.12
87.68860
91.66632
93.00611
2001
97.19
89.07887
93.15312
94.31316
2002
98.33
90.45256
94.55023
95.62051
2003
99.32
91.96800
96.29000
97.54800
year
forecast
The trend of forecast graph with k  0.8 ，is the most
approximate to reality graph, so the coefficient k is 0.8.
B. Double Exponential Smoothing-Based Prediction
Single exponential smoothing as described above
works well for time series without an overall trend.
However, in order to present an overall trend, double
exponential smoothing comes in. Double exponential
smoothing-based prediction makes one more exponential
smoothing based on the data which were forecasted by
single exponential smoothing, but the second exponential
smoothing value for the period t is not the predicted
value forecasted by single exponential smoothing for the
period (t  1) . Such equations were used to make fossil fuel
consumption predictions:
at  2 S t(1)  S t( 2 )
bt 

k
S t1  S t2 
1 k

1
TABLE Ⅱ
Predicted value and relative factors







S t (1)
S t (2)
1980 80.110
80.110
80.110
80.11
0
0
1981 80.008
80.079
80.101
80.049
-0.041
0.001681
1982 79.496
79.904
80.042
79.708
-0.212
0.044944
1983 78.227
79.401
79.850
78.76
-0.533
0.284089
1984 76.246
78.455
79.431
77.06
-0.814
0.662596
1985 73.956
77.105
78.733
74.779
-0.823
0.677329
1986 71.867
75.534
77.773
72.334
-0.467
0.218089
1987 70.514
74.028
76.650
70.282
0.232
0.053824
1988 70.434
72.949
75.540
69.249
1.185
1.404225
1989 72.002
72.665
74.677
69.791
2.211
4.888521
1990 75.191
73.423
74.301
72.168
3.023
9.138529
1991 79.528
75.255
74.587
76.208
3.32
11.02240
1992 84.367
77.988
75.607
81.39
2.977
8.862529
1993 89.135
81.332
77.325
87.057
2.078
4.318084
1994 93.476
84.976
79.620
92.626
0.85
0.722500
1995 97.229
88.652
82.330
97.683
-0.454
0.206116
1996 100.43
92.185
85.286
102.04
-1.61
2.59210
1997 103.22
95.496
88.349
105.71
-2.49
6.20010
1998 105.73
98.566
91.414
108.78
-3.05
9.30250
1999 107.99
101.39
94.408
111.37
-3.38
11.4244
2000 110.06
103.99
97.284
113.58
-3.52
12.3904
2001 111.97
106.39
100.01
115.49
-3.52
12.3904
2002 113.73
108.59
102.59
117.17
-3.44
11.8336
2003 115.37
110.63
105.00
118.66
-3.29
10.8241
2004 116.99
112.54
107.26
120.07
-3.08
9.48640
2005 118.74
114.4
109.40
121.54
-2.8
7.84000
2006 120.79
116.32
111.48
123.23
-2.44
5.95360
year
yt
yt
2
yt 1  y t 1  yt 1  y t 1 
Here are forecast graph and active graph which can
reflect the difference between predicted value and actual
value clearly:
Here are realistic CO2 emissions graph and forecast CO2
emissions graph:
FigⅠ. Graphs of reality &forecast fossil fuels consumption
During the period of 2001–2006 ， forecasting fossil
energy consumption is obviously higher than actual fossil
energy consumption , which indicates fossil energy has
been saved.Therefore, for the economy, electric vehicles'
widespread use is feasible and significant.
For the environment, CO2 emission during the period of
2001–2006 can be forecasted by the data during the
period of 1980–2000 in the same way to fossil energy
consumption and compared with actual emissions:
Fig Ⅱ. Reality &forecast fossil fuels consumption
Reality CO2 emissions are much lower than forecast
CO2 emissions, which indicate the pollution has been
improved because of electric vehicles' widespread use. In
conclusion, for government, the widespread use of electric
vehicles is beneficial to both the environment and the
economic!
C. Fossil fuels consumption conditions
TABLEⅢ
Reality &forecast fossil fuels consumption
year
Coal
Petroleum
Natural
gas
Total
/reality
Total
/forecast
1980
1533.8
2706.1
1217.9
5457.8
5457.8
1981
1583.5
2565.9
1193.8
5343.2
5452.453
1982
1539.1
2431.9
1125.8
5096.8
5423.313
1983
1601.9
2366.8
1062.4
5031.1
5349.067
1984
1724.9
2463.9
1131.2
5320
5234.53
1985
1763.7
2448.7
1106.7
5319.1
5107.389
1986
1735.1
2530
1037.6
5302.7
4999.929
1987
1821.3
2577.9
1090.8
5490
4943.687
1988
1914.4
2682.1
1145.7
5742.2
4969.923
1989
1920.4
2714.9
1210.5
5845.8
5099.335
1990
1931.3
2632.4
1215.6
5779.3
5325.549
1991
1916.9
2573.8
1239.8
5730.5
5612.995
1992
1937.7
2621.8
1289.6
5849.1
5916.537
1993
1998.5
2637.4
1321.2
5957.1
6200.054
1994
2013.4
2700.3
1352.1
6065.8
6444.672
1995
2037.6
2667.3
1410.2
6115.1
6644.898
1996
2125.4
2755.1
1439.4
6319.9
6809.273
1997
2191.5
2799.3
1449.5
6440.3
6954.12
1998
2219.4
2859.1
1423.7
6502.2
7092.914
1999
2218.8
2917.9
1438.8
6575.5
7230.772
2000
2313.7
2978.6
1479.7
6772
7370.669
2001
2231
2991.3
1438.7
6661
7512.138
2002
2257.3
2982.1
1503.7
6743.1
7651.389
2003
2301.2
3042.5
1493.2
6836.9
7784.862
2004
2318.6
3148.3
1472.9
6939.8
7913.18
2005
2340.6
3183.9
1478.7
7003.2
8042.439
We collect the global consumption of coal, oil and
natural gas in the period of 1980-2000, then forecasted the
trend of oil fuels consumption in the year of 20012006,.Set North America region as an example, data are
shown in Table Ⅳ:
Table Ⅳ
Forecast& reality consumption of oil fuels from 2001 to 2006 in
North America region
NO.
year
reality
forecast
22
2001
97.19
111.9705
23
2002
98.33
113.7308
24
2003
99.32
115.3739
25
2004
101.32
116.9929
26
2005
101.78
118.7432
27
2006
100.84
120.7924
With the help of least square method, we get:
Forecast-consumption
f NAf = -0.00003052-0.010487t  0.56361t 2 -5.916t 3  89.685t 4
Reality-consumption
f NAr = 0.00025515-0.018503t  0.44548t 2 -2.7877t 3  81.022t 4
On the basis of World Carbon Dioxide Emissions
from the Consumption and Flaring of Fossil Fuels can get
a figure of seven regions about Carbon Dioxide
Emissions:
Fig Ⅲ World Carbon Dioxide Emissions from the Consumption and
Flaring of Fossil Fuels, 1980-2006
From Fig Ⅲ., we can conclude that the Carbon Dioxide
Emissions of North America, Europe and Eurasia in the
period of 1998-2006 is tend to stability, Carbon Dioxide
Emission of Asia & Oceania increases rapidly, the Carbon
Dioxide Emissions of Central & South America ，Middle
East and Africa increases in a certain proportion. There
must be a better one, with different energy distribution
proportions for the different areas, when the energy
distribution proportions of other areas trend to that of the
area where Carbon Dioxide Emissions is stabile, we
consider that energy utilization of other areas is
optimized ,not to aggravate environmental pollution.
Fig Ⅳ North America Carbon Dioxide Emissions from the
Consumption and Flaring of Fossil Fuels
Emissions in seven regions. Use Carbon Dioxide
Emissions growth rate, not the amount of Carbon Dioxide
Emissions, as an index, for different energy base in
different regions. The Figures above indicate Carbon
Dioxide Emissions of North America is declining slowly,
Carbon Dioxide Emissions of Europe has drastic change
all the time, Carbon Dioxide Emissions of Asia &
Oceania is increasing seriously. The degree of its Carbon
Dioxide contamination is between North America and
Asia & Oceania.
IV. DISCUSSION
Cost effective, investor friendly economics of
Electric vehicles have yet to be demonstrated.
Conventional vehicles have had the great advantage of
over a century of time to mature the current status of the
market, where consumers expect a vehicle that is reliable,
durable, with a long range, strong acceleration, and good
power characteristics. Electric vehicles are still in the
research and development phase, so they are not as
advanced as fossil technologies.
The economic efficiency of electric vehicles depends
substantially on the source of electricity. If the electricity
comes from renewable sources, the electric vehicles are
advantageous to the environment. If the electricity comes
from fossil fuels, the electric vehicles can only be
competitive with electricity generation onboard.
V. CONCLUSION
FigureⅤ Asia & Oceania Carbon Dioxide Emissions from the
Consumption and Flaring of Fossil Fuels
Figure Ⅵ Europe Carbon Dioxide Emissions from the Consumption
and Flaring of Fossil Fuels
With the amount of total energy increasing, Carbon
Dioxide Emissions will increase with the amount of fossil
fuels of total energy increasing, at the same time, Carbon
Dioxide Emissions growth rate is used to represent for the
degree of contamination. Comparative Analysis was
implemented to compare the growth of Carbon Dioxide
Our model indicates the government and vehicle
manufacturers should support the development and use of
electric vehicles. Electric vehicles' widespread use is
useful on both the environment and the economic, as well
as manufacturers’ profit. With electric vehicles'
widespread use, fossil fuel consumption and Carbon
Dioxide Emissions decline.
Although with the use of electric vehicles, Carbon
Dioxide Emissions can be improved, there is still
unbalance energy distribution proportion, causing
unnecessary energy waste and unnecessary pollution,
thus, we offer the optimal energy distribution proportion
to improve the environment and to save nonrenewable
energy resource, which is consistent with the strategy of
sustainable development.
Finally, I suggest the government make some policy
and offer technological development to break the limit of
insufficient power in battery to support the widespread
use of electric vehicles.
ACKNOWLEDGMENT
Funding: This work was supported by the
Heilongjiang Academy of Agricultural Sciences Project
(No. LBH-Z10039), the Doctoral Research Foundation of
Northeast Agricultural University.
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