Feasibility Study of using an Electric Vehicle in the Actual

Infrastructure of a Small City in Spain

Andrés Montero Romero

, Michela Longo

2,*

, Federica Foiadelli

and Wahiba Yaici

Universidad Carlos III de Madrid, Spain

Politecnico di Milano, Italy

CanmetENERGY Research Centre, Canada

wahiba.yaici@nrcan-rncan.gc.ca

Keywords: Electric vehicles, Charging station, Sustainable mobility, Transportation.

Abstract: This study simulates certain conditions in Cuenca, a small city located in the centre of Spain, between Madrid

and Valencia, which uses electric mobility. The objective is to conduct an appraisal of the use of electric

mobility in order to ascertain possible improvements or developments that will be required in a green,

ecological and smart city in the future. In order to facilitate this experiment, an electric vehicle will be driven

from Cuenca to Madrid. Battery charging will take place at designated charging stations along the way, if

required. Four commercial vehicles with different characteristics have been chosen for the simulations. In

case there are any vehicles which cannot reach the destination, likely causes will be reviewed, and solutions

will be suggested.

1 INTRODUCTION

Until recently, the electric vehicle was an unknown

and unfamiliar phenomenon. However, there was a

disposition to replace private vehicles propelled by

Internal Combustion Engines (ICE) with vehicles that

are propelled by electric motors and powered by

batteries (

Kiyakli and Solmaz, 2019; Besselink et al.,

2010). According to experts, the key motivation for

this change is the technological revolution that the

electric vehicle represents. Changes in automotive

policies and a commitment to environmental

protection are additional strong reasons, with the

environment being the most pressing and pervasive

concern (

Evtimov et al., 2017). Considering how

burning of fossil fuels contributes to climate change,

replacing the millions of cars propelled by ICE with

electrical vehicles should significantly alleviate this

problem for the Earth (I.N. Laboratory). Spain has

made good progress in deploying electric vehicles

compared to other European countries (

Hedge et al.,

2016). Registered electric vehicles represent 0.32%

of the market share compared with 1.7 % which is the

average in other European countries (

Valsera-Naranjo

et al., 2009; Yan et al

., 2014). Yearly improvements are

visible, both in perception and thinking of the Spanish

people, as well as in sales and governmental policies

regarding electric vehicles. A limitation to the use of

electric vehicles in Spain is the relatively small

number of charging stations. In spite of widespread

availability of charging equipment, in 2017 Spain was

only fifth place in Europe with 5000 points (4.26% of

European charging stations), while the United

Kingdom (UK) was fourth place with 12.2%,

signifying a huge gap between them. The situation is

more deplorable when reviewing fast charging

stations. Only 12% of charging stations are

configured for fast charge. The geographical

distribution of charging stations is irregular (

He and

Hou, 2017; Mehmet Cem Catalbas et al., 2017)

. They are

principally located only in the biggest cities such as

Madrid, Barcelona, Valencia, Bilbao and Seville.

They are also installed along major roads and

highways and close to the coast for tourism. This

study is focused in checking if people can move from

Cuenca to Madrid and come back using an electric

vehicle, charging the batteries during the trip if is

required. Battery charging will take place at

designated charging stations along the way, if

required. Four commercial vehicles with different

characteristics have been chosen for the simulations.

In case there are any vehicles which cannot reach the

100

Romero, A., Longo, M., Foiadelli, F. and Yaici, W.

Feasibility Study of using an Electric Vehicle in the Actual Infrastructure of a Small City in Spain.

DOI: 10.5220/0011358800003355

In Proceedings of the 1st International Joint Conference on Energy and Environmental Engineering (CoEEE 2021), pages 100-107

ISBN: 978-989-758-599-9

destination, likely causes will be reviewed, and

solutions will be suggested.

The paper is divided into the following sections:

Section 3 describes the model of an EV with a real

driving cycle. In Sections 4 and 5, details of the case

study and simulation results using Matlab-Simulink

are provided, followed by discussions. Finally, the

last section provides the main conclusions of this

study.

2 PERFORMANCE MODEL OF

AN ELECTRIC VEHICLE

DRIVEN IN A REAL PATH

In order to understand the dynamics of a vehicle,

electric or fuel powered car, train or trucks, it is

necessary first to evaluate the forces involved in their

movement (Di Giorgio et al. 2017;

Zhongjing et al.

2013)

. Those principal forces are determined using the

physic laws that are used to model and simulate the

motion of the electric vehicle (

Hosseini et al, 2020; Tan

and Osama, 2013)

. The typical problem is to identify

the forces of a vehicle in a ramp as represented in

figure 1.

Figure 1: Forces of a vehicle located in a ramp.

During driving, the resistance forces which act on

the vehicles are determined with the following

governing equations:

• Aerodynamic resistance:

𝐹



𝜌𝐶



𝐴



𝑣



(1)

where ρ is the air density, whose typical value is 1.225

kg/m

; C

is the aerodynamic coefficient; A

is the

frontal area of the vehicle (m

) and v is the speed of

the vehicle (m/s).

• Tire rolling resistance:

𝐹



=𝑚𝑔𝐶



𝑐𝑜𝑠(𝜃)

(2)

where m is the vehicle mass (kg); g is the gravity

acceleration. Its value is 9.81 m/s

; 𝜃 is the slope of

the ramp and 𝐶



is the tire rolling resistance

coefficient and it varies according to the road surface

(0.013 for concrete or asphalt).

• Gradient resistance:

𝐹



=𝑚𝑔𝑠𝑖𝑛(𝜃)

(3)

where m is the vehicle mass (kg); g is the gravity

acceleration. Its value is 9.81 m/s

and 𝜃 is the slope

of the ramp.

• Inertia resistance:

𝐹



=𝑚𝑎 (4)

where m is the vehicle mass (kg) and a is the

acceleration or deceleration of the vehicle (m/s

Finally, the total resistance force is the sum of all

them:

𝐹



=𝐹



+𝐹



+𝐹



+𝐹



(5)

Manufacturers do not give the data of each of the

component of the vehicle. For this reason, it will be

not accurate to model a whole vehicle by taking into

account the energy flows from the battery to the

wheels including the electronic converter, electric

motor and the transmission system. However, the EV

battery capacity is known. Normally, the EV tries

recharging the battery before spending the 80% of its

capacity. That is known like battery utilisation factor.

Moreover, the efficiency of the power train is also

around 80%. That is known as the 80% rule of thumb

for BEV power train efficiency and battery

utilisation. Therefore, knowing the battery capacity

and the parameters of the vehicle per Eqs. (1–5),

which allow to calculate the resistant forces, the

required energy for moving the vehicle can then be

computed.

The required power which has to be delivered by

the battery is:

𝑃



𝜂



·𝐹



·𝑣+𝑃



(6)

where 𝜂



is a constant overall efficiency of the power

train and 𝑃



is the power usage for auxiliary

systems. In the following, a procedure is provided for

modelling the behaviour of an electric vehicle driven

in a path according to the parameters given in the

manufactures’ specifications and the known position

and characteristics of the actual charging stations.

2.1 Inputs Definition

It is important to know all needed parameters for

characterizing both the vehicles and routes. For

vehicles, the principal parameters are the mass of

vehicle, dimensions, the capacity of the battery of the

vehicle and its aerodynamic coefficient. For more

precision, knowing their maximum acceleration and

speed could be an advantage. Those data are detailed

in technical data of vehicles given by manufacturers.

Referring to the parameters of the routes, these are

principally the total distance, slope in different

intervals, the referent speed in each part of the path

and the location of the charging station where it is

possible to charge the vehicle. Google Earth is a free

Feasibility Study of using an Electric Vehicle in the Actual Infrastructure of a Small City in Spain

101

software which allows getting those parameters by

means of obtaining the altitude, longitude and latitude

of several points which draw the route. After that,

data could be extracted in an Excel file.

2.2 Speed, Acceleration and Slope

Profiles in Simulink

In order to get a better precision, Simulink computes

the speed, acceleration and slope profiles. Input data

in Simulink are the maximum speed of the ways,

which will be the reference speed of the vehicle, and

the slope which have been imported from Excel.

Those data are introduced in “Lookup tables” whose

input is the distance from the starting point. A PID

(Proportional–Integral–Derivative) controller allows

to reach the reference speed of the vehicle when slope

and/or the speed of the way change. The design of the

PID have been done using Ziegler-Nichols method

for each vehicle knowing its acceleration.

2.3 Energy and SOC Calculation

Once acceleration, speed and slope in each stretch of

the paths are known, required power can be calculated

using Equation 6.

It is worth noting that, due to the fact inertial force

is only required in transients, it has not been taken

into account. For calculating the required energy and

the State of Charge (SOC) in each point of the path,

the algorithm has been computed calculating the

consumed energy from the starting until a certain

point as the sum of the consumed energy in little

intervals of 50-100 metres of length.

Taking from Simulink the input data from

calculating the required power and the time between

two intervals of discretization of the path, energy

consumption in that interval is calculated. Finally, the

SOC is calculated.

2.4 Checking if Charging is Required

The last part of the algorithm is to check if charging

the battery of the vehicle is required in order to not

reach a SOC lower than 20% which could damage the

battery. It will also say where the vehicle should be

charged. If there are points which SOC becomes

lower than 20% and there is not any charging station

before, a charging station will be necessary.

Multiplying that power delivered by the battery times

the spending time of the journey, the energy supplied

by the battery can be known.

Finally, the SOC of the battery, that is, the level

of charge of a battery relative to its capacity, is

calculated:

SOC

𝐵𝑎𝑡𝑡𝑒𝑟𝑦 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 − 𝐸𝑛𝑒𝑟𝑔𝑦 𝑐𝑜𝑛𝑠𝑢𝑚𝑒

𝐵𝑎𝑡𝑡𝑒𝑟

𝑦

𝑐𝑎

𝑝

𝑎𝑐𝑖𝑡

𝑦

(7)

3 CASE STUDY

Cuenca is a city in central Spain, and is the capital of

the Cuenca province, in the region of Castile – La

Mancha. Cuenca city is located 168 km from Madrid,

199 km from Valencia and 179 km from Toledo;

these are the surrounding principal Spanish cities. In

2019, the Spanish Statistical Office (Instituto

Nacional de Estadística - INE), recorded the total

population of Cuenca city as 54,690 people while the

province of Cuenca has 196,323 people. This means

that 27.28% of the province’s population live in the

capital city. Cuenca province is one of the most

affected by depopulation in Spain. Depopulation

happened for many reasons: Cuenca is an area with a

large proportion of aged people; there are few big

industries and the economy is principally reliant on

farming, agriculture and forestry activities; and there

is minimal investment in new industries or in

infrastructure. For these reasons, young people seek

employment in the capital city or other city outside

the province, principally in Madrid or Valencia due to

their proximity. In respect of Electric Vehicles,

Castile – La Mancha represents only 3% of the

vehicles registered in Spain, what shows that its

deployment there is insignificant.

Moreover, in the city of Cuenca, amidst the 11

charging stations, only one is public, and is managed

by Iberdrola. The others are either private or are

located in hostels, supermarkets or in car dealerships,

or are out of service. The objective is to determine

whether an electric vehicle can get to Madrid, which

is the city closest to Cuenca. Achieving this feat could

be a motivation for Cuenca residents to purchase

electric vehicles. This is because that route is popular

since many of them currently work or study in the two

cities. It is also commonly traversed for tourism and

leisure.

Four different commercial vehicles have been

selected according to parameters including battery

capacity, and price, and number of sales in past years.

The vehicles are: Citröen C-Zero, Nissan Leaf, BMW

i3 and Tesla model S. The required parameters for the

model can be easily obtained in their specifications.

The assumption will be that the vehicle is driven with

daily lighting and heating or air conditioning turned

CoEEE 2021 - International Joint Conference on Energy and Environmental Engineering

102

on during the trip. So, the term P

aux

of Equation 6 is

equal to 540 W. Regarding the travel route, it is

important to know its parameters such as total length,

the slopes at different intervals of the route, the

reference speed of the vehicle at each point of the

route, location of the actual charging stations and

their number, and the types and capacity (power) of

the connectors. The chosen travel route is the fastest

and most commonly used route to Madrid. Reference

speed will be the maximum allowed by the Spanish

traffic law, which is: 50 km/h inside the urban and

industrial areas, 90 km/h on conventional roads and

120 km/h on highways.

Figure 2 presents the altitude profile of both

routes. It allows the taking of data for calculating the

slope profile. Red points indicate the location of the

actual charging station that can be found during the

trip.

Figure 2: Altitude profile from Cuenca to Madrid.

Table 1 presents the features of those charging

stations.

Table 1: Actual charging stations in the route Cuenca-Madrid.

No Location Type Use Connector Type

Power

(kW)

1 Car dealer Charging allowed

Schuko (EU Plug) 2.3

CEE 3P+N+E 11.0

2 Street charging

Public

(managed by

Iberdrola)

TYPE 2 43.0

CCS2 (x2) 50.0

CHAdeMO (x2) 50.0

3 Hotel - restaurant Charging allowed

CHAdeMO 50.0

CCS2 50.0

TYPE 2 43.0

Tesla Dest. Charger 7.5

4 Private Tesla Dest. Charger 16.0

5 Supermarket Only for clients TYPE 2 (x2) 7.0

6 Hotel Only for clients

Tesla Dest. Charger (x2) 11.0

TYPE 2 11.0

7 Hotel - restaurant Only for clients Schuko (EU Plug) 22.0

8 Street charging Public TYPE 2 22.0

9 Street charging Public TYPE 2 22.0

10 Street charging Public

Schuko (EU Plug) 3.7

TYPE 2 22.0

11 Street charging Public TYPE 2 (x2) 22.0

12 Street charging

Public

(managed by

Iberdrola)

TYPE 2 43.0

CCS2 50.0

CHAdeMO 50.0

13 Car dealer Charging allowed CHAdeMO 50.0

14 Supermarket Only for clients TYPE 2 (x2) 7.0

Feasibility Study of using an Electric Vehicle in the Actual Infrastructure of a Small City in Spain

103

4 RESULTS AND DISCUSSION

The procedure adopts for this work is reported in

figure 3. The result of the simulation is indicated in a

graph in which remaining battery life is represented

as the SOC of the battery for each kilometre from the

starting point. It can show the desired results in this

way:

• If there is at least one point of the graph with SOC

lower than 20%, then theoretically this means that

the vehicle cannot reach the destination.

• The graph indicates the points where the last

charging station that is compatible with the

vehicle is located for charging before SOC

becomes lower than 20%. Those points are

represented in the graph as a step upwards until

SOC is equal to 100% by which time the battery

is fully charged.

• If SOC drops to 0%, the vehicle will stop. It is

possible that a graph could indicate that, after

SOC equals to 0, there is subsequently a

movement upwards until it reaches 100%. In such

case it represented that way in order to observe the

charging range afterwards at that charging station

if the vehicle’s battery is completely depleted but

is later recharged at the same station.

• If SOC never reaches 20%, it means that the

vehicle can reach the destination without charging

its battery during the trip.

Figure 3: Logical algorithm applied to the case study.

Figure 4 presents the simulation results for the

four vehicles in the trip from Cuenca to Madrid.

It is possible to charge a Citröen C-Zero’ battery

both in Cuenca and in Madrid’s commercial centre

because there are CHAdeMO connectors in both

cities. Thus, for a trip from Cuenca to Madrid and

then back to Cuenca, the battery will start with a full

charge both ways. The same is true for the remaining

vehicles because both locations have charging

stations with connectors TYPE 2. It is worth noting

that the return trip is undertaken on the assumption

that the vehicle came from Cuenca.

Once simulations have been done, the feasibility

study reaches the important part: analysis of results

and taking of decisions. Simulations indicate whether

or not electric vehicles can reach their destinations

and return again to Cuenca. If that is not possible,

some measures will be undertaken to resolve the

problems and assist the city of Cuenca to become

green and sustainable in the foreseeable future. For

the Citröen C-Zero, driving it to Madrid’s

commercial centre is not feasible because there are

points where SOC is lower than 20% and charging

stations are unavailable during the trip to charge the

battery. This presents the risk of battery depletion and

the vehicle would stop where SOC becomes 0%. For

the same reason when the trip initiates from Madrid,

it is also not possible to return to Cuenca.

Figure 4: Altitude profile from Cuenca to Madrid.

Simulation results from Cuenca to Madrid in the actual

driving conditions for different vehicles.

In the case of the Nissan Leaf, it is possible to get

to the commercial centre of Madrid and also return to

Cuenca. However, one stop is required halfway

through the journey to charge the battery. Going to

Madrid, the last compatible charging station before

SOC drops lower than 20% is located in the hotel-

restaurant of Fuentidueña de Tajo (point 3 of table 1).

For the return trip, the stop is recommended to be

located at the public charging station of Tarancón

(Point 2 of table 1).

The BMW i3 can similarly get to the destination

in Madrid but it will have to stop once on the way for

charging. The last compatible charging station is in

the supermarket of villarejo de Sabanés (Point 5 of

table 1). The same applies when returning to Cuenca

and the stop is recommended to be in Tarancón (Point

2 of table 1). Driving a Tesla model S, it is possible

reach the destination without any charging being

necessary. The same is the case when returning to

Cuenca. Table 2 is a summary of features of the trip

to Madrid.

CoEEE 2021 - International Joint Conference on Energy and Environmental Engineering

104

Table 2: Characteristics of the trip to Madrid in electric vehicle in the actual environment case study.

Charging

Station

Arrival

SOC [%]

Energy to

charge [kWh]

Cost

[€]

Connector

type

Power

[kW]

Time

[min]

Nissan

Leaf

Fuentidueña

de Ta

29.96 25.214 3.409 TYPE 2 7 216.123

Tarancón* 35.99 23.044 3.115 CHAdeMO 50 27.652

Madrid 67.23 11.797 1.595 CHAdeMO 50 14.157

Tarancón 48.10 18.684 2.526 CHAdeMO 50 22.421

Cuenca 39.33 21.841 2.953 CHAdeMO 50 26.209

Total Cost (€) 10,482

BWM i3

Villarejo de

Sabanés

24.47 28.626 3.870 TYPE 2 7 245.365

Tarancón* 40.09 22.706 3.069 CHAdeMO 50 27.247

Madrid 78.18 8.270 1.118 CCS2 50 9.924

Tarancón 51.54 18.366 2.483 TYPE 2 43 25.627

Cuenca 42.63 21.743 2.939 CCS2 50 26.092

Total Cost (€) 10.410

Tesla

model S

Madrid 58.55 39.3775 5.323 TYPE 2 43 54.945

Cuenca 53.56 44.118 5.964 TYPE 2 43 61.560

Total Cost (€) 11.287

*Alternative stop in Tarancón in order to spend less

time charging the battery.

The problem that occurred during the simulation

with Citröen C-Zero happened because it could not

reach Madrid. SOC of battery of Citröen C-Zero

drops to 20% after 42 km from Cuenca. Assuming

that it could get to the following charging stations at

Tarancón and Fuentidueña del Tajo, the Citröen C-

Zero would still not have reached Madrid without

another stop. It can thus be concluded that it is

impossible to travel from Cuenca to Madrid driving a

Citröen C-Zero. This limitation arises because there

are inadequate charging stations along the travel

route.

Two options are available to resolve it: add new

connectors to charging stations that are already

installed and functioning; or build new charging

stations. This is on the assumption that all the new

charging stations will be equipped with CHAdeMO

connectors with power 50 kW which is typical of

Iberdrola charging infrastructure. New charging

stations should be constructed at strategic points for

many reasons. Good locations would have service

centres such as restaurants, cafes, canteens and hotels

where drivers and other travellers can wait, refresh

themselves, eat or rest comfortably while the vehicle

is charging in a safe environment without the

discomfort of standing up throughout. Other possible

good locations will ideally be close to villages or

industrial areas where cheaper electrical equipment

and spares can easily be sourced since electrical

outlets are already installed, and also for staffing. To

avoid the vehicle’s SOC dropping lower than 20%, a

charging point is required before 42 km from Cuenca.

A village known as Naharros is located 35 km from

Cuenca, with a fuel station and a bar at its entrance.

This could be a good location for the first charging

station.

It will be impossible to reach Tarancón where two

additional charging stations can be found, without

charging once again. Carrascosa del Campo located

57 km from Cuenca, can be an ideal spot for this,

especially since it also has restaurants, hotels, a

medical centre and a service station.

The charging stations of Tarancón and

Fuentidueña del Tajo can be used. It is necessary to

add one more charging station before getting to

Madrid. If the charging station at the supermarket in

Villarejo de Sabanés has the capacity to charge with

Type 1 or CHAdeMO connectors, the problem will be

solved, and it would be possible to get to Madrid

driving a Citröen C-Zero (table 3).

Feasibility Study of using an Electric Vehicle in the Actual Infrastructure of a Small City in Spain

105

Table 3: Characteristics of the trip to Madrid for driving a Citröen C-Zero with new charging stations.

Charging Station

Arrival SOC

[%]

Energy to charge [kWh]

Cost

[€]

Time

[min]

Naharros 34.52 9.494 1.28 11.393

Carracosa del Campo 59.81 5.827 0.787 6.992

Tarancón 47.39 7.628 1.031 9.154

Villarejo de Sabanés 41.34 8.505 1.149 10.206

Madrid 37.05 9.127 1.233 10.952

Villarejo de Sabanés 24.19 10.992 1.486 13.190

Tarancón 39.30 8.801 1.189 10.561

Carrascosa del Campo 43.14 8.244 1.114 9.893

Naharros 56.06 6.371 0.861 7.645

Cuenca 38.22 8.958 1.210 10.750

Total Cost (€) 11.348

5 CONCLUSIONS

The scope of this work was to simulate certain

conditions in Cuenca, between Madrid and Valencia,

which uses electric mobility. The objective is to

conduct an appraisal of the use of electric mobility in

order to ascertain possible improvements or

developments that will be required in a green,

ecological and smart city in the future. In order to

facilitate this experiment, an electric vehicle was

driven from Cuenca to Madrid. Four commercial

vehicles with different characteristics have been

chosen for the simulations. The following

considerations can be drawn from the present study:

• It is not possible to travel to Madrid, the big city

closest to Cuenca, if the electric vehicle is similar

to the Citröen C-Zero, because of its weak battery

capacity. Sadly, this vehicle is economically

affordable by most people.

• It is possible to make a direct trip to Madrid with

powerful and expensive vehicles like Tesla model

S. Smaller, less powerful vehicles like Nissan

Leaf or BWM i3 can also make the trip if they stop

just once for charging. The problem however is

that most people cannot afford those vehicles.

• Province of Cuenca does not have many charging

stations. Most of the proposed new charging

stations which will enable driving the Citröen C-

Zero to destination are located in this area, where,

in spite of poor industry and depopulation, this

kind of infrastructure will be necessary in the

future.

• In the city of Cuenca there are different types of

connectors in charging stations, and these can

charge all types of vehicles. The problem is that

only one charging station is public whereas there

is an increasing number of electric vehicles being

sold.

• The use of electric vehicle and its infrastructure is

increasing in the larger cities in Spain such as

Madrid, Barcelona, Valencia and Bilbao, but not

in poorer and less populated areas. Government at

all levels should give incentives to electric vehicle

manufacturing companies to increase the number

of charging stations in areas similar to Cuenca

before encouraging people to buy electric

vehicles.

• Costs of driving an electric vehicle are much

lower than a conventional car that is powered by

fossil fuels.

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