Modelling of electric and parallel-hybrid electric vehicle using Matlab/Simulink environment and planning of charging stations through a geographic information system and genetic algorithms

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Abstract

In the last decades, the consumption of petrol in the transport sector has increased at a higher pace than in any other sector. Transport represents a quarter of the total amount of greenhouse gases and 36% of energy consumption in Spain. As a consequence, a new law regarding emissions has been approved. Such law regulates the acceptable emission levels of combustion gases for new vehicles sold in any of the European Union Member States. This work deals with parallel-hybrid electric vehicles in order to face the increasing environmental pollution and reduce energy consumption. The present paper shows a modelling of electric and parallel-hybrid electric vehicle using Matlab/Simulink environment which allows us to access different aspects of the vehicle such as engine power, type and size of the battery or weight and to observe how changes can affect the performance and the distance travelled. The model was simulated in order to obtain the electric vehicle's autonomy. Through the use of a Geographic Information System together with a mathematic algorithm based on genetic algorithms the planning of charging stations was obtained, where the installation investment cost was minimized and the geographic distribution was improved in order to increase the quality of the service by improving reliability. After a simulation which took place in a city of Spain, Zaragoza, losses were reduced from 156.60 € to 115.27 €.

Introduction

As a consequence of the use private vehicles with conventional internal combustion engines, petrol consumption in the transport sector has increased at a higher pace than in any other sector in the last decades. Due to the fact that some environmental problems are directly related to vehicle emissions such as the greenhouse effect, acid rain or photochemical smog, and taking into account that products derived from petrol will not last forever (diesel, gas, propane,…) [1], the automobile industry has opted to explore alternative solutions: developing vehicles which can consume and pollute less. Government agencies and organizations have developed stricter regulations regarding fuel consumption and emissions in order to reduce carbon dioxide emissions [2]. The concept Sustainable Mobility was developed because of people's concern about environmental and social problems caused by the use of private cars as general means of transport.

Some of the most relevant disadvantages of this model are air pollution, excess of energy consumption, effects on health or traffic routes overcrowding. Such disadvantages have led to a growing concern about finding some alternatives which can both avoid or minimize negative effects of this model and which help find a new one.

Since it reduces emissions to a minimum level and lowers its dependence on petrol, the electric vehicle is regarded as the best option. Electric vehicles are thus being investigated and modelled aiming at improving their performance. Besides, renewable energies are being used for battery charging of electric vehicles and plug-in electric vehicles [3], [4], [5], [6], [7], [8], [9], [10].

Contrary to internal combustion engine vehicles, the hybrid electric vehicle can help reduce carbon emissions. Nevertheless, a comparison between the hybrid electric vehicle and the full electric vehicle may show that the last one does not produce any emissions [11], [12], [13], [14], [15], [16], [17]. However, electricity production used does involve the use of pollutant emissions, especially when fossil primary energy is used.

Therefore, when analyzing the environmental impact of electric vehicles, emissions produced during the stage of electricity production should be the main focus of attention.

Table 1 shows emissions levels produced by different types of power stations:

To sum up, environmental advantages associated to the use of electric vehicles are:

  • A general decrease of pollutant emissions. A minimal contribution to acoustic pollution

  • An easier control of emission levels.

  • A decrease of dependence on petrol.

A basic fact which limits the development of these vehicles is the battery, as its autonomy (charge supplied to a battery) and energy capacity are not very high due to its inner characteristics [18], [19], [20] and the influence of some external agents such as temperature [21]. As a result, researchers are seeking for new more-efficient technologies [22], [23], [24] by using models which enable an accurate simulation of current-voltage behaviour [25].

As the battery needs to be recharged, it is necessary to build a recharging structure [26]. Places where batteries can be recharged are called charging stations. Several solutions may arise to fit the different of EV owners, namely:

  • charging stations devoted to fleets of EVs;

  • fast charging stations;

  • battery swapping stations;

  • domestic or public individual charging points for slower charging.

All cases need to be considered when addressing the problems that will result from this future shift in the mobility paradigm. However, in the present paper it is only considered slow charging in public charging points which are located in residential areas.

A large-scale increase in Electric Vehicle (EV) consumption is expected during charging periods. Additionally, EV will be able to provide the system with energy, which will also have an impact on electric grids.

The Project called Smart Grid is a way of efficient management of electricity which uses IT to optimize electricity production and distribution in order to find a balance between offer and demand between producers and consumers [27]. Such system consists of a special connection mode of the electric vehicle to the grid which establishes an intelligent link between both elements (battery and electric grid). Not only does it optimize charging times of batteries, but it also establishes a real energy management grid in which connected vehicles turn out to be energy accumulators which offer service to the grid in moments of high demand. This bidirectional flow of electric energy defines an electric map completely new which, moreover, benefits both the user and the electric grid [28].

Therefore, it is important to carry out a study in order to optimize their location. [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40].

The present paper offers the modelling of an electric vehicle and a parallel-hybrid electric vehicle. Henceforth, necessary data to optimize location of charging stations are obtained through a geographic information system and an optimization method based on genetic algorithm.

Section snippets

Modelling of electric vehicle

The modelling and simulation of an electric vehicle has been carried out with Matlab/Simulink programmes, R2013a.

The variables which have been taken into account during the modelling simulation are: type of driving cycle, type of battery, weather conditions, road inclination, vehicle weight and its surface. Simulation is completed when battery depth of discharge is equal or higher than 0.9.

Planning of charging stations

The planning of charging stations for electric vehicles is carried out by using an optimization algorithm called genetic algorithm.

Electric vehicle and parallel-hybrid electric vehicle

Simulation results shown in this section (Fig. 7) focus on the distance travelled by an electric vehicle depending on different parameters until a depth of discharge higher or equal to 0.9 is reached. Firstly, the system is simulated for the EPA Federal Test Procedure, commonly known as FTP-75 to the city driving cycle; both New European Driving Cycle (NEDC) and experimental driving cycle, which represent light traffic and congested traffic. These cycles are used to certify emissions from light

Conclusions

The present study offers a new approach in the development of computer programmes for planning charging stations taking the modelling of electric vehicles.

For the simulation of the electric vehicle, some external and internal factors have been taken into account in order to calculate the battery range. Such factors are: ways of conduction (different types of driving cycle), vehicle geometry (aerodynamic surface, tyre diameter and its drag coefficient), vehicle mass (weight of the empty vehicle

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