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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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  • Alegre, Susana
  • Míguez, Juan V.
  • Carpio, José

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 €.

Suggested Citation

  • Alegre, Susana & Míguez, Juan V. & Carpio, José, 2017. "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," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1020-1027.
    • Handle: RePEc:eee:rensus:v:74:y:2017:i:c:p:1020-1027
    DOI: 10.1016/j.rser.2017.03.041
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    Cited by:

    1. Zhang, Yue & Zhang, Qi & Farnoosh, Arash & Chen, Siyuan & Li, Yan, 2019. "GIS-Based Multi-Objective Particle Swarm Optimization of charging stations for electric vehicles," Energy, Elsevier, vol. 169(C), pages 844-853.
    2. Zhang Yue & Arash Farnoosh & Qi Zang & Siyuan Chen, 2018. "GIS-Based Multi-Objective Particle Swarm Optimization of Charging Station of Electric Vehicles – Taking a District in Beijing as an Example," Working Papers hal-03187920, HAL.
    3. Csiszár, Csaba & Csonka, Bálint & Földes, Dávid & Wirth, Ervin & Lovas, Tamás, 2019. "Urban public charging station locating method for electric vehicles based on land use approach," Journal of Transport Geography, Elsevier, vol. 74(C), pages 173-180.

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