A Novel Energy Optimization Approach for Electrical Vehicles in a Smart City
Electric Vehicles (EVs) have emerged rapidly across the globe as a powerful eco-friendly initiative that if integrated well with an urban environment could be iconic for the city’ host’s commitment to sustainable mobility and be a key ingredient of the smart city concept. This pa...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-03-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1996-1073/12/5/929 |
| _version_ | 1818035770527580160 |
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| author | Flah Aymen Chokri Mahmoudi |
| author_facet | Flah Aymen Chokri Mahmoudi |
| author_sort | Flah Aymen |
| collection | DOAJ |
| description | Electric Vehicles (EVs) have emerged rapidly across the globe as a powerful eco-friendly initiative that if integrated well with an urban environment could be iconic for the city’ host’s commitment to sustainable mobility and be a key ingredient of the smart city concept. This paper examines ways that will help us to develop a better understanding of how EVs can achieve energy use optimization and be connected with a smart city. As a whole, the present study is based on an original idea that would be useful in informing policy-makers, automotive manufacturers and transport operators of how to improve and embrace better EV technologies in the context of smart cities. The proposed approach is based on vehicles and buildings communication for sharing some special information related to the vehicle status and to the road condition. EVs can share their own information related to the energy experience on a specific path. This information can be gathered in a gigantic database and used for managing the power inside these vehicles. In this field, this paper exposes a new approach to power management inside an electric vehicle based on bi-communication between vehicles and buildings. The principle of this method is established on two sections; the first one is related to vehicles’ classification and the second one is attached to the buildings’ recommendation, according to the car position. The classification problem is resolved using the support vector classification method. The recommendation phase is resolved using the artificial intelligence principle and the neural network was employed, for giving the best decision. The optimal decision will be calculated inside the building, according to its position and using the old vehicle’s data, and transferred to the coming vehicle, for optimizing its energy consumption method in the corresponding building zone. Different possibilities and situations were discussed in this approach. The proposed power management methodology was tested and validated using Simulink/Matlab tool. Results related to the battery state of charge and to the consumed energy were compared at the end of this work, for showing the efficiency of this approach. |
| first_indexed | 2024-12-10T07:00:20Z |
| format | Article |
| id | doaj.art-92fa7d112a914d4f843c7c4858486859 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-12-10T07:00:20Z |
| publishDate | 2019-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-92fa7d112a914d4f843c7c48584868592022-12-22T01:58:20ZengMDPI AGEnergies1996-10732019-03-0112592910.3390/en12050929en12050929A Novel Energy Optimization Approach for Electrical Vehicles in a Smart CityFlah Aymen0Chokri Mahmoudi1Laboratory of Proceeding, Energetic, Environment and Electric Systems LR18E534, National School of Engineering of Gabès, University of Gabès, Gabès 6072, TunisiaLaboratory of Proceeding, Energetic, Environment and Electric Systems LR18E534, National School of Engineering of Gabès, University of Gabès, Gabès 6072, TunisiaElectric Vehicles (EVs) have emerged rapidly across the globe as a powerful eco-friendly initiative that if integrated well with an urban environment could be iconic for the city’ host’s commitment to sustainable mobility and be a key ingredient of the smart city concept. This paper examines ways that will help us to develop a better understanding of how EVs can achieve energy use optimization and be connected with a smart city. As a whole, the present study is based on an original idea that would be useful in informing policy-makers, automotive manufacturers and transport operators of how to improve and embrace better EV technologies in the context of smart cities. The proposed approach is based on vehicles and buildings communication for sharing some special information related to the vehicle status and to the road condition. EVs can share their own information related to the energy experience on a specific path. This information can be gathered in a gigantic database and used for managing the power inside these vehicles. In this field, this paper exposes a new approach to power management inside an electric vehicle based on bi-communication between vehicles and buildings. The principle of this method is established on two sections; the first one is related to vehicles’ classification and the second one is attached to the buildings’ recommendation, according to the car position. The classification problem is resolved using the support vector classification method. The recommendation phase is resolved using the artificial intelligence principle and the neural network was employed, for giving the best decision. The optimal decision will be calculated inside the building, according to its position and using the old vehicle’s data, and transferred to the coming vehicle, for optimizing its energy consumption method in the corresponding building zone. Different possibilities and situations were discussed in this approach. The proposed power management methodology was tested and validated using Simulink/Matlab tool. Results related to the battery state of charge and to the consumed energy were compared at the end of this work, for showing the efficiency of this approach.http://www.mdpi.com/1996-1073/12/5/929smart citypower managementelectric vehicleoptimizationclassificationstate of chargeintelligence |
| spellingShingle | Flah Aymen Chokri Mahmoudi A Novel Energy Optimization Approach for Electrical Vehicles in a Smart City Energies smart city power management electric vehicle optimization classification state of charge intelligence |
| title | A Novel Energy Optimization Approach for Electrical Vehicles in a Smart City |
| title_full | A Novel Energy Optimization Approach for Electrical Vehicles in a Smart City |
| title_fullStr | A Novel Energy Optimization Approach for Electrical Vehicles in a Smart City |
| title_full_unstemmed | A Novel Energy Optimization Approach for Electrical Vehicles in a Smart City |
| title_short | A Novel Energy Optimization Approach for Electrical Vehicles in a Smart City |
| title_sort | novel energy optimization approach for electrical vehicles in a smart city |
| topic | smart city power management electric vehicle optimization classification state of charge intelligence |
| url | http://www.mdpi.com/1996-1073/12/5/929 |
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