Develop the optimal solution for the electric vehicle operation management
Due to the worrisome rate of fossil fuels depletion and threats from global warming, relevant authorities have been pressured to look into green efforts in the current developments. With aims of creating a sustainable future, advances in the development of electric vehicles are widely discussed and...
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sg-ntu-dr.10356-535642023-03-04T19:27:55Z Develop the optimal solution for the electric vehicle operation management Gan, Jin Ni School of Mechanical and Aerospace Engineering Yoon Yongjin DRNTU::Engineering Due to the worrisome rate of fossil fuels depletion and threats from global warming, relevant authorities have been pressured to look into green efforts in the current developments. With aims of creating a sustainable future, advances in the development of electric vehicles are widely discussed and researched. Along with policy incentives, smart grid systems have been proposed to replace the conventional grids in order to accommodate high market penetration of electric vehicles in the near future. However, there are many factors to consider when large numbers of electric vehicles require simultaneous charging and optimization of these factors are required. This paper explores the optimization of overall charging performance via reduction of uplink feedback overhead while attaining maximum power delivery to all electric vehicles in the distribution network. By assimilating distribution of battery state of charge to gamma distribution, a close to reality prediction of electric vehicles’ battery profile can be obtained based on the estimated CDF. The uplink feedback overhead is shown to reduce by about 50% as compared to most of the existing smart charging system with slight trade off in the power delivery to the electric vehicles. The proposed charging scheme is shown to be feasible in scenarios where total power supply is able to meet load demand. The performance of proposed charging scheme can be improved and implemented with some modifications which require further research. Bachelor of Engineering (Mechanical Engineering) 2013-06-05T04:42:45Z 2013-06-05T04:42:45Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/53564 en Nanyang Technological University 67 p. application/pdf |
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DRNTU::Engineering Gan, Jin Ni Develop the optimal solution for the electric vehicle operation management |
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Due to the worrisome rate of fossil fuels depletion and threats from global warming, relevant authorities have been pressured to look into green efforts in the current developments. With aims of creating a sustainable future, advances in the development of electric vehicles are widely discussed and researched. Along with policy incentives, smart grid systems have been proposed to replace the conventional grids in order to accommodate high market penetration of electric vehicles in the near future. However, there are many factors to consider when large numbers of electric vehicles require simultaneous charging and optimization of these factors are required. This paper explores the optimization of overall charging performance via reduction of uplink feedback overhead while attaining maximum power delivery to all electric vehicles in the distribution network. By assimilating distribution of battery state of charge to gamma distribution, a close to reality prediction of electric vehicles’ battery profile can be obtained based on the estimated CDF. The uplink feedback overhead is shown to reduce by about 50% as compared to most of the existing smart charging system with slight trade off in the power delivery to the electric vehicles. The proposed charging scheme is shown to be feasible in scenarios where total power supply is able to meet load demand. The performance of proposed charging scheme can be improved and implemented with some modifications which require further research. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Gan, Jin Ni |
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Final Year Project |
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Gan, Jin Ni |
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Gan, Jin Ni |
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Develop the optimal solution for the electric vehicle operation management |
title_short |
Develop the optimal solution for the electric vehicle operation management |
title_full |
Develop the optimal solution for the electric vehicle operation management |
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Develop the optimal solution for the electric vehicle operation management |
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Develop the optimal solution for the electric vehicle operation management |
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develop the optimal solution for the electric vehicle operation management |
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2013 |
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http://hdl.handle.net/10356/53564 |
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