scholarly journals Minimization of Construction Costs for an All Battery-Swapping Electric-Bus Transportation System: Comparison with an All Plug-In System

Author(s):  
Shyang-Chyuan Fang ◽  
Bwo-Ren Ke ◽  
Chen-Yuan Chung

The greenhouse gases and air pollution generated by extensive energy use have exacerbated climate change. An electric-bus (e-bus) transportation system favors reducing pollution and carbon emissions. This study analyzed the minimization of construction costs for an all battery-swapping public e-bus transportation system. A simulation was conducted according to existing timetables and routes. Daytime charging was incorporated during the hours of operation; the two parameters of the daytime charging scheme were the residual battery capacity and battery-charging energy during various intervals of daytime peak electricity hours. The parameters were optimized using three algorithms: particle swarm optimization (PSO), a genetic algorithm (GA), and a PSO–GA. This study observed the effects of optimization on cost changes (e.g., number of e-buses, on-board battery capacity, number of extra batteries, charging facilities, and energy consumption) and compared the plug-in and battery-swapping e-bus systems. The results revealed that daytime charging can reduce the construction costs of both systems. In contrast to the other two algorithms, the PSO–GA yielded the most favorable optimization results for the charging scheme. Finally, according to the cases investigated and the parameters of this study, the construction cost of the plug-in e-bus system was lower than that of the battery-swapping e-bus system.

2015 ◽  
Vol 7 (3) ◽  
pp. 349-356 ◽  
Author(s):  
Kenichiro Eda ◽  
Ryutaro Kanaga ◽  
Weihsiang Yang ◽  
Toshio Hirota ◽  
Yushi Kamiya ◽  
...  

2017 ◽  
Vol 2647 (1) ◽  
pp. 100-108 ◽  
Author(s):  
Zhaocai Liu ◽  
Ziqi Song ◽  
Yi He

Diesel engine buses still make up the majority of the bus fleet in the United States, even with the problem of diesel exhaust and greenhouse gas emissions. Electric buses, which generate no emissions, are a promising green alternative for bus fleets. However, electric buses have a limited travel range and a time-consuming recharging process. Dynamic wireless charging, which allows electric buses to charge while traveling, could alleviate the drawbacks of electric buses. With dynamic wireless charging technology, electric buses can operate with smaller batteries, and the stationary recharging time at the base station can be shortened. The key design variables in deploying dynamic wireless charging facilities for an electric bus system are battery size and the location of the wireless charging facilities. This paper addresses the problem of simultaneously selecting the optimal locations for the wireless charging facilities and designing the battery size for an electric bus system. A mixed integer linear program was developed to minimize the total implementation cost. The model was demonstrated with a real-world bus system. The results demonstrate that the proposed model can solve the optimal deployment problem of dynamic wireless charging facilities for an electric bus system.


Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1229 ◽  
Author(s):  
Hyukjoon Lee ◽  
Dongjin Ji ◽  
Dong-Ho Cho

The design of conventional electric vehicles (EVs) is affected by numerous limitations, such as a short travel distance and long charging time. As one of the first wireless charging systems, the Online Electric Vehicle (OLEV) was developed to overcome the limitations of the current generation of EVs. Using wireless charging, an electric vehicle can be charged by power cables embedded in the road. In this paper, a model and algorithm for the optimal design of a wireless charging electric bus system is proposed. The model is built using a Markov decision process and is used to verify the optimal number of power cables, as well as optimal pickup capacity and battery capacity. Using reinforcement learning, the optimization problem of a wireless charging electric bus system in a diverse traffic environment is then solved. The numerical results show that the proposed algorithm maximizes average reward and minimizes total cost. We show the effectiveness of the proposed algorithm compared with obtaining the exact solution via mixed integer programming (MIP).


1993 ◽  
Vol 03 (02) ◽  
pp. 157-164 ◽  
Author(s):  
P. THANGAVEL ◽  
V.P. MUTHUSWAMY

A simple parallel algorithm for generating N-ary reflected Gray codes is presented. The algorithm is derived from the pattern of N-ary reflected Gray codes. The algorithm runs on a linear processor array with a reconfigurable bus system. A reconfigurable bus system is a bus system whose configuration can be dynamically changed. Recently processor arrays with reconfigurable bus systems were used to solve many problems in constant time. There already exists experimental reconfigurable chips.


2018 ◽  
Vol 30 (4) ◽  
pp. 559-585 ◽  
Author(s):  
Saša Obradović ◽  
Nemanja Lojanica

The European Union has set the target that by 2020 harmful emissions and energy consumption should be reduced by 20% compared to the 1990s. This paper examines the impacts of environmental quality on two parameters of national competitiveness (exports and GDP per capita). The study focuses on the EU-15 countries and covers the period from 1960 to 2013. Even though the analyzed economies are developed countries which are the leaders in environment protection, they are still also the leading emitters of greenhouse gases. The paper uses traditional econometric techniques to test the relations between energy use, CO2 emissions, exports and GDP. The results show that the variables are co-integrated. In addition, energy-led growth hypothesis is valid in most of the analyzed economies. The results have also shown that increased CO2 emissions reduce economic activity and export performance. Finally, we will conclude that there are two tasks for future policy makers: first, to strengthen renewable-energy goals, and second, to adjust the economic structure towards less harmful emissions. In such circumstances, we could expect the economies to further develop clean technologies and to obtain their benefits for national competitiveness.


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