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Keywords = number of charging stops

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20 pages, 4673 KiB  
Article
Sizing Methodology of Dynamic Wireless Charging Infrastructures for Electric Vehicles in Highways: An Italian Case Study
by Valerio Apicella, Alessandro Turati, Giovanni Megna and Benedetto Carambia
Energies 2024, 17(16), 3922; https://doi.org/10.3390/en17163922 - 8 Aug 2024
Cited by 1 | Viewed by 1754
Abstract
The necessity of pushing the road mobility towards more sustainable solutions has become of undeniable importance in last years. For this reason, both research and industry are constantly investigating new technologies able to make the usage of battery electric vehicles(BEV) [...] Read more.
The necessity of pushing the road mobility towards more sustainable solutions has become of undeniable importance in last years. For this reason, both research and industry are constantly investigating new technologies able to make the usage of battery electric vehicles(BEV) as accessible and usable as traditional internal combustion engine vehicles (ICEV). One of the most limiting issues concerns the short range of electric vehicles, which complicates their use for long distances, such as for highway travels. A promising solution seems to be the “charge-while-driving” approach, by exploiting the inductive dynamic wireless power transfer (DWPT) technology. Nevertheless, such systems show different issues, first of all, high investment and maintenance costs. Furthermore, it is not clear how extensive a potential dynamic wireless charging infrastructure needs to be to make a real advantage for electric vehicle drivers. As a consequence, the aim of this paper is to introduce a new methodology to estimate the number and length of wireless charging sections necessary to allow the maximum number of electric vehicles to travel a specific highway without the need to stop for a recharge at a service area. Specifically, the methodology is based on a algorithm that, starting by real traffic data, simulates vehicle flows and defines the basic layout of the wireless charging infrastructure. This simulator can provide a decision support tool for highway road operators. Full article
(This article belongs to the Section F: Electrical Engineering)
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17 pages, 1064 KiB  
Article
Coordinated Charging Scheduling Approach for Plug-In Hybrid Electric Vehicles Considering Multi-Objective Weighting Control in a Large-Scale Future Smart Grid
by Wei Li, Jiekai Shi and Hanyun Zhou
Energies 2024, 17(13), 3148; https://doi.org/10.3390/en17133148 - 26 Jun 2024
Cited by 2 | Viewed by 1496
Abstract
The growing popularity of plug-in hybrid electric vehicles (PHEVs) is due to their environmental advantages. But uncoordinated charging of a large number of PHEVs can lead to a significant surge in peak loads and higher charging costs for PHEV owners. To end this, [...] Read more.
The growing popularity of plug-in hybrid electric vehicles (PHEVs) is due to their environmental advantages. But uncoordinated charging of a large number of PHEVs can lead to a significant surge in peak loads and higher charging costs for PHEV owners. To end this, this paper introduces an innovative approach to address the issue by proposing a multi-objective weighting control for coordinated charging of PHEVs in a future smart grid, which aims to find an economically optimal solution while also considering load stabilization with large-scale PHEV penetration. Technical constraints related to the owner’s demand and power limitations are considered. In the proposed approach, the charging behavior of PHEV owners is modeled by a normal distribution. It is observed that owners typically start charging their vehicles when they arrive home and stop charging when they go to their workplace. The charging cost is then calculated based on the tiered electricity price and charging power. By adjusting the cost weighting factor and the load stability weighting factor in the multi-objective function, the grid allows for flexible weight selection between the two objectives. This approach effectively encourages owners to actively participate in coordinated charging scheduling, which sets it apart from existing works. The algorithm offers better robustness and adaptability for large-scale PHEV penetration, making it highly relevant for the future smart grid. Finally, numerical simulations are presented to demonstrate the desirable performance of theory and simulation. Full article
(This article belongs to the Section A1: Smart Grids and Microgrids)
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23 pages, 5821 KiB  
Article
Optimizing Charging Pad Deployment by Applying a Quad-Tree Scheme
by Rei-Heng Cheng, Chang-Wu Yu and Zuo-Li Zhang
Algorithms 2024, 17(6), 264; https://doi.org/10.3390/a17060264 - 14 Jun 2024
Cited by 3 | Viewed by 1089
Abstract
The recent advancement in wireless power transmission (WPT) has led to the development of wireless rechargeable sensor networks (WRSNs), since this technology provides a means to replenish sensor nodes wirelessly, offering a solution to the energy challenges faced by WSNs. Most of the [...] Read more.
The recent advancement in wireless power transmission (WPT) has led to the development of wireless rechargeable sensor networks (WRSNs), since this technology provides a means to replenish sensor nodes wirelessly, offering a solution to the energy challenges faced by WSNs. Most of the recent previous work has focused on charging sensor nodes using wireless charging vehicles (WCVs) equipped with high-capacity batteries and WPT devices. In these schemes, a vehicle can move close to a sensor node and wirelessly charge it without physical contact. While these schemes can mitigate the energy problem to some extent, they overlook two primary challenges of applied WCVs: off-road navigation and vehicle speed limitations. To overcome these challenges, previous work proposed a new WRSN model equipped with one drone coupled with several pads deployed to charge the drone when it cannot reach the subsequent stop. This wireless charging pad deployment aims to deploy the minimum number of pads so that at least one feasible routing path from the base station can be established for the drone to reach every SN in a given WRSN. The major weakness of previous studies is that they only consider deploying a wireless charging pad at the locations of the wireless sensor nodes. Their schemes are limited and constrained because usually every point in the deployed area can be considered to deploy a pad. Moreover, the deployed pads suggested by these schemes may not be able to meet the connected requirements due to sparse environments. In this work, we introduce a new scheme that utilizes the Quad-Tree concept to address the wireless charging pad deployment problem and reduce the number of deployed pads at the same time. Extensive simulations were conducted to illustrate the merits of the proposed schemes by comparing them with different previous schemes on maps of varying sizes. In the case of large maps, the proposed schemes surpassed all previous works, indicating that our approach is more suitable for large-scale network environments. Full article
(This article belongs to the Collection Feature Paper in Algorithms and Complexity Theory)
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20 pages, 2471 KiB  
Article
Interactions of Low-Energy Muons with Silicon: Numerical Simulation of Negative Muon Capture and Prospects for Soft Errors
by Jean-Luc Autran and Daniela Munteanu
J. Nucl. Eng. 2024, 5(1), 91-110; https://doi.org/10.3390/jne5010007 - 5 Mar 2024
Cited by 1 | Viewed by 2237
Abstract
In this paper, the interactions of low-energy muons (E < 10 MeV) with natural silicon, the basic material of microelectronics, are studied by Geant4 and SRIM simulation. The study is circumscribed to muons susceptible to slowdown/stop in the target and able to transfer [...] Read more.
In this paper, the interactions of low-energy muons (E < 10 MeV) with natural silicon, the basic material of microelectronics, are studied by Geant4 and SRIM simulation. The study is circumscribed to muons susceptible to slowdown/stop in the target and able to transfer sufficient energy to the semiconductor to create single events in silicon devices or related circuits. The capture of negative muons by silicon atoms is of particular interest, as the resulting nucleus evaporation and its effects can be catastrophic in terms of the emission of secondary ionizing particles ranging from protons to aluminum ions. We investigate in detail these different nuclear capture reactions in silicon and quantitatively evaluate their relative importance in terms of number of products, energy, linear energy transfer, and range distributions, as well as in terms of charge creation in silicon. Finally, consequences in the domain of soft errors in microelectronics are discussed. Full article
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18 pages, 5843 KiB  
Article
Fast Design and Numerical Simulation of a Metal Hydride Reactor Embedded in a Conventional Shell-and-Tube Heat Exchanger
by Ruizhe Ran, Jing Wang, Fusheng Yang and Rahmatjan Imin
Energies 2024, 17(3), 712; https://doi.org/10.3390/en17030712 - 1 Feb 2024
Viewed by 2213
Abstract
The purpose of this work is to present a convenient design approach for metal hydride reactors that meet the specific requirements for hydrogen storage. Three methods from the literature, the time scale, the acceptable envelope, and the reaction front, are used to estimate [...] Read more.
The purpose of this work is to present a convenient design approach for metal hydride reactors that meet the specific requirements for hydrogen storage. Three methods from the literature, the time scale, the acceptable envelope, and the reaction front, are used to estimate the maximum thickness of the bed allowing for sufficient heat transfer. Further heat transfer calculations are performed within the framework of standardized heat exchanger via the homemade design software, to generate the complete geometry and dimensions of the reactor. LaNi5 material packed in tubular units based on conventional shell-and-tube heat exchanger is selected for analysis for an expected charging time of 500 s, 1000 s, and 1500 s. Apparently, the smaller the expected charging time, the smaller the bed thickness and hence the diameter of the tubular units. After comparison, the method of reaction front was adopted to output standard tube diameters and calculate the weight of the reactor. Significant weight differences were found to result from the varying wall thickness and number of tubes. In general, the shorter the expected charging time, the more tubular units with a small diameter will be built and the heavier the reactor. Fluent 2022 R2 was used to solve the reactor model with a tube diameter of 50 mm supposed to fulfill a charging time of 1500 s. The simulation results revealed that the reaction fraction reaches its maximum and the hydrogen storage process is completed at 500 s. However, because the calculation is conducted on meeting the heat exchange requirements, the average temperature of the bed layer is close to the initial temperature of 290 K and stops changing at 1500 s. The applicability of the method to the design of metal hydride reactors is thus confirmed by the temperature and reaction fraction judgment criteria. Full article
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19 pages, 10330 KiB  
Article
An Enhanced Path Planner for Electric Vehicles Considering User-Defined Time Windows and Preferences
by Maximiliano Cubillos, Mauro Dell’Amico, Ola Jabali, Federico Malucelli and Emanuele Tresoldi
Energies 2023, 16(10), 4173; https://doi.org/10.3390/en16104173 - 18 May 2023
Cited by 4 | Viewed by 2023
Abstract
A number of decision support tools facilitating the use of Electric Vehicles (EVs) have been recently developed. Due to the EVs’ limited autonomy, routing and path planning are the main challenges treated in such tools. Specifically, determining at which Charging Stations (CSs) to [...] Read more.
A number of decision support tools facilitating the use of Electric Vehicles (EVs) have been recently developed. Due to the EVs’ limited autonomy, routing and path planning are the main challenges treated in such tools. Specifically, determining at which Charging Stations (CSs) to stop, and how much the EV should charge at them is complex. This complexity is further compounded by the fact that charging times depend on the CS technology, the EV characteristics, and follow a nonlinear function. Considering these factors, we propose a path-planning methodology for EVs with user preferences, where charging is performed at public CSs. To achieve this, we introduce the Electric Vehicle Shortest Path Problem with time windows and user preferences (EVSPPWP) and propose an efficient heuristic algorithm for it. Given an origin and a destination, the algorithm prioritizes CSs close to Points of Interest (POIs) that match user inputted preferences, and user-defined time windows are considered for activities such as lunch and spending the night at hotels. The algorithm produces flexible solutions by considering clusters of charging points (CPs) as separate CSs. Furthermore, the algorithm yields resilient paths by ensuring that recommended paths have a minimum number of CSs in their vicinity. The main contributions of our methodology are the following: modeling user-defined time windows, including user-defined weights for different POI categories, creating CSs based on clusters of CPs with sufficient proximity, using resilient paths, and proposing an efficient algorithm for solving the EVSPPWP. To facilitate the use of our methodology, the algorithm was integrated into a web interface. We demonstrate the use of the web interface, giving usage examples and comparing different settings. Full article
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16 pages, 2589 KiB  
Article
Design of Electric Bus Transit Routes with Charging Stations under Demand Uncertainty
by Xiaoqing Su, Lanqing Jiang and Yucheng Huang
Energies 2023, 16(4), 1848; https://doi.org/10.3390/en16041848 - 13 Feb 2023
Cited by 7 | Viewed by 2394
Abstract
This paper investigates the design problem of an electric bus (E-bus) route with charging stations to smooth the operations between E-bus service and charging. The design variables include the locations of E-bus stops, number of charging piles at charging stations, fare, and headway. [...] Read more.
This paper investigates the design problem of an electric bus (E-bus) route with charging stations to smooth the operations between E-bus service and charging. The design variables include the locations of E-bus stops, number of charging piles at charging stations, fare, and headway. A mathematical programming model is proposed to maximize social welfare in consideration of the uncertain charging demand at charging stations. The model solution algorithm is also designed. The model and algorithm are demonstrated on the E-bus route 931 in the city of Suzhou, China. The results of the case studies show that (i) the right number of stops on a bus route can contribute to the highest social welfare; (ii) the pile–bus ratio decreases with the increase of E-bus fleet size, thereby improving the E-bus charging efficiency at charging stations; and (iii) deploying charging stations at one end of a bus route can achieve a shorter waiting time for E-bus compared with deployment at two ends. Full article
(This article belongs to the Special Issue Energy Saving in Traffic Infrastructure)
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17 pages, 1160 KiB  
Article
Linear Programming-Based Power Management for a Multi-Feeder Ultra-Fast DC Charging Station
by Luigi Rubino, Guido Rubino and Raffaele Esempio
Energies 2023, 16(3), 1213; https://doi.org/10.3390/en16031213 - 22 Jan 2023
Cited by 23 | Viewed by 2791
Abstract
The growing number of electric vehicles (EVs) affects the national electricity system in terms of power demand and load variation. Turning our attention to Italy, the number of vehicles on the road is 39 million; this represents a major challenge, as they will [...] Read more.
The growing number of electric vehicles (EVs) affects the national electricity system in terms of power demand and load variation. Turning our attention to Italy, the number of vehicles on the road is 39 million; this represents a major challenge, as they will need to be recharged constantly when the transition to electric technology is complete. If we consider that the average power is 55 GW and the installed system can produce 120 GW of peak power, we can calculate that with only 5% of vehicles in recharging mode, the power demand increases to 126 GW, which is approximately 140% of installed power. The integration of renewable energy sources will help the grid, but this solution is less useful for handling large load variations that negatively affect the grid. In addition, some vehicles committed to public utility must have a reduced stop time and can be considered to have higher priority. The introduction of priorities implies that the power absorption limit cannot be easily introduced by limiting the number of charging vehicles, but rather by computing the power flow that respects constraints and integrates renewable and local storage power contributions. The problem formulated in this manner does not have a unique solution; in this study, the linear programming method is used to optimise renewable resources, local storage, and EVs to mitigate their effects on the grid. Simulations are performed to verify the proposed method. Full article
(This article belongs to the Special Issue Research and Technology Development in Electric Power Systems)
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17 pages, 5928 KiB  
Article
A Low-Cost Hardware Architecture for EV Battery Cell Characterization Using an IoT-Based Platform
by Rafael Martínez-Sánchez, Ángel Molina-García, Alfonso P. Ramallo-González, Juan Sánchez-Valverde and Benito Úbeda-Miñarro
Sensors 2023, 23(2), 816; https://doi.org/10.3390/s23020816 - 10 Jan 2023
Cited by 7 | Viewed by 3442
Abstract
Since 1997, when the first hybrid vehicle was launched on the market, until today, the number of NIMH batteries that have been discarded due to their obsolescence has not stopped increasing, with an even faster rate more recently due to the progressive disappearance [...] Read more.
Since 1997, when the first hybrid vehicle was launched on the market, until today, the number of NIMH batteries that have been discarded due to their obsolescence has not stopped increasing, with an even faster rate more recently due to the progressive disappearance of thermal vehicles on the market. The battery technologies used are mostly NIMH for hybrid vehicles and Li ion for pure electric vehicles, making recycling difficult due to the hazardous materials they contain. For this reason, and with the aim of extending the life of the batteries, even including a second life within electric vehicle applications, this paper describes and evaluates a low-cost system to characterize individual cells of commercial electric vehicle batteries by identifying such abnormally performing cells that are out of use, minimizing regeneration costs in a more sustainable manner. A platform based on the IoT technology is developed, allowing the automation of charging and discharging cycles of each independent cell according to some parameters given by the user, and monitoring the real-time data of such battery cells. A case study based on a commercial Toyota Prius battery is also included in the paper. The results show the suitability of the proposed solution as an alternative way to characterize individual cells for subsequent electric vehicle applications, decreasing operating costs and providing an autonomous, flexible, and reliable system. Full article
(This article belongs to the Special Issue Feature Papers in the Internet of Things Section 2022)
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21 pages, 5413 KiB  
Article
Spatial Heterogeneity Analysis for Influencing Factors of Outbound Ridership of Subway Stations Considering the Optimal Scale Range of “7D” Built Environments
by Zhenbao Wang, Jiarui Song, Yuchen Zhang, Shihao Li, Jianlin Jia and Chengcheng Song
Sustainability 2022, 14(23), 16314; https://doi.org/10.3390/su142316314 - 6 Dec 2022
Cited by 17 | Viewed by 2831
Abstract
The accuracy of the regression model of ridership of subway stations depends on the scale range of the built environment around the subway stations. Previous studies have not considered the Modifiable Area Unit Problem (MAUP) to establish the regression model of subway station [...] Read more.
The accuracy of the regression model of ridership of subway stations depends on the scale range of the built environment around the subway stations. Previous studies have not considered the Modifiable Area Unit Problem (MAUP) to establish the regression model of subway station ridership. Taking Beijing as an example, this paper expanded the built environment variables from “5D” category to “7D” category, added indicators such as parking fee standard and population density factor, and proposed a Multi-Scale Geographical Weighted Regression (MGWR) model of outbound ridership of subway stations with standardized variables. The goodness of fit of regression models under 10 spatial scales or built environment around subway stations are compared, and the spatial heterogeneity of built environment factors under the optimal spatial scale of outbound ridership of subway stations during the morning peak on weekdays is discussed. The results show that: (1) the scale range overlapped by 1000 m radius circular buffer zone and Thiessen polygon has the highest explanatory power for the regression model, and is regarded as the optimal scale range of built environment; (2) the density of office facilities, sports and leisure facilities, medical service facilities, building density and floor area ratio (FAR) has a significant impact on the outbound ridership of all subway stations; (3) office facilities, catering facilities, FAR, number of parking lots, and whether subway stations are transfer stations have a positive impact on outbound ridership. The number of medical service facilities, sports and leisure facilities, bus stops and building density have a negative impact on outbound ridership; (4) the two added factors in this study: parking charge standard and population density, as the influencing factors of the built environment, have a significant impact on the outbound ridership of some subway stations; and (5) the different local coefficients of the built environment factors at different stations are discussed, which indicate the spatial heterogeneity on the outbound ridership. The results can provide an important theoretical basis for the prediction and analysis of demand of ridership at subway stations and the integration of the built environment around the stations. Full article
(This article belongs to the Special Issue Urban and Social Geography and Sustainability)
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18 pages, 3863 KiB  
Article
Analysis of Urban Electric Vehicle Trip Rule Statistics and Ownership Prediction
by Hui Gao, Lutong Yang, Anyue Zhang and Mingxin Sheng
Symmetry 2021, 13(11), 2052; https://doi.org/10.3390/sym13112052 - 31 Oct 2021
Cited by 6 | Viewed by 2894
Abstract
In order to play the important role of electric vehicles to promote the realization of the 3060 double carbon target, electric vehicles have seen explosive growth. However, due to the tight symmetry between the number and distribution of electric vehicles and their corresponding [...] Read more.
In order to play the important role of electric vehicles to promote the realization of the 3060 double carbon target, electric vehicles have seen explosive growth. However, due to the tight symmetry between the number and distribution of electric vehicles and their corresponding charging facilities, the layout of charging facilities has higher requirements. This paper collects travel data in the form of a traffic travel questionnaire for electric vehicle users. Based on the vehicle parking demand model of the queuing theory and Monte Carlo simulation, the paper gives the number of stopping vehicles and the time of vehicles stopping in different places such as residential areas, workplaces, supermarket parking and roadside. In addition, based on the Bass prediction model, the main parameters are modeled in the model, and the price correction coefficient is introduced. The improved Bass model is used to predict the growth trend of electric vehicles in different regions in different years and in different incentive sites. By predicting the ownership of urban electric vehicles and accurately grasping the distribution and operation of electric vehicles, this paper can provide guidance and suggestions for the planning and construction of charging facilities in different regions, effectively reduce the investment cost of charging facilities and guide local governments to formulate reasonable planning schemes. Full article
(This article belongs to the Special Issue Symmetry in Power Battery Management Systems)
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21 pages, 8277 KiB  
Article
Novel Cu/Zn Reinforced Polymer Composites: Experimental Characterization for Radiation Protection Efficiency (RPE) and Shielding Properties for Alpha, Proton, Neutron, and Gamma Radiations
by Ghada ALMisned, F. Akman, Waheed S. AbuShanab, Huseyin O. Tekin, Mustata R. Kaçal, Shams A. M. Issa, Hasan Polat, Meral Oltulu, Antoaneta Ene and Hesham M. H. Zakaly
Polymers 2021, 13(18), 3157; https://doi.org/10.3390/polym13183157 - 17 Sep 2021
Cited by 30 | Viewed by 3882
Abstract
In this study, brass (Cu/Zn) reinforced polymer composites with different proportions of brass powders were fabricated. Different types of nuclear shielding parameters such as mass and linear attenuation coefficients, radiation protection efficiency, half and tenth value layers, and effective atomic number values were [...] Read more.
In this study, brass (Cu/Zn) reinforced polymer composites with different proportions of brass powders were fabricated. Different types of nuclear shielding parameters such as mass and linear attenuation coefficients, radiation protection efficiency, half and tenth value layers, and effective atomic number values were determined experimentally and theoretically in the energy range of 0.060–1.408 MeV in terms of gamma-ray shielding capabilities of fabricated polymer composites. A high Purity Germanium detector (HPGe) in conjunction with a Multi-Channel Analyzer (MCA) and twenty-two characteristic gamma-ray energies have been used in the experimental phase. In addition, the exposure and energy absorption buildup factors of reinforced Cu/Zn composites were calculated, and relative dose distribution values were computed to verify them. Proton mass stopping power (ΨP), proton projected range (ΦP), alpha mass stopping power (ΨA), and alpha projected range (ΦA) parameters, which indicate the interactions of the produced composites with charged particle radiation, were investigated. Fast neutron removal cross-section (ΣR) results were determined to give an idea in terms of neutron shielding. According to the obtained results, it is reported that the CuZn20 coded sample’s ability to attenuate gamma-ray and charged particle radiation is more efficient than that of other prepared composites. A CuZn05 coded sample was found to be more suitable for neutron shielding capability. Full article
(This article belongs to the Section Polymer Composites and Nanocomposites)
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21 pages, 1059 KiB  
Article
Optimal Electric Bus Scheduling Based on the Combination of All-Stop and Short-Turning Strategies
by Yiming Bie, Mingjie Hao and Mengzhu Guo
Sustainability 2021, 13(4), 1827; https://doi.org/10.3390/su13041827 - 8 Feb 2021
Cited by 39 | Viewed by 4351
Abstract
The emission of greenhouse gases from public transportation has aroused extensive public attention in recent years. Electric buses have the advantage of zero emission, which could prevent the further deterioration of environmental problems. Since 2018, the number of electric buses has exceeded that [...] Read more.
The emission of greenhouse gases from public transportation has aroused extensive public attention in recent years. Electric buses have the advantage of zero emission, which could prevent the further deterioration of environmental problems. Since 2018, the number of electric buses has exceeded that of traditional buses. Thus, it is an inevitable trend for the sustainable development of the automobile industry to replace traditional fuel buses, and developing electric buses is an important measure to relieve traffic congestion. Furthermore, the bus scheduling has a significant impact on passenger travel times and operating costs. It is common that passenger demand at different stops is uneven in a public transportation system. Since applying all-stop scheduling only cannot match the passenger demand of some stops with bus resources, this paper proposes an integrated all-stop and short-turning service for electric buses, reducing the influence of uneven ridership on load factor to enhance transit attractiveness. Simultaneously, considering the time-of-use pricing strategy used by the power sector, the combinational charging strategy of daytime and overnight is proposed to reduce electricity costs. Finally, the branch-and-price algorithm is adopted to solve this problem. Compared with all-stop scheduling, the results demonstrate a reduction of 13.5% in total time cost under the combinational scheduling. Full article
(This article belongs to the Special Issue Modeling Activity-Travel Behavior for Sustainable Transportation)
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20 pages, 5790 KiB  
Article
Optimizing Wireless Charging Locations for Battery Electric Bus Transit with a Genetic Algorithm
by Gang Chen, Dawei Hu, Steven Chien, Lei Guo and Mingzheng Liu
Sustainability 2020, 12(21), 8971; https://doi.org/10.3390/su12218971 - 29 Oct 2020
Cited by 25 | Viewed by 3517
Abstract
Electrifying bus transit has been deemed as an effective way to reduce the emissions of transit vehicles. However, some concerns about on-board battery hinder its further development. Recently, dynamic wireless power transfer (DWPT) technologies have been developed, which enable buses to charge in-motion [...] Read more.
Electrifying bus transit has been deemed as an effective way to reduce the emissions of transit vehicles. However, some concerns about on-board battery hinder its further development. Recently, dynamic wireless power transfer (DWPT) technologies have been developed, which enable buses to charge in-motion and overcome the drawback (short service range) with opportunity charging. This paper proposes a mathematic model which optimizes the locations for DWPT devices deployed at stops and size of battery capacity for battery electric buses (BEB) in a multi-route network, which considers the battery’s service life, depth of discharge and weight. A tangible solution algorithm based on a genetic algorithm (GA) is developed to find the optimal solution. A case study based on the bus network from Xi’an China is conducted to investigate the relationship among optimized costs, greenhouse gas (GHG) emissions, battery service life, size of the battery capacity and the number of DWPT devices. The results demonstrated that a bus network powered by DWPT shows better performance in both costs (a 43.3% reduction) and emissions (a 14.4% reduction) compared to that with stationary charging at bus terminals. Full article
(This article belongs to the Section Sustainable Transportation)
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17 pages, 3369 KiB  
Article
Estimation of the Energy Consumption of Battery Electric Buses for Public Transport Networks Using Real-World Data and Deep Learning
by Teresa Pamuła and Wiesław Pamuła
Energies 2020, 13(9), 2340; https://doi.org/10.3390/en13092340 - 8 May 2020
Cited by 95 | Viewed by 7289
Abstract
The estimation of energy consumption is an important prerequisite for planning the required infrastructure for charging and optimising the schedules of battery electric buses used in public urban transport. This paper proposes a model using a reduced number of readily acquired bus trip [...] Read more.
The estimation of energy consumption is an important prerequisite for planning the required infrastructure for charging and optimising the schedules of battery electric buses used in public urban transport. This paper proposes a model using a reduced number of readily acquired bus trip parameters: arrival times at the bus stops, map positions of the bus stops and a parameter indicating the trip conditions. A deep learning network is developed for deriving the estimates of energy consumption stop by stop of bus lines. Deep learning networks belong to the important group of methods capable of the analysis of large datasets—“big data”. This property allows for the scaling of the method and application to different sized transport networks. Validation of the network is done using real-world data provided by bus authorities of the town of Jaworzno in Poland. The estimates of energy consumption are compared with the results obtained using a regression model that is based on the collected data. Estimation errors do not exceed 7.1% for the set of several thousand bus trips. The study results indicate spots in the public transport network of potential power deficiency which can be alleviated by introducing a charging station or correcting the bus trip schedules. Full article
(This article belongs to the Section E: Electric Vehicles)
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