The construction of urban transportation infrastructures on the supply side is severely limited due to the extensive development of central urban land. Therefore, optimizing the traffic structure with limited resources is particularly important. The work used the optimum capacity of the road network as one of the constraints. Multi-objective linear programming was used to establish the traffic structure model. The total travel volume, energy consumption, travel quality, and social cost were selected as the optimization objectives of the urban transportation structure. The influencing factors of infrastructure capacity (e.g., total travel demand, optimal capacity of road network, slow traffic capacity, and parking lot capacity) were selected as the constraint conditions in optimizing urban transportation structure. The objective was to develop an optimization model considering the constraints of urban infrastructure. Finally, the optimal traffic structure was compared with the actual travel structure using the actual case of Yuexiu District, Guangzhou, China. Suggestions were provided for optimization.
{"title":"A Multi-Target Urban Transportation Structure Model under the Optimal\u0000 Capacity Limitation of Road Networks","authors":"Jinwei Zhang, Jianping Gao","doi":"10.4271/13-06-01-0003","DOIUrl":"https://doi.org/10.4271/13-06-01-0003","url":null,"abstract":"The construction of urban transportation infrastructures on the supply side is\u0000 severely limited due to the extensive development of central urban land.\u0000 Therefore, optimizing the traffic structure with limited resources is\u0000 particularly important. The work used the optimum capacity of the road network\u0000 as one of the constraints. Multi-objective linear programming was used to\u0000 establish the traffic structure model. The total travel volume, energy\u0000 consumption, travel quality, and social cost were selected as the optimization\u0000 objectives of the urban transportation structure. The influencing factors of\u0000 infrastructure capacity (e.g., total travel demand, optimal capacity of road\u0000 network, slow traffic capacity, and parking lot capacity) were selected as the\u0000 constraint conditions in optimizing urban transportation structure. The\u0000 objective was to develop an optimization model considering the constraints of\u0000 urban infrastructure. Finally, the optimal traffic structure was compared with\u0000 the actual travel structure using the actual case of Yuexiu District, Guangzhou,\u0000 China. Suggestions were provided for optimization.","PeriodicalId":181105,"journal":{"name":"SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy","volume":"4 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141919968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many cities are built around rivers in the world, and the river-crossing corridors are often their traffic bottlenecks, leading to severe congestions. Changsha is a city divided into two parts by a river with eight river-crossing corridors in China. Aiming at this issue, take Changsha as an example, this study explores developing a precise traffic restriction policy on those river-crossing corridors. First, an investigation is conducted to collect traffic flow data of those corridors. It is found that those corridors generally have serious congestion at peak hours, but their congestion levels vary greatly by corridor and direction. Then, two Greenberg models are developed for the 4-lane and 6 & 8-lane corridors, respectively, to figure out their traffic flow features. Third, a precise traffic restriction policy that balances traffic flows in different corridors is proposed. It would restrict 10% of motor vehicles on those most congested corridors, and the restricted vehicles are proportionally diverted to the neighboring non-congested corridors by detour distances. Finally, based on the estimated Greenberg models, traffic speeds of those corridors after traffic restrictions are then predicted. It is found that traffic congestions in those congested corridors are greatly alleviated, and the average travel speed of all the corridors increases by 2.8 km/h at the AM peak and 4.5 km/h at the PM peak, respectively.
{"title":"Exploration of a Precise Traffic Restriction Policy on Urban\u0000 River-Crossing Corridors: A Case Study in Changsha, China","authors":"Chenhui Liu, Qiuju Luo, Xingyu Wang","doi":"10.4271/13-06-02-0010","DOIUrl":"https://doi.org/10.4271/13-06-02-0010","url":null,"abstract":"Many cities are built around rivers in the world, and the river-crossing\u0000 corridors are often their traffic bottlenecks, leading to severe congestions.\u0000 Changsha is a city divided into two parts by a river with eight river-crossing\u0000 corridors in China. Aiming at this issue, take Changsha as an example, this\u0000 study explores developing a precise traffic restriction policy on those\u0000 river-crossing corridors. First, an investigation is conducted to collect\u0000 traffic flow data of those corridors. It is found that those corridors generally\u0000 have serious congestion at peak hours, but their congestion levels vary greatly\u0000 by corridor and direction. Then, two Greenberg models are developed for the\u0000 4-lane and 6 & 8-lane corridors, respectively, to figure out their traffic\u0000 flow features. Third, a precise traffic restriction policy that balances traffic\u0000 flows in different corridors is proposed. It would restrict 10% of motor\u0000 vehicles on those most congested corridors, and the restricted vehicles are\u0000 proportionally diverted to the neighboring non-congested corridors by detour\u0000 distances. Finally, based on the estimated Greenberg models, traffic speeds of\u0000 those corridors after traffic restrictions are then predicted. It is found that\u0000 traffic congestions in those congested corridors are greatly alleviated, and the\u0000 average travel speed of all the corridors increases by 2.8 km/h at the AM peak\u0000 and 4.5 km/h at the PM peak, respectively.","PeriodicalId":181105,"journal":{"name":"SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy","volume":"54 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Moradi, M. Rezayat, Saleh Meiabadi, A. R. Fakhir, M. Shamsborhan, Giuseppe Casalino, M. Karamimoghadam
This research systematically explores the significant impact of geometrical dimensions within fused deposition modeling (FDM), with a focus on the influence of raster angle and interior fill percentage. Through meticulous experimentation and the application of response surface modeling (RSM), the influence on critical parameters such as weight, length, width at ends, width at neck, thickness, maximum load, and elongation at tensile strength is thoroughly analyzed. The study, supported by ANOVA, highlights the notable effects of raster angle and interior fill percentage, particularly on width at ends, width at neck, and thickness. During the optimization phase, specific parameters—precisely, a raster angle of 31.68 and an interior fill percentage of 27.15—are identified, resulting in an exceptional desirability score of 0.504. These insights, substantiated by robust statistical data, fill a critical gap in the understanding of 3D-printed parts, offering practical recommendations for superior mechanical performance across diverse applications.
本研究系统地探讨了熔融沉积建模（FDM）中几何尺寸的重要影响，重点是光栅角度和内部填充百分比的影响。通过细致的实验和响应面建模（RSM）的应用，深入分析了对重量、长度、两端宽度、颈部宽度、厚度、最大载荷和拉伸强度伸长率等关键参数的影响。在方差分析的支持下，研究突出了光栅角度和内部填充百分比的显著影响，尤其是对两端宽度、颈部宽度和厚度的影响。在优化阶段，确定了特定的参数--准确地说，光栅角为 31.68，内部填充率为 27.15，从而获得了 0.504 的优异可取分。这些见解得到了可靠统计数据的证实，填补了人们对 3D 打印部件认识的一个重要空白，为各种应用领域的卓越机械性能提供了切实可行的建议。
{"title":"Precision Enhancement in Tough Polylactic Acid Material Extrusion: A\u0000 Systematic Response Surface Investigation for Sustainable\u0000 Manufacturing","authors":"M. Moradi, M. Rezayat, Saleh Meiabadi, A. R. Fakhir, M. Shamsborhan, Giuseppe Casalino, M. Karamimoghadam","doi":"10.4271/13-05-03-0018","DOIUrl":"https://doi.org/10.4271/13-05-03-0018","url":null,"abstract":"This research systematically explores the significant impact of geometrical\u0000 dimensions within fused deposition modeling (FDM), with a focus on the influence\u0000 of raster angle and interior fill percentage. Through meticulous experimentation\u0000 and the application of response surface modeling (RSM), the influence on\u0000 critical parameters such as weight, length, width at ends, width at neck,\u0000 thickness, maximum load, and elongation at tensile strength is thoroughly\u0000 analyzed. The study, supported by ANOVA, highlights the notable effects of\u0000 raster angle and interior fill percentage, particularly on width at ends, width\u0000 at neck, and thickness. During the optimization phase, specific\u0000 parameters—precisely, a raster angle of 31.68 and an interior fill percentage of\u0000 27.15—are identified, resulting in an exceptional desirability score of 0.504.\u0000 These insights, substantiated by robust statistical data, fill a critical gap in\u0000 the understanding of 3D-printed parts, offering practical recommendations for\u0000 superior mechanical performance across diverse applications.","PeriodicalId":181105,"journal":{"name":"SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy","volume":"77 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141812806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Meiling Su, Ling Liu, Xiyang Chen, Rongxian Long, Chenhui Liu
To identify the influences of various built environment factors on ridership at urban rail transit stations, a case study was conducted on the Changsha Metro. First, spatial and temporal distributions of the station-level AM peak and PM peak boarding ridership are analyzed. The Moran’s I test indicates that both of them show significant spatial correlations. Then, the pedestrian catchment area of each metro station is delineated using the Thiessen polygon method with an 800-m radius. The built environment factors within each pedestrian catchment area, involving population and employment, land use, accessibility, and station attributes, are collected. Finally, the mixed geographically weighted regression models are constructed to quantitatively identify the effects of these built environment factors on the AM and PM peak ridership, respectively. The estimation results indicate that population density and employment density have significant but opposite influences on the AM and PM peak ridership, which can be attributed to the opposite travel directions of commuters in the AM and PM peak. The recreational facility density, road density, and 10-min walking accessibility could significantly positively affect the PM peak ridership, and their influences vary greatly over space. Besides, the operating time of stations significantly positively affects both the AM and PM peak ridership, transfer stations have significantly larger PM peak ridership and terminal stations have significantly larger AM peak ridership. The findings are expected to provide new insights for agencies to formulate appropriate measures to improve the ridership of urban rail transit.
为了确定各种建筑环境因素对城市轨道交通车站乘客量的影响，我们对长沙地铁进行了案例研究。首先，分析了车站早高峰和晚高峰乘车人次的时空分布。Moran's I 检验表明，两者在空间上存在显著的相关性。然后，采用 Thiessen 多边形方法，以 800 米为半径，划定了每个地铁站的行人集聚区。收集每个行人集聚区内的建筑环境因素，包括人口和就业、土地利用、可达性和车站属性。最后，建立混合地理加权回归模型，分别定量确定这些建筑环境因素对上午和下午高峰乘客量的影响。估计结果表明，人口密度和就业密度对早高峰和晚高峰乘客量的影响显著但相反，这可能是由于早高峰和晚高峰乘客的出行方向相反。娱乐设施密度、道路密度和 10 分钟步行可达性对下午高峰乘客量有显著的正向影响，且影响程度随空间变化较大。此外，车站运营时间对早高峰和晚高峰乘客量均有明显的正向影响，换乘站的晚高峰乘客量明显更大，终点站的早高峰乘客量明显更大。这些研究结果有望为相关机构提供新的启示，以制定适当的措施来提高城市轨道交通的乘客率。
{"title":"Exploration of the Impact of Built Environment Factors on Morning and\u0000 Evening Peak Ridership at Urban Rail Transit Stations: A Case Study of Changsha,\u0000 China","authors":"Meiling Su, Ling Liu, Xiyang Chen, Rongxian Long, Chenhui Liu","doi":"10.4271/13-06-02-0009","DOIUrl":"https://doi.org/10.4271/13-06-02-0009","url":null,"abstract":"To identify the influences of various built environment factors on ridership at\u0000 urban rail transit stations, a case study was conducted on the Changsha Metro.\u0000 First, spatial and temporal distributions of the station-level AM peak and PM\u0000 peak boarding ridership are analyzed. The Moran’s I test indicates that both of\u0000 them show significant spatial correlations. Then, the pedestrian catchment area\u0000 of each metro station is delineated using the Thiessen polygon method with an\u0000 800-m radius. The built environment factors within each pedestrian catchment\u0000 area, involving population and employment, land use, accessibility, and station\u0000 attributes, are collected. Finally, the mixed geographically weighted regression\u0000 models are constructed to quantitatively identify the effects of these built\u0000 environment factors on the AM and PM peak ridership, respectively. The\u0000 estimation results indicate that population density and employment density have\u0000 significant but opposite influences on the AM and PM peak ridership, which can\u0000 be attributed to the opposite travel directions of commuters in the AM and PM\u0000 peak. The recreational facility density, road density, and 10-min walking\u0000 accessibility could significantly positively affect the PM peak ridership, and\u0000 their influences vary greatly over space. Besides, the operating time of\u0000 stations significantly positively affects both the AM and PM peak ridership,\u0000 transfer stations have significantly larger PM peak ridership and terminal\u0000 stations have significantly larger AM peak ridership. The findings are expected\u0000 to provide new insights for agencies to formulate appropriate measures to\u0000 improve the ridership of urban rail transit.","PeriodicalId":181105,"journal":{"name":"SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy","volume":"3 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Supply chain management is key to industry efficiency, while information security and transparency are at the core of operations management. Blockchain technology shows great potential in this regard and can effectively make up for existing shortcomings. This article deeply explores the application of blockchain in new energy vehicle supply chain management, focusing on enhancing the systematization and collaboration of the supply chain through smart contract mechanisms. We established a collaborative contract model for the three-level supply chain. Especially from the perspective of the intermediate supply chain, we designed a smart contract mechanism to optimize key links such as order processing, payment, and logistics tracking, and used the alliance chain to ensure the safe sharing and sharing of information. At the same time, we have also developed an interactive system for each link of the supply chain and achieved smooth interaction in the new energy vehicle supply chain by adjusting the parameters and functions of smart contracts. Using the Ethereum scripting language, we built a blockchain smart contract mechanism based on supply chain contracts. This research not only demonstrates the potential value of blockchain technology in promoting supply chain information sharing and enhancing mutual trust, but also highlights its importance in supply chain management innovation and practical application.
{"title":"Efficient Smart Contract Mechanism for New Energy Vehicle Supply\u0000 Chain Based on Alliance Chain","authors":"Peng Wang","doi":"10.4271/13-06-01-0002","DOIUrl":"https://doi.org/10.4271/13-06-01-0002","url":null,"abstract":"Supply chain management is key to industry efficiency, while information security\u0000 and transparency are at the core of operations management. Blockchain technology\u0000 shows great potential in this regard and can effectively make up for existing\u0000 shortcomings. This article deeply explores the application of blockchain in new\u0000 energy vehicle supply chain management, focusing on enhancing the\u0000 systematization and collaboration of the supply chain through smart contract\u0000 mechanisms. We established a collaborative contract model for the three-level\u0000 supply chain. Especially from the perspective of the intermediate supply chain,\u0000 we designed a smart contract mechanism to optimize key links such as order\u0000 processing, payment, and logistics tracking, and used the alliance chain to\u0000 ensure the safe sharing and sharing of information. At the same time, we have\u0000 also developed an interactive system for each link of the supply chain and\u0000 achieved smooth interaction in the new energy vehicle supply chain by adjusting\u0000 the parameters and functions of smart contracts. Using the Ethereum scripting\u0000 language, we built a blockchain smart contract mechanism based on supply chain\u0000 contracts. This research not only demonstrates the potential value of blockchain\u0000 technology in promoting supply chain information sharing and enhancing mutual\u0000 trust, but also highlights its importance in supply chain management innovation\u0000 and practical application.","PeriodicalId":181105,"journal":{"name":"SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy","volume":"55 s190","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141834792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the face of the world’s population growth and ensuing demands, the industrial sector assumes a crucial role in the management of limited energy supplies. Superalloys based on nickel, which are well-known for their remarkable mechanical qualities and resilience to corrosion, are now essential in vital applications like rocket engines, gas turbines, and aviation. However, these metals’ toughness presents a number of difficulties during machining operations, especially with regard to power consumption. This abstract explores the variables that affect power consumption during the machining of superalloys based on nickel in great detail and suggests ways to improve energy efficiency in this area. The effects of important variables on power consumption are extensively investigated, including cutting speed, feed rate, depth of cut, tool geometry, and cooling/lubrication techniques. A careful balance between these factors is necessary to maximize machining efficiency and reduce power usage. Furthermore, this study reviews the effect of different heat source applications on power consumption and the resultant quality of machined nickel-based superalloys. Additionally, the critical role of cooling and lubrication in mitigating the adverse effects of high temperatures generated during machining is thoroughly examined. Innovative cooling strategies, including cryogenic or high-pressure coolant systems, are explored as potential avenues to enhance heat dissipation and minimize power requirements. In essence, this abstract not only sheds light on the challenges inherent in machining nickel-based superalloys but also offers actionable insights into how energy efficiency can be maximized through strategic parameter optimization and the adoption of innovative cooling techniques. By addressing these aspects, manufacturers can effectively navigate the complexities of machining superalloys while minimizing their environmental footprint and operational costs.
{"title":"Optimizing Power Consumption in Machining Nickel-Based Superalloys:\u0000 Strategies for Energy Efficiency","authors":"Alper Başaran, Mahmut Özer, Hakan Kazan","doi":"10.4271/13-05-03-0017","DOIUrl":"https://doi.org/10.4271/13-05-03-0017","url":null,"abstract":"In the face of the world’s population growth and ensuing demands, the industrial\u0000 sector assumes a crucial role in the management of limited energy supplies.\u0000 Superalloys based on nickel, which are well-known for their remarkable\u0000 mechanical qualities and resilience to corrosion, are now essential in vital\u0000 applications like rocket engines, gas turbines, and aviation. However, these\u0000 metals’ toughness presents a number of difficulties during machining operations,\u0000 especially with regard to power consumption. This abstract explores the\u0000 variables that affect power consumption during the machining of superalloys\u0000 based on nickel in great detail and suggests ways to improve energy efficiency\u0000 in this area. The effects of important variables on power consumption are\u0000 extensively investigated, including cutting speed, feed rate, depth of cut, tool\u0000 geometry, and cooling/lubrication techniques. A careful balance between these\u0000 factors is necessary to maximize machining efficiency and reduce power usage.\u0000 Furthermore, this study reviews the effect of different heat source applications\u0000 on power consumption and the resultant quality of machined nickel-based\u0000 superalloys. Additionally, the critical role of cooling and lubrication in\u0000 mitigating the adverse effects of high temperatures generated during machining\u0000 is thoroughly examined. Innovative cooling strategies, including cryogenic or\u0000 high-pressure coolant systems, are explored as potential avenues to enhance heat\u0000 dissipation and minimize power requirements. In essence, this abstract not only\u0000 sheds light on the challenges inherent in machining nickel-based superalloys but\u0000 also offers actionable insights into how energy efficiency can be maximized\u0000 through strategic parameter optimization and the adoption of innovative cooling\u0000 techniques. By addressing these aspects, manufacturers can effectively navigate\u0000 the complexities of machining superalloys while minimizing their environmental\u0000 footprint and operational costs.","PeriodicalId":181105,"journal":{"name":"SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy","volume":"113 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141657293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Life cycle analyses suggest that electric vehicles are more efficient than gasoline internal combustion engine vehicles (ICEVs). Although the latest available data reveal that electric vehicle (EV) life cycle operational efficiency is only 17% (3 percentage points) higher than a gasoline ICEV, overall life cycle efficiencies including manufacturing for EVs are 2 percentage points lower than for ICEVs. Greenhouse gas (GHG) emissions of EVs are only 4% lower than ICEVs, but criteria emissions of NOx and PM are approaching or exceeding two times those of gasoline ICEVs. Significant reductions in electric grid emissions are required to realize EV’s anticipated emission benefits. In contrast, hybrid electric vehicles (HEVs) have over 70% higher efficiency and 28% lower GHG emissions than today’s EVs. For heavy-duty trucks using today’s gray hydrogen, produced by steam–methane reforming, overall life cycle efficiencies of ICEs and fuel cells are 63% higher than electric powertrains using today’s electric grid, but 25% lower than diesel-fueled ICEs. GHG emissions of ICEs and fuel cells using gray hydrogen are 34% lower than electric powertrains using today’s grid, but are over 50% higher than diesel-fueled ICEs. Only 1% of today’s hydrogen is green, derived by electrolysis using renewable energy. Using green hydrogen, life cycle efficiencies of ICEs or fuel cells are 36% lower than with gray hydrogen. GHG emissions of green hydrogen-fueled ICE or fuel cell powertrains, although reduced by 69% relative to gray hydrogen, are nearly twice those of an electric powertrain using renewable electricity.
{"title":"Efficiency and Emissions of Electric and Hydrogen Light- and\u0000 Heavy-Duty Vehicles","authors":"Wallace R. Wade","doi":"10.4271/13-05-02-0015","DOIUrl":"https://doi.org/10.4271/13-05-02-0015","url":null,"abstract":"Life cycle analyses suggest that electric vehicles are more efficient than\u0000 gasoline internal combustion engine vehicles (ICEVs). Although the latest\u0000 available data reveal that electric vehicle (EV) life cycle operational\u0000 efficiency is only 17% (3 percentage points) higher than a gasoline ICEV,\u0000 overall life cycle efficiencies including manufacturing for EVs are 2 percentage\u0000 points lower than for ICEVs. Greenhouse gas (GHG) emissions of EVs are only 4%\u0000 lower than ICEVs, but criteria emissions of NOx and PM are\u0000 approaching or exceeding two times those of gasoline ICEVs. Significant\u0000 reductions in electric grid emissions are required to realize EV’s anticipated\u0000 emission benefits. In contrast, hybrid electric vehicles (HEVs) have over 70%\u0000 higher efficiency and 28% lower GHG emissions than today’s EVs. For heavy-duty\u0000 trucks using today’s gray hydrogen, produced by steam–methane\u0000 reforming, overall life cycle efficiencies of ICEs and fuel cells are 63% higher\u0000 than electric powertrains using today’s electric grid, but 25% lower than\u0000 diesel-fueled ICEs. GHG emissions of ICEs and fuel cells using\u0000 gray hydrogen are 34% lower than electric powertrains using\u0000 today’s grid, but are over 50% higher than diesel-fueled ICEs. Only 1% of\u0000 today’s hydrogen is green, derived by electrolysis using\u0000 renewable energy. Using green hydrogen, life cycle efficiencies\u0000 of ICEs or fuel cells are 36% lower than with gray hydrogen.\u0000 GHG emissions of green hydrogen-fueled ICE or fuel cell\u0000 powertrains, although reduced by 69% relative to gray hydrogen,\u0000 are nearly twice those of an electric powertrain using renewable\u0000 electricity.","PeriodicalId":181105,"journal":{"name":"SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy","volume":"111 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141352504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Deepak Kumar, Amir F. N. Abdul-Manan, Gautam Kalghatgi, A. Agarwal
The initial cost of battery electric vehicles (BEVs) is higher than internal combustion engine-powered vehicles (ICEVs) due to expensive batteries. Various factors affect the total cost of ownership of a vehicle. In India, consumers are concerned with a vehicle’s initial purchase cost and prefer owning an economical vehicle. The higher cost and shorter range of BEVs compared to ICEVs severely limit their penetration in the Indian market. However, government subsidies and incentives support BEVs. The total cost of ownership assessment is used to evaluate the entire cost of a vehicle to find the most economical option among different powertrains. This study compares 2W (two-wheeler) and 4W (four-wheeler) BEV’s cost vis-à-vis equivalent ICEVs in Delhi and Mumbai. The cost analysis assesses the current and future government policies to promote BEVs. Two assumed policies were applied to estimate future scenarios. Annual distance traveled, battery replacement assumptions, and fuel/electricity prices were used for sensitivity analyses. It was found that the total cost of ownership of 2W BEVs in Mumbai and Delhi was lower than the ICEVs, only if heavily supported by government subsidies and incentives. In contrast, with assumed future policies, owning 4W BEVs was costlier, even with government subsidies. This study showed that if a vehicle travels more than the average annual distance traveled, BEVs can be a better option and make sense for niche applications such as taxi fleet operations or ride-hailing services. The current incentives were much more for 4W than 2W, implying a disproportionate allocation of subsidies to the wealthier, who can afford 4W vehicles. The funds required for subsidies, losses in fuel taxes because of lower sales, and tax exemptions offered to BEVs could cost up to ₹146,062 crores (i.e., $19 billion) annually to the Indian government in 2030, which is ~ ₹973 per capita, excluding investments required to build charging infrastructure. Therefore, India needs a targeted subsidy allocation plan, prioritizing 2W, and a phased strategy for an orderly and inclusive transition to a sustainable mobility future. Graphical Abstract
{"title":"Economic Competitiveness of Battery Electric Vehicles vs Internal\u0000 Combustion Engine Vehicles in India: A Case Study for Two- and\u0000 Four-Wheelers","authors":"Deepak Kumar, Amir F. N. Abdul-Manan, Gautam Kalghatgi, A. Agarwal","doi":"10.4271/13-05-02-0014","DOIUrl":"https://doi.org/10.4271/13-05-02-0014","url":null,"abstract":"The initial cost of battery electric vehicles (BEVs) is higher than internal\u0000 combustion engine-powered vehicles (ICEVs) due to expensive batteries. Various\u0000 factors affect the total cost of ownership of a vehicle. In India, consumers are\u0000 concerned with a vehicle’s initial purchase cost and prefer owning an economical\u0000 vehicle. The higher cost and shorter range of BEVs compared to ICEVs severely\u0000 limit their penetration in the Indian market. However, government subsidies and\u0000 incentives support BEVs. The total cost of ownership assessment is used to\u0000 evaluate the entire cost of a vehicle to find the most economical option among\u0000 different powertrains. This study compares 2W (two-wheeler) and 4W\u0000 (four-wheeler) BEV’s cost vis-à-vis equivalent ICEVs in Delhi and Mumbai. The\u0000 cost analysis assesses the current and future government policies to promote\u0000 BEVs. Two assumed policies were applied to estimate future scenarios. Annual\u0000 distance traveled, battery replacement assumptions, and fuel/electricity prices\u0000 were used for sensitivity analyses. It was found that the total cost of\u0000 ownership of 2W BEVs in Mumbai and Delhi was lower than the ICEVs, only if\u0000 heavily supported by government subsidies and incentives. In contrast, with\u0000 assumed future policies, owning 4W BEVs was costlier, even with government\u0000 subsidies. This study showed that if a vehicle travels more than the average\u0000 annual distance traveled, BEVs can be a better option and make sense for niche\u0000 applications such as taxi fleet operations or ride-hailing services. The current\u0000 incentives were much more for 4W than 2W, implying a disproportionate allocation\u0000 of subsidies to the wealthier, who can afford 4W vehicles. The funds required\u0000 for subsidies, losses in fuel taxes because of lower sales, and tax exemptions\u0000 offered to BEVs could cost up to ₹146,062 crores (i.e., $19 billion) annually to\u0000 the Indian government in 2030, which is ~ ₹973 per capita, excluding investments\u0000 required to build charging infrastructure. Therefore, India needs a targeted\u0000 subsidy allocation plan, prioritizing 2W, and a phased strategy for an orderly\u0000 and inclusive transition to a sustainable mobility future.\u0000\u0000 \u0000\u0000 Graphical Abstract\u0000 \u0000 \u0000 \u0000","PeriodicalId":181105,"journal":{"name":"SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy","volume":"15 S9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140741226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the continuous progress of society, people have higher and higher requirements for the quality of life. Energy is an important substance base for human existence and development. In the construction industry, construction project construction period cost control has become particularly important. The existing engineering projects have not significantly optimized the quality of construction period cost, leading to waste of resources. Therefore, it is particularly important to establish an efficient, reasonable, and perfect system to ensure the scientific use of construction project construction period cost. The Internet of things (IoT) technology was applied to engineering projects to study the fuzzy balance optimization of construction period, cost and quality of engineering projects, and analyze the connotation and influencing factors of engineering quality and the construction project target system under the concept of sustainable development, and through the balance analysis of project duration cost, project duration quality, project cost quality, and environmental pollution experiment on different processes of the project, it was found that the application of the IoT technology has reduced the construction period of the project. The IoT technology makes a fuzzy balanced optimization of the construction period cost quality of the project, which can reduce the cost consumption of the project and improve the quality of the project. The application of the IoT technology has reduced the environmental pollution by 2.4%. Based on the IoT technology, the construction period cost quality of the project has been optimized. On the premise of ensuring the project quality, it can reduce the construction period, reduce costs, reduce environmental pollution, and reduce the use of energy to promote sustainable development.
{"title":"Evaluation on Fuzzy Equilibrium Optimization of Construction Project\u0000 Duration Cost Quality Based on Internet of Things Technology","authors":"Xie Feng, Pan Hu, Sibao Chen","doi":"10.4271/13-05-02-0012","DOIUrl":"https://doi.org/10.4271/13-05-02-0012","url":null,"abstract":"With the continuous progress of society, people have higher and higher\u0000 requirements for the quality of life. Energy is an important substance base for\u0000 human existence and development. In the construction industry, construction\u0000 project construction period cost control has become particularly important. The\u0000 existing engineering projects have not significantly optimized the quality of\u0000 construction period cost, leading to waste of resources. Therefore, it is\u0000 particularly important to establish an efficient, reasonable, and perfect system\u0000 to ensure the scientific use of construction project construction period cost.\u0000 The Internet of things (IoT) technology was applied to engineering projects to\u0000 study the fuzzy balance optimization of construction period, cost and quality of\u0000 engineering projects, and analyze the connotation and influencing factors of\u0000 engineering quality and the construction project target system under the concept\u0000 of sustainable development, and through the balance analysis of project duration\u0000 cost, project duration quality, project cost quality, and environmental\u0000 pollution experiment on different processes of the project, it was found that\u0000 the application of the IoT technology has reduced the construction period of the\u0000 project. The IoT technology makes a fuzzy balanced optimization of the\u0000 construction period cost quality of the project, which can reduce the cost\u0000 consumption of the project and improve the quality of the project. The\u0000 application of the IoT technology has reduced the environmental pollution by\u0000 2.4%. Based on the IoT technology, the construction period cost quality of the\u0000 project has been optimized. On the premise of ensuring the project quality, it\u0000 can reduce the construction period, reduce costs, reduce environmental\u0000 pollution, and reduce the use of energy to promote sustainable development.","PeriodicalId":181105,"journal":{"name":"SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy","volume":"115 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140381435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The global automotive industry’s shift toward electrification hinges on battery electric vehicles (BEV) having a reduced total cost of ownership compared to traditional vehicles. Although BEVs exhibit lower operational costs than internal combustion engine (ICE) vehicles, their initial acquisition expense is higher due to expensive battery packs. This study evaluates total ownership costs for four vehicle types: traditional ICE-based car, BEV, split-power hybrid, and plug-in hybrid. Unlike previous analyses comparing production vehicles, this study employs a hypothetical sedan with different powertrains for a more equitable assessment. The study uses a drive-cycle model grounded in fundamental vehicle dynamics to determine the fuel and electricity consumption for each vehicle in highway and urban conditions. These figures serve a Monte Carlo simulation, projecting a vehicle’s operating cost over a decade based on average daily distance and highway driving percentage. Results show plug-in hybrids generally offer the most economical choice. Due to the BEVs’ heavier weight and battery cost, they only become more cost-effective than plug-in hybrids after 160 km daily travel, associated with only a small percentage of drivers in the United States. Nevertheless, they remain cheaper than conventional vehicles for most distances. The study also investigates the effects of government subsidies, battery cost, and weight on overall expenses for each powertrain. It concludes that opting for less expensive, albeit heavier batteries would generally reduce EV ownership costs for consumers.
{"title":"Modeling and Comparing the Total Cost of Ownership of Passenger\u0000 Automobiles with Conventional, Electric, and Hybrid Powertrains","authors":"Vikram Mittal, Rajesh Shah","doi":"10.4271/13-05-02-0013","DOIUrl":"https://doi.org/10.4271/13-05-02-0013","url":null,"abstract":"The global automotive industry’s shift toward electrification hinges on battery\u0000 electric vehicles (BEV) having a reduced total cost of ownership compared to\u0000 traditional vehicles. Although BEVs exhibit lower operational costs than\u0000 internal combustion engine (ICE) vehicles, their initial acquisition expense is\u0000 higher due to expensive battery packs. This study evaluates total ownership\u0000 costs for four vehicle types: traditional ICE-based car, BEV, split-power\u0000 hybrid, and plug-in hybrid. Unlike previous analyses comparing production\u0000 vehicles, this study employs a hypothetical sedan with different powertrains for\u0000 a more equitable assessment. The study uses a drive-cycle model grounded in\u0000 fundamental vehicle dynamics to determine the fuel and electricity consumption\u0000 for each vehicle in highway and urban conditions. These figures serve a Monte\u0000 Carlo simulation, projecting a vehicle’s operating cost over a decade based on\u0000 average daily distance and highway driving percentage. Results show plug-in\u0000 hybrids generally offer the most economical choice. Due to the BEVs’ heavier\u0000 weight and battery cost, they only become more cost-effective than plug-in\u0000 hybrids after 160 km daily travel, associated with only a small percentage of\u0000 drivers in the United States. Nevertheless, they remain cheaper than\u0000 conventional vehicles for most distances. The study also investigates the\u0000 effects of government subsidies, battery cost, and weight on overall expenses\u0000 for each powertrain. It concludes that opting for less expensive, albeit heavier\u0000 batteries would generally reduce EV ownership costs for consumers.","PeriodicalId":181105,"journal":{"name":"SAE International Journal of Sustainable Transportation, Energy, Environment, & Policy","volume":"4 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139598583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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