Green Energy and Intelligent Transportation最新文献_第2页

A comparative review of user acceptance factors for drones and sidewalk robots in autonomous last mile delivery 无人机和人行道机器人在自主最后一英里配送中的用户接受度比较分析

Green Energy and Intelligent Transportation Pub Date : 2025-04-12 DOI: 10.1016/j.geits.2025.100310

Didem Cicek , Burak Kantarci , Sandra Schillo

引用次数: 0

Optical communication based V2V for vehicle platooning 基于光通信的V2V车辆队列

Green Energy and Intelligent Transportation Pub Date : 2025-04-10 DOI: 10.1016/j.geits.2025.100278

Jiajun Zhang , Ran Zhan , Yuhao Wang , Xiaobo Qu

{"title":"Optical communication based V2V for vehicle platooning","authors":"Jiajun Zhang , Ran Zhan , Yuhao Wang , Xiaobo Qu","doi":"10.1016/j.geits.2025.100278","DOIUrl":"10.1016/j.geits.2025.100278","url":null,"abstract":"<div><div>Vehicle platooning offers significant advantages, including improved fuel economy, reduced congestion and collisions, and decreased air resistance, owing to synchronized acceleration and braking within the platoon. In a vehicle platoon, vehicle-to-vehicle (V2V) communication plays a pivotal role in facilitating information transmission between leading vehicle (L+V) and following vehicle (FV). However, existing V2V communication solutions, such as Dedicated Short-Range Communications (DSRC), Cellular Vehicle-to-Everything (C–V2X), and Visible Light Communication (VLC), face limitations, including high costs, infrastructural and network demands, and privacy concerns. To overcome these challenges, our research introduces a novel vision-based, network-independent information transmission approach. This method can be used as a complement to traditional V2V methods, especially under poor network conditions or potential attacks from adversaries. Simulations and experiments reveal that our approach can facilitate vehicle-to-vehicle information transmission even when network conditions are completely absent, thereby enhancing driving safety. This is achieved through the use of an LED matrix embedded in the leading vehicle′s taillight for communication. This innovative approach holds promise as a solution to the challenges associated with conventional V2V communication methods.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 4","pages":"Article 100278"},"PeriodicalIF":0.0,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472397","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}

引用次数: 0

Cybersecurity in Smart Railways: Exploring risks, vulnerabilities and mitigation in the data communication services 智能铁路中的网络安全：探索数据通信服务中的风险、漏洞和缓解措施

Green Energy and Intelligent Transportation Pub Date : 2025-04-02 DOI: 10.1016/j.geits.2025.100305

Tiago Fernandes , João Paulo Magalhães , Wellington Alves

{"title":"Cybersecurity in Smart Railways: Exploring risks, vulnerabilities and mitigation in the data communication services","authors":"Tiago Fernandes , João Paulo Magalhães , Wellington Alves","doi":"10.1016/j.geits.2025.100305","DOIUrl":"10.1016/j.geits.2025.100305","url":null,"abstract":"<div><div>Smart trains and railways are gaining increasing significance in major global cities as they offer solutions to issues like traffic congestion and environmental pollution. Technological advancements have facilitated the transition from conventional systems to more advanced, highly efficient, and personalized railway systems. However, the complexity of these systems presents challenges, especially in terms of reliability, interoperability security, and privacy. With the potential vulnerability of railway systems to cyberattacks, it becomes crucial for these emerging smart systems to establish stringent privacy and security requirements. Cybersecurity is a key requirement to enable railways to deploy and take advantage of the full extent of a connected, digital environment. This research explores the cybersecurity landscape within Smart Railways aiming to identify potential threats and associated risks on these systems, focusing on analyzing the current literature related to Smart Railways and cybersecurity aspects, then listing key technologies used by smart systems, and finally proposing an illustration of use cases application to call attention to the impact of attacks, providing then as a set of good practices that must be followed to reduce risks and to the safeguard the operability for Rail Transportation. The research findings suggest that over the last few years, there has been a significant increase in research activity in this area, indicating a growing recognition of the importance of cybersecurity in the railway industry. The results also pointed out several gaps related to this topic, namely the lack of standardization in cybersecurity practices and limited consideration of human factors that can impact cybersecurity.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 4","pages":"Article 100305"},"PeriodicalIF":0.0,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948849","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}

引用次数: 0

A physics-informed neural network-based method for predicting degradation trajectories and remaining useful life of supercapacitors 一种基于物理信息神经网络的超级电容器退化轨迹和剩余使用寿命预测方法

Green Energy and Intelligent Transportation Pub Date : 2025-03-26 DOI: 10.1016/j.geits.2025.100291

Lixin E , Jun Wang , Ruixin Yang , Chenxu Wang , Hailong Li , Rui Xiong

{"title":"A physics-informed neural network-based method for predicting degradation trajectories and remaining useful life of supercapacitors","authors":"Lixin E , Jun Wang , Ruixin Yang , Chenxu Wang , Hailong Li , Rui Xiong","doi":"10.1016/j.geits.2025.100291","DOIUrl":"10.1016/j.geits.2025.100291","url":null,"abstract":"<div><div>Supercapacitors are widely used in transportation and renewable energy fields due to their high power density, stable cycling performance, and rapid charge–discharge capabilities. To ensure efficient applications of supercapacitors, accurately predicting their degradation trajectories and remaining useful life (RUL) is crucial. For this purpose, a physics-informed neural network (PINN) model is developed using Long Short-Term Memory (LSTM) as the base architecture. Physical equations are embedded into the loss function to ensure consistency with domain knowledge, allowing the loss function to incorporate both physical and data-driven components. The balance between these two loss components is dynamically determined through Bayesian optimization, to enhance the model's accuracy further. Validation results show a root mean square error (RMSE) of 3 mF (the rated capacity is 1 F) in the degradation trajectory prediction and a RMSE of 269 cycles (the average cycle life is 5180 cycles) for the RUL. Ablation experiments were conducted to validate the effectiveness of integrating physical information into the LSTM framework. Results demonstrate that the proposed model outperforms both the data-driven LSTM method and the empirical equation-based method that the PINN model can reduce the RMSE by 85% and 87.5% for degradation trajectory prediction, and 86.5% and 94.6% for RUL prediction, respectively. In addition, a comparison with advanced models demonstrates that our model reduces the requirement significantly on training data while maintaining comparable prediction accuracy, which favors scenarios where data is scarce.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 3","pages":"Article 100291"},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852097","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}

引用次数: 0

Multi-objective electric vehicle charge scheduling for photovoltaic and battery energy storage based electric vehicle charging stations in distribution network 基于光伏和电池储能的配电网电动汽车充电站多目标充电调度

Green Energy and Intelligent Transportation Pub Date : 2025-03-26 DOI: 10.1016/j.geits.2025.100296

Sigma Ray , Kumari Kasturi , Manas Ranjan Nayak

{"title":"Multi-objective electric vehicle charge scheduling for photovoltaic and battery energy storage based electric vehicle charging stations in distribution network","authors":"Sigma Ray , Kumari Kasturi , Manas Ranjan Nayak","doi":"10.1016/j.geits.2025.100296","DOIUrl":"10.1016/j.geits.2025.100296","url":null,"abstract":"<div><div>Recently, with the increasing demand of the electric vehicle (EV) in transportation, the power grid faces critical challenges in meeting the extra power demand. Companies are focusing on expanding EV charging infrastructure to meet customer requirements. Ensuring power supply security, reliability, and economics for EV charging stations remains a challenge, despite efforts to align photovoltaic (PV) and battery energy storage system (BESS) based designs with distribution system requirements. A criteria weight ranking mechanism has been designed to accept charging requests for EVs depending on the criteria weights specified by the EV owner. This paper uses a multi-objective remora optimization algorithm (MOROA) to determine the optimal location of two electric vehicle charging stations (EVCS) in the distribution system, and capacity of PV & BESS units in two EVCS for optimizing three conflicting objective functions, such as (1) minimizing total power loss; (2) minimizing annual substation power cost, and annual capital, operation & maintenance cost of the PV and BESS, and (3) minimizing emission from upstream grid. Moreover, the EVs are also scheduled optimally at each charging station. The effectiveness of these methodologies has been demonstrated through four case studies using IEEE 33 bus radial distribution system (RDS). Furthermore, the smart EV charge scheduling reduces the overall load burden on the grid network and the benefit of EVCS operators and EV owners.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 4","pages":"Article 100296"},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134654","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}

引用次数: 0

Industry-oriented roadmap for lithium plating detection from short to long term 行业导向的镀锂检测路线图，从短期到长期

IF 16.4

Green Energy and Intelligent Transportation Pub Date : 2025-03-26 DOI: 10.1016/j.geits.2025.100290

Yu Tian, Cheng Lin, Rui Xiong

引用次数: 0

Unveiling the explosion potential of lithium-ion batteries: A quantitative approach to safety assessment 揭示锂离子电池的爆炸潜力：一种定量的安全评估方法

IF 16.4

Green Energy and Intelligent Transportation Pub Date : 2025-03-18 DOI: 10.1016/j.geits.2025.100289

Zhenpo Wang , Tongxin Shan , Shanyu Zhao , Wim J. Malfait

{"title":"Unveiling the explosion potential of lithium-ion batteries: A quantitative approach to safety assessment","authors":"Zhenpo Wang , Tongxin Shan , Shanyu Zhao , Wim J. Malfait","doi":"10.1016/j.geits.2025.100289","DOIUrl":"10.1016/j.geits.2025.100289","url":null,"abstract":"<div><div>The safety of lithium-ion batteries is a critical and challenging focus of current research. This perspective article systematically summarized and compared evaluation methods for the trinitrotoluene-equivalent (TNT-equivalent) of lithium-ion batteries (LIBs) based on various characteristic parameters and proposed a mechanism-driven calculation approach. Using experimental data for validation, the study input TNT-equivalent values derived from different methods into an explosion dynamics model to predict explosion pressures, identifying the optimal calculation method through comparison with measured data. Results showed that the mechanism-driven approach accurately predicts explosion characteristics at different SOCs, with errors below 3%. This method eliminates the need for complex dynamic testing while providing precise predictions by linking the explosion equivalent to intrinsic thermal runaway (TR) mechanisms. The findings contribute to building safety analysis databases, establishing testing standards, and supporting the safety design of battery systems.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 5","pages":"Article 100289"},"PeriodicalIF":16.4,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144917574","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}

引用次数: 0

Evaluating electric vehicle and emission standards improvement in a Latin American city 评估拉丁美洲城市的电动汽车和排放标准改善情况

IF 16.4

Green Energy and Intelligent Transportation Pub Date : 2025-03-08 DOI: 10.1016/j.geits.2025.100284

David A. Serrato , Juan E. Tibaquirá , Juan C. López , Juan C. Castillo , Michael Giraldo , Luis F. Quirama

{"title":"Evaluating electric vehicle and emission standards improvement in a Latin American city","authors":"David A. Serrato , Juan E. Tibaquirá , Juan C. López , Juan C. Castillo , Michael Giraldo , Luis F. Quirama","doi":"10.1016/j.geits.2025.100284","DOIUrl":"10.1016/j.geits.2025.100284","url":null,"abstract":"<div><div>Electric vehicles (EVs) are considered a solution for reducing the environmental and public health impacts of light-duty vehicles and decarbonizing the transportation sector. However, their adoption in low- and middle-income countries is limited due to reliance on international models that may not account for local conditions. This study presents a comprehensive methodology for evaluating the integration of EVs into Bogotá, Colombia's vehicle fleet, and uniquely applies European emission standards, highlighting the potential to improve air quality in Latin American urban centers. It examines energy demand, greenhouse gas emissions, air pollutants, and the associated environmental, health, and infrastructure costs. The analysis covers three scenarios over 30 years. Results indicate that promoting EV adoption is more effective in reducing energy consumption and CO<sub>2</sub> emissions compared to the broad deployment of electric buses. Furthermore, the scenario with the most ambitious electrification goals presented the lowest NPV, despite having the highest infrastructure investment cost.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 6","pages":"Article 100284"},"PeriodicalIF":16.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050501","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}

引用次数: 0

Big data generation platform for battery faults under real-world variances 真实方差下电池故障大数据生成平台

Green Energy and Intelligent Transportation Pub Date : 2025-02-21 DOI: 10.1016/j.geits.2025.100282

Daniel Luder , Praise Thomas John , Paul Busch , Martin Börner , Wenjiong Cao , Philipp Dechent , Elias Barbers , Stephan Bihn , Lishuo Liu , Xuning Feng , Dirk Uwe Sauer , Weihan Li

{"title":"Big data generation platform for battery faults under real-world variances","authors":"Daniel Luder , Praise Thomas John , Paul Busch , Martin Börner , Wenjiong Cao , Philipp Dechent , Elias Barbers , Stephan Bihn , Lishuo Liu , Xuning Feng , Dirk Uwe Sauer , Weihan Li","doi":"10.1016/j.geits.2025.100282","DOIUrl":"10.1016/j.geits.2025.100282","url":null,"abstract":"<div><div>There is an increasing demand for real-time data-driven fault diagnosis of lithium-ion batteries that can predict battery faults at an early stage to avoid safety issues and improve battery reliability. However, such prediction methods require large amounts of data, generally obtained through experiments or during the operation phase, resulting in substantial economic and time efforts. In this context, generating realistic battery pack data that covers all sensor values a battery management system receives, as well as including fault models, is of particular interest and can mitigate the need to perform extensive laboratory testing. This paper focuses on the systematic development of a data generation platform capable of simulating a large scale of battery packs with random battery faults and generating big data for the following battery fault diagnostics. Initially, the electrical, thermal, and aging modeling of a battery pack is performed. After this, four types of faults, namely hard short circuit, soft short circuit, abnormal internal resistance, and abnormal contact resistance, are modeled using equivalent circuit models. To generate realistic data, both cell-to-cell variations and pack-level variations are considered. Variations included are, for example, the manufacturing quality, temperatures, aging processes, road conditions, state of charge, and fault severity. By combining the battery pack models, fault models, and the different variations through Monte Carlo simulations, a large data set representing different packs with varying levels of inconsistencies is generated.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 3","pages":"Article 100282"},"PeriodicalIF":0.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143934930","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}

引用次数: 0

Optimal allocation of distributed generation units and fast electric vehicle charging stations for sustainable cities 可持续城市分布式发电机组和快速电动汽车充电站的优化配置

IF 16.4

Green Energy and Intelligent Transportation Pub Date : 2025-02-15 DOI: 10.1016/j.geits.2025.100281

Isaac Prempeh , Albert K. Awopone , Patrick N. Ayambire , Ragab A. El-Sehiemy

{"title":"Optimal allocation of distributed generation units and fast electric vehicle charging stations for sustainable cities","authors":"Isaac Prempeh , Albert K. Awopone , Patrick N. Ayambire , Ragab A. El-Sehiemy","doi":"10.1016/j.geits.2025.100281","DOIUrl":"10.1016/j.geits.2025.100281","url":null,"abstract":"<div><div>The rise of electric vehicles (EVs) in sustainable cities has fuelled interest in Distributed Generation (DG) units allocation. A well-planned and efficient charging infrastructure is required for effective e-mobility. The paper examined the single-objective frameworks of optimal simultaneous allocation of DG units and fast EV charging stations (EVCS). The applications are employed on the IEEE 69 bus network and a real part of the Ghana network in the Ashanti region. The optimization tasks are carried out by using Particle swarm optimization (PSO) and artificial bee colony (ABC) algorithms. The impact of optimal placement on the networks was analysed. The results show that with high penetration levels of DG units (up to 40%) and fast EVCS, PSO, and ABC can achieve a significant power loss reduction that reaches 68%. Furthermore, PSO outperforms ABC in relation to the voltage deviation index on both the test network and the 33 kV Ashanti region network, while still satisfying the IEC standards' 5% margins. The results indicate that PSO and ABC are viable swarm algorithms for mitigating active power loss and enhancing the voltage profile of a system through concurrent allocation.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 5","pages":"Article 100281"},"PeriodicalIF":16.4,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144925937","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}

引用次数: 0