Green Energy and Intelligent Transportation最新文献

{"title":"When LoRa meets distributed machine learning to optimize the network connectivity for green and intelligent transportation system","authors":"Malak Abid Ali Khan ,&nbsp;Hongbin Ma ,&nbsp;Arshad Farhad ,&nbsp;Asad Mujeeb ,&nbsp;Imran Khan Mirani ,&nbsp;Muhammad Hamza","doi":"10.1016/j.geits.2024.100204","DOIUrl":"https://doi.org/10.1016/j.geits.2024.100204","url":null,"abstract":"<div><p>LoRa technology contributes to green energy by enabling efficient, long-range communication for the Internet of Things (IoT). This paper addresses the challenges related to coverage range in outdoor monitoring systems utilizing LoRa, where the network performance is affected by the density of gateways (GWs) and end devices (EDs), as well as environmental conditions. To mitigate interference, data throughput losses, and high-power consumption, the proposed spreading factor (SF) and hybrid (data rate|SF) models dynamically adjust the transmission parameters. The orchestration of concurrent data modifications within the network server (NS) is crucial for uninterrupted communication between GWs and EDs, especially in monitoring electric vehicle (EV) stations to reduce traffic congestion and pollution. Employing K-means and density-based spatial clustering of applications with noise (DBSCAN) algorithms optimizes ED allocation, averts data congestion, and improves the signal-to-interference noise ratio (SINR). These methods ensure seamless information reception by meticulously allocated EDs across various GW combinations. To estimate the free-space losses (FSL), a log-distance path loss model (log-PL) is used. Exploring various bandwidths (BWs), bidirectional communications, and duty cycles (DCs) helps to prevent saturation, thus prolonging the operational lifespan of EDs. Empirical findings reveal a notable packet rejection rate (PRR) of 0% for the DBSCAN (hybrid model). In contrast, the K-means exhibits a PRR ranging from 5% (hybrid model) to 35.29% (SF model) for the ten GWs combination. Notably, the network saturation is reduced to 10.185% and 9.503%, respectively, highlighting an improvement in the average efficiency of slotted ALOHA (91.1%) and pure ALOHA (90.7%). These enhancements increase the lifespan of EDs to 15,465.27 days.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"3 3","pages":"Article 100204"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153724000562/pdfft?md5=6f1cedcafc15a78f311218be820d0515&pid=1-s2.0-S2773153724000562-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141422682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Annotated survey and perspectives on rail transport energy system RAMS evaluation technology","authors":"Ruifeng Shi ,&nbsp;Lingzhi Zhang ,&nbsp;Feng Lin ,&nbsp;Jin Ning ,&nbsp;Limin Jia ,&nbsp;Kwang Y. Lee","doi":"10.1016/j.geits.2024.100164","DOIUrl":"10.1016/j.geits.2024.100164","url":null,"abstract":"<div><p>The rail transit system plays a crucial role in modern transportation. With the increasing demand for clean and green energy in the transport sector, its energy system is expected to achieve low-carbon and highly efficient energy utilization in rail transit. However, the gradual development of the rail transport energy system has led to an increase in its complexity, and the rising difficulty of system assessment has faced the limitations of traditional assessment methods. Hence, it is essential to develop effective assessment methods. This paper begins by providing a systematic review of the development status of Reliability, Availability, Maintainability and Safety (RAMS) assessment and analyzing the shortcomings of traditional RAMS assessment technology in the context of rail transit energy systems. Subsequently, based on the four fundamental properties of RAMS, it summarizes the current state of key assessment technologies in the field of rail transit. Moreover, the paper delves into the challenges and potential solutions concerning the implementation of RAMS assessment technology for rail transit energy systems. Finally, the paper offers an outlook on the future development of RAMS assessment for rail transport energy systems. By comprehensively analyzing these aspects, the paper aims to contribute valuable insights into optimizing the rail transit energy system, promoting its sustainable and efficient operation in the context of clean and green energy utilization.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"3 3","pages":"Article 100164"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153724000161/pdfft?md5=ff189dbab44ff188118f4e3b0aae26db&pid=1-s2.0-S2773153724000161-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139454852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fault detection of new and aged lithium-ion battery cells in electric vehicles","authors":"Sara Sepasiahooyi ,&nbsp;Farzaneh Abdollahi","doi":"10.1016/j.geits.2024.100165","DOIUrl":"10.1016/j.geits.2024.100165","url":null,"abstract":"<div><p>In this paper, a novel model-based fault detection in the battery management system of an electric vehicle is proposed. Two adaptive observers are designed to detect state-of-charge faults and voltage sensor faults, considering the impact of battery aging. Battery aging primarily affects capacity and resistance, becoming more pronounced in the later stages of a battery lifespan. By incorporating aging effects into our fault diagnosis scheme, our proposed approach prevents false or missed alarms for the aged battery cells. The aging effect of battery, capacity fading and resistance growth, are considered unknown parameters. An adaptive observer is employed to design a fault detector, considering unknown parameters in the battery model. The adaptive observers are designed for two different scenarios: In the first scenario, it is presumed that aging effects remain constant over time due to their slow rate of change. Then, it is assumed that aging effects are time-varying. Therefore, the fault detection scheme can detect faults of new battery cells as well as aged cells. Some simulations have been conducted on a Lithium-ion battery cell and extended to battery pack, to demonstrate the performance of the proposed approach in more real-world scenarios. The results showed that the designed observers can detect faults correctly in a seven years old battery as well as a new one.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"3 3","pages":"Article 100165"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153724000173/pdfft?md5=2457a5d15917c4653e8c47b7a2af194b&pid=1-s2.0-S2773153724000173-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139539634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Receding horizon based collision avoidance for UAM aircraft at intersections","authors":"Negasa Yahi,&nbsp;Jose Matute,&nbsp;Ali Karimoddini","doi":"10.1016/j.geits.2024.100205","DOIUrl":"10.1016/j.geits.2024.100205","url":null,"abstract":"<div><div>Urban Air Mobility (UAM) is an emerging aviation sector which the goal is to transform air transportation with safe, on-demand air travel for both passengers and cargo. UAM flight planning strategically separates flows of aircraft on intersecting routes vertically by allocating distinct flight levels to them, and aircraft are required to maintain the flight level when crossing the intersection. However, there is a possibility that an aircraft may fail to maintain the assigned flight level, leading to a potential conflict at intersections. This paper aims to address conflicts at intersections in the context of UAM, focusing on decentralized conflict detection and resolution. A novel approach is developed to facilitate information exchange among UAM components, including the provider of services to UAM, UAM operators, and the pilot in command. A receding horizon trajectory planning approach is proposed for the execution of conflict resolution, optimizing trajectory planning by eliminating potential problems and challenges associated with geometric approaches. The proposed trajectory planner considers the model and constraints of UAM aircraft, offering optimal solutions for safe separation at UAM airspace intersections. The significance of the proposed planning framework is demonstrated through simulations considering conflict at intersections by communicating the UAM components through request and replay services and generating resolution maneuvers on-the-fly for each aircraft involved in the conflict.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"3 6","pages":"Article 100205"},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141136836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Overall eVTOL aircraft design for urban air mobility","authors":"Jiechao Zhang,&nbsp;Yaolong Liu,&nbsp;Yao Zheng","doi":"10.1016/j.geits.2024.100150","DOIUrl":"10.1016/j.geits.2024.100150","url":null,"abstract":"<div><p>Electric vertical takeoff and landing (eVTOL) aircraft have emerged as a potential alternative to the existing transportation system, offering a transition from two-dimensional commuting and logistics to three-dimensional mobility. As a groundbreaking innovation in both the automotive and aviation sectors, eVTOL holds significant promise but also presents notable challenges. This paper aims to address the overall aircraft design (OAD) approach specifically tailored for eVTOL in the context of Urban Air Mobility (UAM). In contrast to traditional OAD methods, this study introduces and integrates disciplinary methodologies specifically catered to eVTOL aircraft design. A case study is conducted on a tilt-duct eVTOL aircraft with a typical UAM mission, and the disciplinary performance, including initial sizing, aerodynamics, electric propulsion systems, stability and control, weight, mission analysis and noise, is examined using the OAD methodologies. The findings demonstrate that the current approach effectively evaluates the fundamental aircraft-level performance of eVTOL, albeit further high-fidelity disciplinary analysis and optimization methods are required for future MDO-based eVTOL overall aircraft design.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"3 2","pages":"Article 100150"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153724000021/pdfft?md5=34eda0b9ee4b3c073328ee184fd1864e&pid=1-s2.0-S2773153724000021-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139455849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal-restricted A∗ algorithm as a support for lane-free traffic at intersections with mixed flows","authors":"Haifei Chi ,&nbsp;Pinlong Cai ,&nbsp;Daocheng Fu ,&nbsp;Junda Zhai ,&nbsp;Yadan Zeng ,&nbsp;Botian Shi","doi":"10.1016/j.geits.2024.100159","DOIUrl":"10.1016/j.geits.2024.100159","url":null,"abstract":"<div><p>Improving the capacity of intersections is the key to enhancing road traffic systems. Benefiting from the application of Connected Automated Vehicles (CAVs) in the foreseeing future, it is promising to fully utilize spatiotemporal resources at intersections through cooperative and intelligent trajectory planning for CAVs. Lane-free traffic is currently a highly anticipated solution that can achieve more flexible trajectories without being limited by lane boundaries. However, it is challenging to apply efficient lane-free traffic to be compatible with the traditional intersection control mode for mixed flow composed of CAVs and Human-driving Vehicles (HVs). To address the research gap, this paper proposes a spatiotemporal-restricted A∗ algorithm to obtain efficient and flexible lane-free trajectories for CAVs. First, we restrict the feasible area of the heuristic search algorithm by considering the feasible area and orientation of vehicles to maintain the trajectory directionality of different turning behaviors. Second, we propose a spatiotemporal sparse sampling method by defining the four-dimensional spatiotemporal grid to accelerate the execution of the heuristic search algorithm. Third, we consider the motions of HVs as dynamic obstacles with rational trajectory fluctuation during the process of trajectory planning for CAVs. The proposed method can retain the advantage of efficiently exploring feasible trajectories through the hybrid A∗ algorithm, while also utilizing multiple spatiotemporal constraints to accelerate solution efficiency. The experimental results of the simulated and real scenarios with mixed flows show that the proposed model can continuously enhance traffic efficiency and fuel economy as the penetration of CAVs gradually increases.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"3 2","pages":"Article 100159"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153724000112/pdfft?md5=2c8f0d5905097a25e192b5b1df224d57&pid=1-s2.0-S2773153724000112-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139456100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A reinforcement learning approach to vehicle coordination for structured advanced air mobility","authors":"Sabrullah Deniz,&nbsp;Yufei Wu,&nbsp;Yang Shi,&nbsp;Zhenbo Wang","doi":"10.1016/j.geits.2024.100157","DOIUrl":"10.1016/j.geits.2024.100157","url":null,"abstract":"<div><p>Advanced Air Mobility (AAM) has emerged as a pioneering concept designed to optimize the efficacy and ecological sustainability of air transportation. Its core objective is to provide highly automated air transportation services for passengers or cargo, operating at low altitudes within urban, suburban, and rural regions. AAM seeks to enhance the efficiency and environmental viability of the aviation sector by revolutionizing the way air travel is conducted. In a complex aviation environment, traffic management and control are essential technologies for safe and effective AAM operations. One of the most difficult obstacles in the envisioned AAM systems is vehicle coordination at merging points and intersections. The escalating demand for air mobility services, particularly within urban areas, poses significant complexities to the execution of such missions. In this study, we propose a novel multi-agent reinforcement learning (MARL) approach to efficiently manage high-density AAM operations in structured airspace. Our approach provides effective guidance to AAM vehicles, ensuring conflict avoidance, mitigating traffic congestion, reducing travel time, and maintaining safe separation. Specifically, intelligent learning-based algorithms are developed to provide speed guidance for each AAM vehicle, ensuring secure merging into air corridors and safe passage through intersections. To validate the effectiveness of our proposed model, we conduct training and evaluation using BlueSky, an open-source air traffic control simulation environment. Through the simulation of thousands of aircraft and the integration of real-world data, our study demonstrates the promising potential of MARL in enabling safe and efficient AAM operations. The simulation results validate the efficacy of our approach and its ability to achieve the desired outcomes.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"3 2","pages":"Article 100157"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773153724000094/pdfft?md5=ca43f6257641dbaba04d1fd52c0b85ec&pid=1-s2.0-S2773153724000094-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139634766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"State estimation of lithium-ion battery for shipboard applications: Key challenges and future trends","authors":"Laiqiang Kong,&nbsp;Yingbing Luo,&nbsp;Sidun Fang,&nbsp;Tao Niu,&nbsp;Guanhong Chen,&nbsp;Lijun Yang,&nbsp;Ruijin Liao","doi":"10.1016/j.geits.2024.100192","DOIUrl":"10.1016/j.geits.2024.100192","url":null,"abstract":"<div><div>With the aggravation of environmental problems caused by the long-term dependence of shipping traffic on heavy fossil fuels, it is an irreversible development trend for electrified ships to integrate large-capacity battery energy storage systems (ESSs). As the main component, the shipboard lithium-ion battery (LIB) plays an important role in the operation of ship power system to balance the source and load sides. By analyzing the effects of temperature, vibration, humidity and salt spray on battery characteristics in the shipping environment, this paper points out that the characteristics of shipboard LIB have certain differences on the state changes with the land-based batteries. Then, this paper systematically reviews the most commonly used LIB modeling and state estimation methods and their applicability to the shipping environment, including the empirical models, electrochemical models, equivalent circuit models (ECMs) and data-driven models. On this basis, the state estimation methods of state of charge (SOC), state of power (SOP), state of health (SOH), state of energy (SOE) and state of temperature (SOT) are reviewed. Finally, the challenges and prospects of shipboard LIB research are prospected, in the hope of providing inspiration for the development and design of efficient and safe electric ships.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 3","pages":"Article 100192"},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140269439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A critical review of compensation converters for capacitive power transfer in wireless electric vehicle charging circuit topologies","authors":"Mohammad Amir ,&nbsp;Izhar Ahmad Saifi ,&nbsp;Mohammad Waseem ,&nbsp;Mohd Tariq","doi":"10.1016/j.geits.2024.100196","DOIUrl":"10.1016/j.geits.2024.100196","url":null,"abstract":"<div><div>The compensation circuit plays a crucial role in the framework of Capacitive Power Transfer (CPT) in wireless Electric Vehicle (EV) charging schemes. Various wireless charging factors such as power transfer capacity, efficiency, and frequency depend on the design of compensation circuit topology. In CPT, power is transferred between the two capacitor plates (one transmitter plate embedded on the track and the other plate which is inserted in the wireless EV chassis operates as a receiver). The transmitter plate is excited by a high frequency source and power is transferred between the plates through an electric field. This review paper introduced an experimental prototype of the Corbin Sparrow (CS), featuring an onboard battery charger and an off-board DC charging port. Additionally, it presented a novel conformal bumper-based approach, highlighting its distinct advantages compared to alternative charging methods. The major challenges to employing capacitive technology in transferring power up to kW level are-the greater air gap between the capacitor of vehicle chassis &amp; ground and the high value of electric field strength in the contour of plates. Also, due to the low value of coupling capacitance, there is the requirement for suitable gain and compensated network which is a major area of concern. This review paper proposed various designs of compensation circuit topologies to achieve the effectiveness of the CPT scheme for Wireless Power Transfer (WPT) systems.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 2","pages":"Article 100196"},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140270580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A strong robust state-of-charge estimation method based on the gas-liquid dynamics model","authors":"Biao Chen ,&nbsp;Liang Song ,&nbsp;Haobin Jiang ,&nbsp;Zhiguo Zhao ,&nbsp;Jun Zhu ,&nbsp;Keqiang Xu","doi":"10.1016/j.geits.2024.100193","DOIUrl":"10.1016/j.geits.2024.100193","url":null,"abstract":"<div><div>Model-based strategies for estimating the state-of-charge (SOC) of Li-ion batteries are essential in real-time applications, such as electric vehicles and large-scale energy storage. However, based on existing models, developing estimation methods with strong robustness to initial and cumulative errors, high SOC estimation accuracy, and adaptability to sparse data remains challenging. Herein, the modeling principles of the gas-liquid dynamics model are systematically clarified, and a SOC estimation method based on this model and a dual extended Kalman filter with a watchdog function is proposed. The proposed method is comprehensively compared with general extended Kalman filter and dual extended Kalman filter methods under five working conditions. The results indicate that all three methods based on the gas-liquid dynamics model have good estimation accuracy, with a maximum SOC error of 0.016 under correct initial conditions. But the proposed method has significant advantages in robustness to large initial errors, cumulative errors, and sparse data. This study provides new insights into efficient online SOC estimation.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 3","pages":"Article 100193"},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140278044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}