Etransportation最新文献

{"title":"Trustworthy V2G scheduling and energy trading: A blockchain-based framework","authors":"Yunwang Chen ,&nbsp;Xiang Lei ,&nbsp;Songyan Niu ,&nbsp;Linni Jian","doi":"10.1016/j.etran.2024.100376","DOIUrl":"10.1016/j.etran.2024.100376","url":null,"abstract":"<div><div>The rapid growth of electric vehicles (EVs) and the deployment of vehicle-to-grid (V2G) technology pose significant challenges for distributed power grids, particularly in fostering trust and ensuring effective coordination among stakeholders. Establishing a trustworthy V2G operation environment is crucial for enabling large-scale EV user participation and realizing V2G's potential in real-world applications. In this paper, an integrated scheduling and trading framework is developed to conduct transparent and efficacious coordination in V2G operations. In blockchain implementation, a cyber-physical blockchain architecture is proposed to enhance transaction efficiency and scalability by leveraging smart charging points (SCPs) for rapid transaction validation through a fast-path practical byzantine fault tolerance (fast-path PBFT) consensus mechanism. From the energy dispatching perspective, a game-theoretical pricing strategy is employed and smart contracts are utilized for autonomous decision-making between EVs and operators, aiming to optimize the trading process and maximize economic benefits. Numerical evaluation of blockchain consensus shows the effect of the fast-path PBFT consensus in improving systems scalability with a balanced trade-off in robustness. A case study, utilizing real-world data from the Southern University of Science and Technology (SUSTech), demonstrates significant reductions in EV charging costs and the framework's potential to support auxiliary grid services.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"22 ","pages":"Article 100376"},"PeriodicalIF":15.0,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Will it get there? A deep learning model for predicting next-trip state of charge in Urban Green Freight Delivery with electric vehicles","authors":"Wenbo Lu ,&nbsp;Zheng Yuan ,&nbsp;Ting Wang ,&nbsp;Peikun Li ,&nbsp;Yong Zhang","doi":"10.1016/j.etran.2024.100372","DOIUrl":"10.1016/j.etran.2024.100372","url":null,"abstract":"<div><div>To enhance urban freight efficiency and green development, China has implemented the Urban Green Freight Delivery (UGFD) project, which includes optimizing vehicle traffic control policies and increasing the number of new energy vehicles (NEV). However, range anxiety is a significant challenge for freight drivers performing delivery tasks with electric vehicles (a major component of NEV). We constructed a prediction model for the state of charge (SOC), or battery remaining energy percentage when UGFD vehicles reach the next trip point, aiming to alleviate this issue. The model consists of three modules: (1) a vehicle SOC context prediction module, (2) a vehicle energy consumption prediction module, and (3) a multi-perspective SOC prediction value fusion module. Specifically, in the SOC context prediction module, historical SOC sequences, vehicle status (loading/unloading, charging), and time intervals between SOC points are used to accurately describe context change trends, and directly predict the vehicle SOC at the next trip point. The energy consumption prediction module combines community-level and grid-level geographical location information for the vehicle stops using weather, vehicle parameters, etc., to model the spatial dynamic correlation of energy consumption. The vehicle SOC at the next trip point is the difference between the current vehicle SOC and the predicted energy consumption. The multi-perspective SOC prediction value fusion module is a combination of the predicted values from the context and energy consumption perspectives, resulting in the final vehicle SOC prediction value. Taking Suzhou, China as an example, the results show that the mean absolute error, root mean square error, and symmetric mean absolute percentage error for the constructed model are 23.67%, 10.39%, and 20.03% less, respectively, than for the baseline models focusing on SOC short-term time series prediction. The research results can provide scientific evidence for formulating refined energy management, charging station layout, and freight delivery optimization approaches.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"22 ","pages":"Article 100372"},"PeriodicalIF":15.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Industrialization challenges for sulfide-based all solid state battery","authors":"Yujing Wu ,&nbsp;Ziqi Zhang ,&nbsp;Qinggang Zhang ,&nbsp;Zhaoshuai Zhang ,&nbsp;Jiawei Li ,&nbsp;Ming Liu ,&nbsp;Hong Li ,&nbsp;Liquan Chen ,&nbsp;Fan Wu","doi":"10.1016/j.etran.2024.100371","DOIUrl":"10.1016/j.etran.2024.100371","url":null,"abstract":"<div><div>All-solid-state battery(ASSB) is the most promising solution for next-generation energy-storage device due to its high energy density, fast charging capability, enhanced safety, wide operating temperature range and long cycle life. Although great efforts and breakthroughs have been made in recent years, many challenges still exist for its industrialization. This perspective aims to summarize the most critical challenges in mass production of ASSB to fully release its potential and facilitate the arrival of a more sustainable future.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"22 ","pages":"Article 100371"},"PeriodicalIF":15.0,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of EV fast charging in the urban context: An agent-based model approach","authors":"F. Hipolito ,&nbsp;J. Rich ,&nbsp;Peter Bach Andersen","doi":"10.1016/j.etran.2024.100369","DOIUrl":"10.1016/j.etran.2024.100369","url":null,"abstract":"<div><div>Using an agent-based simulation approach, this paper investigates the role of fast-charging infrastructure in urban environments. The simulation model tracks the spatial and temporal behaviours of electric vehicles (EVs), facilitating a comprehensive analysis of the deployment of charging infrastructure. Notably, the model incorporates non-parametric queuing dynamics, information-sharing regarding waiting times, and diverse agent characteristics, deepening insights into the subject matter. Drawing on a large-scale implementation in the municipalities of Frederiksberg and Copenhagen, the study advocates for adopting fast chargers by demonstrating several key points. Firstly, information-sharing significantly reduces waiting times, particularly within the fast-charging network, with potential reductions of up to 30% during peak demand periods. Secondly, larger fast-charging clusters comprising 10–14 outlets outperform smaller clusters, primarily due to reduced waiting times and enhanced prediction accuracy of waiting times, which is a consequence of the information-sharing. Thirdly, placement strategies based on unserved demand metrics yield superior outcomes than those solely driven by observed demand patterns. By effectively monitoring both observed and unmet demand, these strategies tend to better optimize charging infrastructure placement. These insights, which emerge from the sophisticated and heterogeneous nature of the simulation framework, highlight the value of information and unserved demand in this field.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"22 ","pages":"Article 100369"},"PeriodicalIF":15.0,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving energy efficiency for suburban railways: A two-stage scheduling optimization in a rail-EV smart hub","authors":"Yinyu Chen ,&nbsp;Minwu Chen ,&nbsp;Wenjie Lu ,&nbsp;Agustí Egea-Àlvarez ,&nbsp;Lie Xu","doi":"10.1016/j.etran.2024.100366","DOIUrl":"10.1016/j.etran.2024.100366","url":null,"abstract":"<div><div>As the scale of suburban rail and electric vehicles (EVs) continues to expand with the revolution of electrification of transportation, park and ride (P&amp;R) facilities are increasingly recognized as critical energy coupling points between suburban rail traction transformers and EV charging stations. However, flexible coordination of the energy distribution among the bidirectional power flow of multiple trains and EVs’ charging demand becomes an urgent issue. In this paper, we establish a rail-EV Smart Energy Hub (SEH) framework integrating trains, ultra-capacitors (UC), and battery-based EVs. An emendable two-stage optimization model is proposed, enabling railways to provide R2X (railway-to-anything) services. The first stage determines the optimal train trajectory and adjusts timetables to minimize the energy consumption of multiple trains. In the second stage, the charging strategy of the EV is coordinated with the charging/discharging scheme of the UC, which takes the train power flow determined in the first stage as input. Meanwhile, the voltage unbalance caused by the railway is constrained to comply with the limits set by IEC/TR 61000-3-13. Case studies based on actual suburban railway lines in China demonstrate that the proposed scheduling optimization approach can significantly reduce the energy consumption of both railways and EVs.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"22 ","pages":"Article 100366"},"PeriodicalIF":15.0,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On safety of swelled commercial lithium-ion batteries: A study on aging, swelling, and abuse tests","authors":"Yiding Li ,&nbsp;Shicong Ding ,&nbsp;Li Wang ,&nbsp;Wenwei Wang ,&nbsp;Cheng Lin ,&nbsp;Xiangming He","doi":"10.1016/j.etran.2024.100368","DOIUrl":"10.1016/j.etran.2024.100368","url":null,"abstract":"<div><div>Lithium-ion battery technology has advanced significantly, making these power sources essential for portable electronic devices such as smartphones. In 2023, global smartphone shipments reached nearly 1.2 billion units, underscoring the widespread reliance on these batteries. However, as batteries age, they may swell and potentially pose explosion risks. To investigate the safety of swollen batteries, this study conducts accelerated aging and swelling tests on lithium-ion batteries from five leading brands, which together represent over half of the global smartphone market share. The research involves a series of comprehensive tests, including Accelerated Rate Calorimeters (ARC) test, mechanical, electrical, and thermal abuse tests in accordance with Chinese national standards, as well as gas composition and theoretical flammability analyses on both new and swollen batteries. The findings indicate that swollen batteries generally exhibit safer behavior under floating charging conditions, and both new and swollen batteries pass the abuse tests within the standard framework. This study suggests that the safety of swollen lithium-ion batteries cannot be categorically labeled as dangerous or safe and should be assessed within the context of specific environments.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"22 ","pages":"Article 100368"},"PeriodicalIF":15.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microstructure-based digital twin thermo-electrochemical modeling of LIBs at the cell-to-module scale","authors":"Siyoung Park ,&nbsp;Hyobin Lee ,&nbsp;Seungyeop Choi ,&nbsp;Jaejin Lim ,&nbsp;Suhwan Kim ,&nbsp;Jihun Song ,&nbsp;Mukarram Ali ,&nbsp;Tae-Soon Kwon ,&nbsp;Chilhoon Doh ,&nbsp;Yong Min Lee","doi":"10.1016/j.etran.2024.100370","DOIUrl":"10.1016/j.etran.2024.100370","url":null,"abstract":"<div><div>As the application of lithium-ion batteries (LIBs) expands beyond conventional electric vehicles (EVs) to heavy vehicles such as electric trucks or trams, the importance of thermal management in LIB systems is increasing, even at the module or pack level. In particular, because monitoring the thermal behaviors of each cell is not feasible, thermo-electrochemical modeling and simulations in the module or pack level are essential for analyzing and ensuring thermal stability. However, because the conventional lumped thermo-electrochemical models cannot reflect the actual structure of LIB cells, there might be considerable differences may exist between simulation and experimental results. To fill these gaps, we have newly developed a 3D microstructure-based digital twin model of a battery module (8.8 Ah/18.5 V, five LIB pouch cells in series) for an unmanned railway vehicle. Unlike traditional lumped models, our digital twin model accurately well reflects the internal structure of cells and can calculate the heat generation of each component inside a cell. As a result, contrary to a lumped model, the digital twin model can not only simulate the inhomogeneous temperature gradient inside a cell, but also estimates higher local maximum temperatures (T_{DT, max}/T_{L, max} = 137.2 °C/123.9 °C @ 10C discharge) in cells which can trigger thermal runaway. Therefore, microstructure-based digital twin modeling can alleviate concerns regarding the thermal runaway of LIB cells, modules, and packs, and provide safe operating conditions.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"22 ","pages":"Article 100370"},"PeriodicalIF":15.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Battery engineering safety technologies (BEST): M5 framework of mechanisms, modes, metrics, modeling, and mitigation","authors":"Jingyuan Zhao ,&nbsp;Zhilong Lv ,&nbsp;Di Li ,&nbsp;Xuning Feng ,&nbsp;Zhenghong Wang ,&nbsp;Yuyan Wu ,&nbsp;Dapai Shi ,&nbsp;Michael Fowler ,&nbsp;Andrew F. Burke","doi":"10.1016/j.etran.2024.100364","DOIUrl":"10.1016/j.etran.2024.100364","url":null,"abstract":"<div><div>The increasing adoption of electric vehicles (EVs) has underscored the importance of lithium-ion batteries (LIBs), which, however, pose inherent safety risks. These issues can escalate from moderate faults to critical failures, potentially leading to thermal runaway—a dangerous chain reaction that can result in fires and explosions. Therefore, addressing and mitigating these safety hazards is crucial. This review introduces the concept of Battery Engineering Safety Technologies (BEST), summarizing recent advancements and aiming to outline a holistic and hierarchical framework for addressing real-world battery safety issues step by step: mechanisms, modes, metrics, modelling, and mitigation. Specifically, the M5 framework includes: (a) identification of mechanisms and causes, (b) failure mode and effects analysis, (c) metrics for evaluation, (d) modelling and forecasting, and (e) mitigation through material optimization, cell, and system design. Applications of the M5 hierarchical assessment, stemming from observational, empirical, statistical, and physical understanding of batteries at the materials, cell, and pack levels, not only have the potential to produce new insights but also contribute to dramatic efficiencies, more accurate predictions, and better interpretability for the evolution of electrochemical systems. It concludes with an overview of current challenges and future directions in battery safety research, emphasizing data-centered, AI-based digital solutions.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"22 ","pages":"Article 100364"},"PeriodicalIF":15.0,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142357907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synergies of variable renewable energy and electric vehicle battery swapping stations: Case study for Beijing","authors":"Chongyu Zhang ,&nbsp;Xi Lu ,&nbsp;Shi Chen ,&nbsp;Mai Shi ,&nbsp;Yisheng Sun ,&nbsp;Shuxiao Wang ,&nbsp;Shaojun Zhang ,&nbsp;Yujuan Fang ,&nbsp;Ning Zhang ,&nbsp;Aoife M. Foley ,&nbsp;Kebin He","doi":"10.1016/j.etran.2024.100363","DOIUrl":"10.1016/j.etran.2024.100363","url":null,"abstract":"<div><div>Battery swapping technology has emerged as a promising option for simultaneously addressing electric vehicle (EV) range anxiety and uncoordinated charging impacts, thereby enabling a renewable-powered future at the city scale. This study aims to explore the potential synergies between variable renewable energy (VRE), including wind and solar power, and the city-scale operation of battery swapping stations (BSSs) under varying levels of VRE penetration. To this end, an integrated modeling framework that combines multisource traffic data with node-based BSS deployment optimization and hourly power system dispatch simulations was developed. Beijing in 2025 was selected as the case study due to its ambitious EV development goals and the substantial need for VRE integration. The simulation results reveal that system-optimized BSS operations, particularly through bidirectional charging (V2G), can significantly enhance VRE integration, reduce net load fluctuations, and mitigate carbon emissions. Specifically, increasing VRE penetration from 30 % to 70 % reduces VRE curtailment by 1.1 TWh to 6.4 TWh and avoids 3.0 t to 6.3 t of carbon emissions per vehicle annually. The economic analysis further indicates that while current time-of-use electricity pricing leads to higher costs for BSS operations, a real-time pricing mechanism offers a more economically viable solution, benefiting both power system operators and BSS operators. The integrated modeling framework developed in this study not only advances the understanding of city-scale BSS operations but also provides a valuable tool for analyzing the complex interactions between EV infrastructure, VRE integration, and urban power grids.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"22 ","pages":"Article 100363"},"PeriodicalIF":15.0,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing capacity estimation of retired electric vehicle lithium-ion batteries through transfer learning from electrochemical impedance spectroscopy","authors":"Wenjun Fan ,&nbsp;Bo Jiang ,&nbsp;Xueyuan Wang ,&nbsp;Yongjun Yuan ,&nbsp;Jiangong Zhu ,&nbsp;Xuezhe Wei ,&nbsp;Haifeng Dai","doi":"10.1016/j.etran.2024.100362","DOIUrl":"10.1016/j.etran.2024.100362","url":null,"abstract":"<div><p>The low economic feasibility caused by inefficient testing and inaccurate performance estimation is one of the main bottlenecks in the echelon utilization of large-scale retired batteries. This study proposes a fast and accurate capacity estimation method for retired batteries based on electrochemical impedance spectroscopy (EIS). Firstly, the EIS of the batteries that experience multi-condition aging in the laboratory are collected. EIS characteristic parameter sequences highly related to battery performance, including real part and magnitude, are directly extracted to establish a base bi-directional long short-term memory model. Secondly, a transfer learning method based on feature matching is designed, which applies a linear transformation layer to map the features between the source and target domains. The proposed transfer learning method has been effectively validated on laboratory battery data measured at different temperatures and retired battery datasets of different material types. The improvements are especially notable for retired batteries. The detection time has been reduced, with each cell requiring only 1.67 min. And using only a small amount of data as input for transfer learning can achieve an accuracy improvement of over 90 %, indicating an effective transfer channel from the base model established on laboratory small-capacity battery aging data to large-capacity retired battery data is successfully established for the first time. For retired nickel-cobalt-manganese batteries, the mean absolute percentage error (MAPE) and the root mean square percentage error (RMSPE) are 2.33 % and 2.75 %, respectively, while for retired lithium-iron-phosphate batteries, the MAPE and RMSPE reached 4.12 % and 5.04 %, respectively. The results demonstrate the proposed method reduces the cost of repeated testing, modeling, and training for specific retired batteries while maintaining the accuracy of capacity estimation. This advancement helps to improve the efficiency of large-scale retired battery grading, and injects new momentum into facilitating more effective decision-making processes.</p></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"22 ","pages":"Article 100362"},"PeriodicalIF":15.0,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}