Etransportation最新文献

{"title":"Degradation analysis and tanks-in-series modeling of lithium-ion batteries with state of health-adaptive charging strategies","authors":"Xingjun Li ,&nbsp;Dan Yu ,&nbsp;Søren Byg Vilsen ,&nbsp;Puneet Jindal ,&nbsp;Venkat R. Subramanian ,&nbsp;Daniel Ioan Stroe","doi":"10.1016/j.etran.2026.100561","DOIUrl":"10.1016/j.etran.2026.100561","url":null,"abstract":"<div><div>Dynamic operating conditions significantly impact the lifetime of lithium-ion batteries in electric vehicles. While battery lifetime can be extended by optimizing charging profiles to reduce degradation, many existing charging optimization approaches are developed based on fixed, idealized full charge-discharge cycles. These differ from the random and partial charge-discharge behavior in real-world operation and do not consider the influence of battery degradation on charging current profile optimization. To address these limitations, this study designs two groups of battery aging tests to study charging optimization in real-world operation: one subjected to four fixed charging scenarios based on typical daily commuting patterns, and the other to dynamically changing charging scenarios based on state of health change. Capacity degradation, internal resistance increase, and charging time of all cells are analyzed and compared. Degradation modes such as loss of active materials and lithium inventory are examined through incremental capacity and differential voltage analyses. A novel tanks-in-series thermal-aging model is proposed to rapidly simulate battery behavior under dynamic charging, enabling rapid exploration of more charging scenarios constrained by experimental channels or costly to perform. Results demonstrate that dynamically switching charging strategies based on state of health can effectively extend battery lifetime while reducing overall charging time. Moreover, the model proves efficient in identifying optimal charging strategies. These findings offer valuable insights into charging optimization considering practical use scenarios, and present a promising tool for charging optimization.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"28 ","pages":"Article 100561"},"PeriodicalIF":17.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173840","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":"Elucidating internal explosion dynamics in lithium-ion batteries: From experimental analysis to theoretical modeling","authors":"Mengqi Zhang ,&nbsp;Chengshan Xu ,&nbsp;Shaw Kang Wong ,&nbsp;Huaibin Wang ,&nbsp;Fangshu Zhang ,&nbsp;Changyong Jin ,&nbsp;Yong Peng ,&nbsp;Peiben Wang ,&nbsp;Fachao Jiang ,&nbsp;Xuning Feng","doi":"10.1016/j.etran.2026.100588","DOIUrl":"10.1016/j.etran.2026.100588","url":null,"abstract":"<div><div>The explosion risk inherent in high-energy-density and large-scale batteries remains a significant barrier to their widespread deployment in energy storage and transportation systems. Within an individual cell, thermal runaway generates both solid and gaseous reaction fronts, the dynamic behaviors of which have been partially characterized in prior studies. The rapid propagation of these thermal runaway fronts through narrow gas channels between electrodes can trigger internal explosions. This study develops a comprehensive mathematical model to describe the internal dynamics of batteries during thermal runaway, derived from experimental observations and quantitative data, to establish boundary conditions for explosion initiation. Explosion phenomena were systematically examined in various types of cells, with experimentally measured gas explosion limits ranging from approximately 5.39% to 47.5%. By drawing an analogy with the deflagration-to-detonation transition, a hypothesis of thermal runaway front-induced detonation was proposed and mathematically formulated. A velocity expression for the thermal runaway gas front was derived, showing that its propagation speed is material-dependent—directly proportional to the gas generation rate and the velocity of the solid front, and inversely proportional to the width of the gas channel. Based on this formulation, boundary conditions for internal detonation were established. For high-energy-density and large-format batteries, the calculated Mach numbers of the solid front, gas front, and exhaust gas at the safety valve may exceed 1, indicating the potential for detonation. These results confirm the feasibility of internal detonation and provide a quantitative criterion for evaluating explosion risks. The proposed framework is applicable to various battery chemistries and offers theoretical guidance for the safety design of next generation high energy batteries.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"28 ","pages":"Article 100588"},"PeriodicalIF":17.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147849990","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":"Accurate electrolyte volume of lithium-ion battery via ultrasonic sensing and time-delay neural networks","authors":"Fangze Zhao ,&nbsp;Xuebing Han ,&nbsp;Languang Lu ,&nbsp;Xiangjun Li ,&nbsp;Peng Guo ,&nbsp;Lifang Liu ,&nbsp;Jianfeng Hua ,&nbsp;Yuejiu Zheng ,&nbsp;Minggao Ouyang","doi":"10.1016/j.etran.2026.100552","DOIUrl":"10.1016/j.etran.2026.100552","url":null,"abstract":"<div><div>Electrolyte content is a pivotal determinant of the electrochemical performance and thermal safety of lithium-ion batteries. Yet, current measurement approaches—ranging from destructive offline analyses to expensive nondestructive imaging—suffer from latency, complexity, or insufficient accuracy, limiting their suitability for real-time and high-precision monitoring. Here, we present a nondestructive strategy for electrolyte volume assessment that integrates ultrasonic sensing with deep learning. An acoustic simulation model was first developed to characterize wave propagation in wetted versus unwetted regions, revealing distinct transmission pathways and providing direct validation of the underlying physical mechanism. Ultrasonic measurements on cells with varying filling levels further demonstrated that conventional acoustic features, such as peak amplitude, time-of-flight, and energy, show weak correlations with electrolyte volume. By contrast, ultrasonic imaging clearly captured the progressive shrinkage of wetted regions as electrolyte decreased. Leveraging this insight, a time-delay neural network (TDNN) was employed to extract nonlinear temporal features directly from raw waveforms, while a physics-informed correction—incorporating the prior knowledge that electrolyte reduction leads to shrinkage of wetted regions—was introduced to refine predictions. Experimental validation confirmed that the method achieves a stable prediction error within ±2% and demonstrates strong generalizability across different battery chemistries. This work provides a practical and accurate nondestructive pathway for electrolyte volume determination, offering new opportunities for quality control and health monitoring in lithium-ion batteries.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"28 ","pages":"Article 100552"},"PeriodicalIF":17.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173835","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":"Impact of electric vehicles on low-voltage distribution networks: A critical review","authors":"P. Zunino,&nbsp;T. Unterluggauer,&nbsp;M. Marinelli,&nbsp;J. Engelhardt","doi":"10.1016/j.etran.2026.100594","DOIUrl":"10.1016/j.etran.2026.100594","url":null,"abstract":"<div><div>The integration of electric vehicles (EVs) into low-voltage power distribution networks (LVDNs) introduces a new class of mobile, high-power, and behaviorally uncertain loads. This review article systematically analyzes the existing literature to assess how EV charging affects transformer and cable loading, voltage deviation, phase unbalance, power losses, and harmonics. Unlike existing reviews that assess the impact of EVs alongside other distributed technologies, or those that focus primarily on medium-voltage networks, this paper provides a targeted synthesis of EV impacts specifically within LVDNs. The analysis shows that the types and severity of impacts are influenced by grid topology: rural networks are more prone to voltage deviations due to long feeders, urban networks face transformer overloading from dense residential demand, and suburban networks are vulnerable to both. Moreover, user-centric charging strategies, especially when applied uniformly across many EVs, can aggravate grid issues by synchronizing demand. Conversely, EVs hold significant potential as flexible grid assets, provided that local flexibility solutions and coordination mechanisms are in place. To this end, the review identifies key opportunities to strengthen research and practice, including clearer methodological reporting, standardized baseline scenarios, and more realistic modeling approaches that reflect the heterogeneity of charging behaviors and EV types. While simulation remains a powerful tool, expanding empirical validation through field studies is essential to ground findings in operational reality. Such studies can also demonstrate how improved observability in LVDNs is critical for unlocking EV flexibility and enabling proactive grid integration.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"28 ","pages":"Article 100594"},"PeriodicalIF":17.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147797748","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 pack diagnostics for electric vehicles: Robustness of the state of health measurement and differential voltage analysis at the vehicle level","authors":"Philip Bilfinger,&nbsp;Philipp Rosner,&nbsp;Markus Schreiber,&nbsp;Tobias Brehler,&nbsp;Cristina Grosu,&nbsp;Jan Schöberl,&nbsp;Kareem Abo Gamra,&nbsp;Markus Lienkamp","doi":"10.1016/j.etran.2026.100589","DOIUrl":"10.1016/j.etran.2026.100589","url":null,"abstract":"<div><div>Battery aging reduces an electric vehicle’s (EV) range and power capabilities, which are key factors for purchasing (second-hand) electric vehicles. As both properties degrade with time and usage, reliable methods are necessary to track battery aging and provide insights into the degradation progression. In the battery domain, aging is often assessed through remaining energy measurements such as for the state of health (SOH) metric, and differential voltage (DV) analysis. Recent studies have demonstrated that both methods are similarly applicable at the vehicle level using low-power charging measurements. In this article, the robustness of vehicle-level charging measurements for SOH determination and DV analysis are evaluated under variations in external conditions, including charging power, ambient temperature, current direction, and resting state of charge, using the state-of-the-art EVs Volkswagen ID.3, Cupra Born and Tesla Model 3. Additionally, the reproducibility and comparability of the measurement procedure are analyzed through measurements with multiple vehicles of the same model. Overall, vehicle-level SOH determination and DV analysis prove to be robust and reproducible when boundary conditions are consistently met, e.g, containment of charging power and temperatures. The results are also comparable across identical EV models, enabling the use of pristine reference vehicles as a basis for assessing aging in EVs lacking an initial battery characterization.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"28 ","pages":"Article 100589"},"PeriodicalIF":17.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147849997","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":"Electrical load forecasting for V2G scheduling: A feature-driven multi-head attention-LSTM approach","authors":"Tianyu Yan ,&nbsp;Jiahao Zhong ,&nbsp;Ziyun Shao ,&nbsp;C.C. Chan ,&nbsp;Linni Jian","doi":"10.1016/j.etran.2026.100556","DOIUrl":"10.1016/j.etran.2026.100556","url":null,"abstract":"<div><div>Electrical load forecasting (ELF) is a critical technology for vehicle-to-grid (V2G) scheduling, as it provides the necessary information to achieve the scheduling objective of minimizing load variance. Existing studies have demonstrated that the closer the relative magnitude relationships among forecasted loads at different time periods are to those of the actual loads, the more satisfactory V2G scheduling performance can be achieved. Inspired by the above conclusion, this paper proposes an ELF approach for V2G scheduling. By calculating the difference between load values at each time period and the daily average, a feature called load relative magnitude (LRM) is constructed to provide relative magnitude relationships between loads for the forecasting model, which is beneficial for enhancing V2G scheduling performance. Moreover, this approach builds a feature-driven multi-head attention-long short-term memory (FDMHA-LSTM) model and the constructed LRM feature is the driver. In particular, given that the multi-head attention (MHA) mechanism can be guided to focus on the key parts of the task, the LRM feature is employed to weight the Key matrix for enhancing prediction accuracy during peak and valley periods, and these periods are particularly important for V2G scheduling performance. Furthermore, extensive experiments on real-world load data demonstrate the effectiveness and superiority of the proposed model. Specifically, the proposed model can boost V2G scheduling performance by 15% to 22.3% under scenarios with varying numbers of EVs compared to LSTM model, and also demonstrates advantages over CNN and compact Transformer baselines.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"28 ","pages":"Article 100556"},"PeriodicalIF":17.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173832","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":"Cooperative scheduling for multi-fleet battery swapping in electrified mines: A simulation-based optimization approach","authors":"Honghui Zou ,&nbsp;Kaiqi Zhao ,&nbsp;Yanli Liu ,&nbsp;Ronghui Zhang ,&nbsp;Xiaolei Ma","doi":"10.1016/j.etran.2026.100562","DOIUrl":"10.1016/j.etran.2026.100562","url":null,"abstract":"<div><div>Global carbon reduction policies have accelerated the electrification transition in open-pit mine. To meet the continuous operational demands of mining truck fleets, the battery swapping (BS) mode has emerged as an efficient solution. This study investigates cooperative scheduling of multiple fleets in an open-pit mining system equipped with distributed BS stations and centralized charging facilities, including electric mining trucks and battery delivery vehicles. An innovative discrete event simulation (DES)-based optimization framework is proposed, which leverages the controllability of BS demand and battery supply to coordinate supply- and demand-side operations, thereby unlocking potential efficiencies and deriving an optimal scheduling scheme for mining truck operation, BS activities, and battery logistics. A DES model is developed to simulate the interactions among heterogeneous fleets, various resources and facilities, as well as cascading delays induced by queuing in the operational, BS, and battery pickup processes. Furthermore, the DES model is also employed as a repair tool to rapidly correct infeasible solutions. To address the curse of dimensionality inherent in simulation-based optimization, we propose the non-dominated sorting population-based large neighborhood search (NSPLNS) algorithm, which integrates the advantages of population-based multi-objective search and individual-directed enhancement. A series of customized operators tailored to improving the quality of solutions are designed, and parallel simulations to enhance algorithmic efficiency are explicitly incorporated into the algorithm. A real-world case study from Inner Mongolia, China, is used to evaluate the proposed framework and algorithm. Numerical experiments analyze algorithm performance, the impact of customized operators, and conduct sensitivity analyses. Numerical results demonstrate that the proposed model and algorithm enhance the operational economics by maximizing profit, and improve BS efficiency by minimizing queueing and BS time. The source code of this study is publicly available at: <span><span>https://github.com/HonghuiZou/NSPLNS</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"28 ","pages":"Article 100562"},"PeriodicalIF":17.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173834","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":"Visualizing electrolyte dynamics and monitoring salt concentration to improve commercial Si-based Li-ion batteries","authors":"Nilanka M. Keppetipola ,&nbsp;Clémence Alphen ,&nbsp;Marina-Lamprini Vlara ,&nbsp;Christoph Stangl ,&nbsp;Christophe Caucheteur ,&nbsp;Ozlem Sel ,&nbsp;Jean-Marie Tarascon","doi":"10.1016/j.etran.2026.100554","DOIUrl":"10.1016/j.etran.2026.100554","url":null,"abstract":"<div><div>The race for Li-ion batteries with higher energy density has led researchers toward Si-rich/Carbon composites, though their &gt;200 % volume change induces strong electrolyte dynamics. The challenge is therefore to understand how this electrolyte dynamics contributes to cell formation and degradation under real operating conditions. Herein, we answer this question by combining optical calorimetry, and use of multiplexed tilted fiber Bragg grating sensors (TFBGs), to monitor electrolyte motion and Li-ion concentration gradient within a cell. For proof of concept, we used 21700 cylindrical prototype cells based on either graphite or SiC composite as negative electrode. We found a continuous and irreversible heat generation associated with the solid electrolyte interphase (SEI) formation throughout the entire charging process for SiC, unlike graphite-based cells. In addition, we provided evidence of reversible changes in hydrostatic pressure in SiC cells during cycling, related to the real-time movement of the electrolyte. Interestingly, the concomitant expansion-contraction and electrolyte movement caused depletion and inhomogeneous LiPF₆ concentration, with nearly 35 % in the bottom area and 10 % in the middle area of the cell mandrel after 100 cycles. These insights, obtained through <em>operando</em> optical detection of cylindrical cells, should be of great help to battery manufacturers in streamlining formation protocols and reducing manufacturing costs.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"28 ","pages":"Article 100554"},"PeriodicalIF":17.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173833","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":"Developing an efficient hierarchical regrouping method for uncharacterized retired electric vehicle Li-ion batteries based on partial pulse discharge curves","authors":"Jun Zhang ,&nbsp;Zheming Tong ,&nbsp;Ning Ren ,&nbsp;Xing Chen ,&nbsp;Xiangkun Elvis Cao","doi":"10.1016/j.etran.2026.100591","DOIUrl":"10.1016/j.etran.2026.100591","url":null,"abstract":"<div><div>The echelon utilization of retired electric vehicle lithium-ion batteries (REV-LIBs) has been proven to reduce the carbon emissions and costs throughout the whole life cycle, an advantage that has been fully verified through diverse application scenarios such as energy storage systems. However, the significant performance discrepancies among cells and time-consuming characterization remain key bottlenecks hindering its large-scale implementation. To address these challenges, this study proposes a data-driven hierarchical screening and grouping framework for REV-LIBs with unknown initial states, based on partial pulse testing and eliminating the need for pre-adjustment of initial states. By analyzing the unsupervised clustering results derived from different features, the incorporation of polarization characteristics into clustering features improves the consistency of batteries in the same group by 7.3%, compared to the conventional clustering method relying on capacity and direct current internal resistance (DCIR). Subsequently, partial pulse discharge curves and a two-dimensional convolutional neural network (2D-CNN) model are employed to conduct classification and estimate the capacity and DCIR of retired batteries, respectively, with experimental results showing that this approach achieves a classification accuracy exceeding 96.0%, the maximum absolute error (MaxAE) of capacity estimation below 3.0%, and that of DCIR estimation below 5.0%. The test duration can be shortened to 18 min by increasing the discharge rate and shortening the rest time. Finally, topology-aware regrouping is implemented to further enhance the capacity uniformity of series branches by over 52.9% and the resistance uniformity of parallel branches by more than 86.0%. This research presents a practical and feasible solution for both the estimation of capacity and DCIR and the multi-level regrouping of REV-LIBs with unknown initial states, which is highly significant for large-scale engineering applications.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"28 ","pages":"Article 100591"},"PeriodicalIF":17.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147797750","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 multifunctional organic phase change materials for battery thermal safety in electric transportation systems: A critical review","authors":"Xinxi Li ,&nbsp;Beiwen Liang ,&nbsp;Jian Deng ,&nbsp;Wensheng Yang ,&nbsp;Qiqiu Huang ,&nbsp;Ziyu Huang ,&nbsp;Gengfeng Zhao ,&nbsp;Shuyao Li ,&nbsp;Zikai Guo ,&nbsp;Jianzhe Liu ,&nbsp;Canbing Li","doi":"10.1016/j.etran.2026.100558","DOIUrl":"10.1016/j.etran.2026.100558","url":null,"abstract":"<div><div>Electric transportation systems are great alternatives to conventional fossil-fuel-powered transportation systems. The thermal safety of high-energy-density lithium-ion batteries (LIBs), which are the main energy source in electric transportation systems, is one of the most major challenges facing the applications of these systems. Phase change material (PCM)-based battery thermal management systems are an effective solution for battery thermal safety, and they have a great application potential. However, the thermal safety of LIBs involves thermal management and thermal runaway protection, which require composite PCMs (CPCMs) with excellent thermal management cooling effect and stable thermal runaway protection capability. Thus, the optimizing strategies used for enhancing the structural stability, thermal conductivity, and flame retardancy of CPCMs were compared and analyzed. Moreover, the design of PCMs with thermal management and thermal-runaway-flame-retardant suppression capabilities was discussed. Finally, future research directions for using multifunctional PCMs in battery thermal safety systems were proposed based on critical thinking. This review will provide new insights and attract considerable attention to the reliability of thermal safety systems based on multifunctional PCMs in future designs, especially in the field of battery thermal safety.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"28 ","pages":"Article 100558"},"PeriodicalIF":17.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173841","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}