Etransportation最新文献

{"title":"Maritime electrification pathways for sustainable shipping: Technological advances, environmental drivers, challenges, and prospects","authors":"Zhe Wang ,&nbsp;Pengzhi Liao ,&nbsp;Fei Long ,&nbsp;Zhengquan Wang ,&nbsp;Yulong Ji ,&nbsp;Fenghui Han","doi":"10.1016/j.etran.2025.100462","DOIUrl":"10.1016/j.etran.2025.100462","url":null,"abstract":"<div><div>Maritime electrification has gained unprecedented momentum as the shipping industry faces stringent global decarbonization targets and increasingly rigorous International Maritime Organization (IMO) regulations. This review provides a systematic assessment of the technological advances, environmental drivers, challenges, and future prospects of ship electrification, with a focus on three primary pathways: Battery-Electric Ships (BES), Hybrid-Electric Ships (HES), and Fuel Cell Electric Ships (FCES). The analysis encompasses technological maturity levels (TRL), economic competitiveness, lifecycle environmental performance, and regional deployment feasibility. Findings indicate that HES currently dominate commercial applications owing to their operational flexibility and compliance readiness, while BES demonstrate strong potential for short-sea and inland shipping routes, and FCES represent a long-term solution for deep decarbonization provided that green hydrogen and ammonia infrastructure becomes available. The review highlights persistent barriers, including limited energy density for large vessels, insufficient megawatt-scale charging and refueling infrastructure, durability and reliability concerns under harsh marine conditions, and misaligned global policy frameworks. Notable contributions include the provision of quantitative TRL evaluations for BES, HES, and FCES, a comparative analysis of regional deployment strategies targeting emission-intensive maritime zones, and the identification of AI-enabled digital twin technologies as a promising approach to optimize energy management and fleet operations. To accelerate maritime electrification, future research is directed toward breakthroughs in solid-state batteries, advanced corrosion-resistant materials, safe and efficient hydrogen/ammonia storage, port-level renewable microgrids, and standardized international safety regulations. Overall, this review establishes a comprehensive roadmap for academia, industry stakeholders, and policymakers to advance the transition toward sustainable, zero-emission shipping.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100462"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004529","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":"3D-printed honeycomb lithium-silicon alloy anodes for stabilized interface in sulfide all-solid-state batteries","authors":"Lutong Wang ,&nbsp;Ziqi Zhang ,&nbsp;Fuqiang Xu ,&nbsp;Jixian Luo ,&nbsp;Chuang Yi ,&nbsp;Hong Li ,&nbsp;Liquan Chen ,&nbsp;Fan Wu","doi":"10.1016/j.etran.2025.100476","DOIUrl":"10.1016/j.etran.2025.100476","url":null,"abstract":"<div><div>Solid-state batteries have emerged as a crucial development direction for next-generation energy storage technologies, owing to their high energy density, long cycle life, and excellent safety. However, the most challenging issue of interfacial contact/degradation in solid-state batteries remains unsolved. Herein, a novel Si-C interlocking honeycomb electrode is designed/realized via 3D printing technology. Achieves 98.9 % capacity retention over 2100 cycles at 1C. The honeycomb pore walls form a mortise-tenon structure with the electrolyte to maintain good interfacial contact, while the hard carbon layer isolates the electrolyte from the lithium-silicon interface, thereby stabilizing the growth of the solid electrolyte interphase (SEI) and achieving stress-electrochemical coupling regulation. Moreover, as the honeycomb channels form an interpenetrating structure with the solid electrolyte, a three-dimensional ion transport network is established, shortening the lithium-ion diffusion path, enhancing the interfacial contact between the electrode and solid electrolyte, reducing the risk of lithium dendrite formation, and improving the rate performance of all-solid-state batteries. This approach leverages structural design to enhance material performance, for the first time enabling the compatibility of 3D-printed structured silicon-based anodes with sulfide-based all-solid-state systems, thus providing a scalable solution for next-generation high-energy-density batteries.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100476"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004531","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":"Online generation of full-frequency electrochemical impedance spectra for Lithium-ion batteries using early-stage partial relaxation voltage curve","authors":"Jiajun Zhu ,&nbsp;Xin Lai ,&nbsp;Zhicheng Zhu ,&nbsp;Penghui Ke ,&nbsp;Yuejiu Zheng ,&nbsp;Xiaopeng Tang ,&nbsp;Xiang Li ,&nbsp;Ye Yuan ,&nbsp;Haoyu Chong ,&nbsp;Chenhui Yan ,&nbsp;Ying Wang ,&nbsp;Yanke Lin ,&nbsp;Xiaolei Zhou ,&nbsp;Yingjie Chen","doi":"10.1016/j.etran.2025.100482","DOIUrl":"10.1016/j.etran.2025.100482","url":null,"abstract":"<div><div>Electrochemical impedance spectroscopy (EIS) serves as a powerful non-destructive tool for lithium-ion battery state assessment, yet its real-time application faces significant challenges including expensive hardware requirements, time-consuming measurements, and stringent data quality demands. This study develops a hardware-free online electrochemical impedance spectroscopy using only relaxation voltage, achieved through a physics-informed neural network (PINN) that predicts full-frequency EIS from early-stage partial relaxation curves. The proposed approach exhibits remarkable insensitivity to battery state of charge and state of health, as validated by a comprehensive dataset containing over 300 impedance spectra from four batteries under various aging conditions. Experimental results demonstrate accurate EIS prediction with relative errors (RE) below 5.6 % and mean absolute errors (MAE) below 1.12 mΩ when using complete relaxation curves. Crucially, the method maintains reliability under practical constraints, achieving maximum RE of 6.1 % and MAE of 1.29 mΩ even with limited sampling data and shortened relaxation curves. By enabling online full-frequency EIS acquisition through relaxation voltage signals without hardware requirements, this work establishes a new paradigm for real-time battery diagnostics, providing valuable insights for state estimation and fault detection in battery management systems.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100482"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145057327","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":"A reconfigurable battery system for a Tesla Model Y: Package and efficiency analysis","authors":"Andreas Wiedenmann ,&nbsp;Julian Estaller ,&nbsp;Johannes Buberger ,&nbsp;Wolfgang Grupp ,&nbsp;Manuel Kuder ,&nbsp;Antje Neve ,&nbsp;Thomas Weyh","doi":"10.1016/j.etran.2025.100464","DOIUrl":"10.1016/j.etran.2025.100464","url":null,"abstract":"<div><div>This study investigates the integration of a modular multilevel inverter-based reconfigurable battery system into an existing electric vehicle. The aim is to evaluate how such systems can replace conventional traction inverters, battery management systems, and on-board chargers. To this end, a classification of the different topology levels and possible forms of integration of power electronics, control logic, and driver electronics is performed. A Tesla Model Y’s traction battery is redesigned, retaining its structural properties and the 4680 cell format. A package analysis shows that the multilevel system occupies a volume comparable to the conventional battery pack, while the volume previously reserved for dedicated power electronics becomes available. Efficiency simulations demonstrate that the multilevel inverter can increase the overall vehicle efficiency, especially in situations with low driving speeds and high torque requirements. As a result, WLTP energy consumption is reduced from 14.9 kWh/100km to 14.5 kWh/100km. However, the battery efficiency is reduced at higher speeds due to higher cell currents. In addition, the system enables bidirectional charging at full system power, including supply to external loads or the grid, and a more integrated vehicle architecture.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100464"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096467","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":"Cathode with a temperature-switchable interlayer for thermally self-regulating smart lithium-ion batteries","authors":"Kehan Le ,&nbsp;Chunchun Sang ,&nbsp;Qijun Luo ,&nbsp;Hui Li ,&nbsp;Yongjin Fang ,&nbsp;Xinping Ai","doi":"10.1016/j.etran.2025.100483","DOIUrl":"10.1016/j.etran.2025.100483","url":null,"abstract":"<div><div>Thermal safety is crucial for the large-scale application of lithium-ion batteries (LIBs) in electric vehicles and energy storage stations. To boost thermal safety of LIBs, we propose herein a reversible temperature-responsive membrane (RTRM) and use this membrane as surface-modification layer of current collector to develop temperature-responsive cathodes. The RTRM is fabricated by uniformly dispersing conductive fillers of short-cut carbon fibers (CCFs) in a blended plastic matrix of low-density polyethylene (LDPE) and ultra-high molecular weight polyethylene (UHMWPE) through solution casting. Benefiting from the large thermal expansion provided by LDPE and good structural reproducibility given rise by the ultra-high melt viscosity of UHMWPE, the as-fabricated RTRM exhibits a strong and reversible positive temperature coefficient (PTC) effect, with its resistivity increasing sharply by 7.1 orders of magnitude at 110–120 °C and returning to the initial value reversibly upon cooling down even after 30 thermal cycles. As a result, the LiFePO₄ cathode with the RTRM demonstrates a reversible temperature-switching behavior by spontaneously halting the electrode reaction at elevated temperatures and resuming the electrode reaction upon cooling, thereby providing reversible thermal protection for LIBs. Notably, such a temperature-switchable cathode maintains normal charge-discharge performance even after 28 thermal on/off cycles. This study offers a promising strategy for developing temperature-responsive cathode and thermally self-regulating smart LIBs.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100483"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096465","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 resource sustainability for lithium-ion batteries -A review of existing carbon emission reduction perspectives","authors":"Wenfang Gao ,&nbsp;Xianju Zeng ,&nbsp;Weiguang Lv ,&nbsp;Zhengqing Ye ,&nbsp;Bingxin Zhou ,&nbsp;Guangming Zhang ,&nbsp;Zhijun Ren ,&nbsp;Zhiyuan Feng ,&nbsp;Wei Jin ,&nbsp;Zhi Sun","doi":"10.1016/j.etran.2025.100491","DOIUrl":"10.1016/j.etran.2025.100491","url":null,"abstract":"<div><div>The resource recycling of lithium-ion batteries (LIBs) can significantly reduce the carbon emission, which has received unprecedented attention from both the academic and industrial communities. However, the large consumption of valuable materials (<em>e.g.</em>, Li, Co, Ni, Mn, graphite) for LIBs not only intensifies the pressure on global resource supply, but also raises the carbon footprint of the industry. Herein, this review systematically analyses the LIBs industry from the aspects of resource supply and resource cycle, in combination with the carbon emission reduction analyzation of LIBs industry. By analyzing the development status of LIBs materials, the resource composition and critical metals are clearly clarified. With LIBs demand increasing, the resource criticality, primary and secondary resource supply are deeply evaluated where Li and Co supply face enormous challenges. The recycling of spent LIBs gives an effective way for resource utilization and circulation. The carbon emission intensity of the whole LIBs industrial chain is discussed from the perspective of resource supply, utilization, and balance, where the carbon emission reduction mainly relies on the use of low-carbon energy and the recycling/reproduction processes. This critical review revealed that resource sustainability and carbon neutralization are an inseparable system, and can give guidance to the development of LIBs materials to ensure the sustainable development of resources in the future.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100491"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219593","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":"Physics-enhanced U-net and deep reinforcement learning for automated optimization of pin-fin heat sinks in electric vehicle power modules","authors":"Yubo Lian,&nbsp;Heping Ling,&nbsp;Gan Song,&nbsp;Jiapei Yang,&nbsp;Hanzhi Wang,&nbsp;Zhe Zhang,&nbsp;Shaokuan Mao,&nbsp;Bin He","doi":"10.1016/j.etran.2025.100463","DOIUrl":"10.1016/j.etran.2025.100463","url":null,"abstract":"<div><div>The use of pin-fin structures in compact energy devices, such as electric vehicle power modules, is a widely adopted thermal management strategy to enhance heat transfer efficiency. In this study, we present an innovative deep learning framework that integrates a physics-enhanced U-net architecture with a deep reinforcement learning agent to achieve autonomous optimal design of pin-fin arrays. The physics-enhanced U-net is trained to predict thermal-flow fields, while the integrated deep reinforcement learning agent autonomously optimizes pin-fin configurations to minimize both pressure drop and junction temperature. First, we generate a high-fidelity training dataset through an automated computational pipeline that integrates COMSOL Multiphysics for thermal-flow field simulations with a custom Matlab script for parametric generation of 1080 training samples. Subsequently, we train our physics-enhanced U-net architecture to predict the velocity, pressure and temperature fields from various pin-fin structure inputs. The proposed model demonstrates both high prediction accuracy and robustness, achieving mean-squared-errors on the order of 10⁻⁴ for all output fields. As a result, the trained U-net model achieves exceptional prediction accuracy, demonstrating 93.9 % precision for pressure drop and 99.5 % for junction temperature. Finally, we integrate the deep reinforcement learning agent with the trained U-net model to establish an automated optimization framework for pin-fin design, enabling intelligent exploration of design space. The proposed deep learning framework successfully automates the optimization of pin-fin heat sinks for a high power density module. The model demonstrates exceptional capability in generating optimal designs, with the optimized configuration achieving an 8.8 K reduction in junction temperature and 11.3 % decrease in pressure drop comparing to a baseline design. These improvements can be translated into approximately 10 % augmentation in power output, which validates both the effectiveness and robustness of our deep learning driven design approach.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100463"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027081","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":"Multi-parameter degradation of PEMFCs in freeze/thaw cycles: Impacts of assembly force and initial membrane water content on cold start durability for transportation applications","authors":"Lei Shi ,&nbsp;Ruitao Li ,&nbsp;Chang Du ,&nbsp;Julong Zhou ,&nbsp;Yahui Yi ,&nbsp;Ze Liu ,&nbsp;Jianbin Su ,&nbsp;Liqin Qian ,&nbsp;Tiancai Ma ,&nbsp;Shijia Yang ,&nbsp;Chengyu Xia ,&nbsp;Xingwang Tang","doi":"10.1016/j.etran.2025.100505","DOIUrl":"10.1016/j.etran.2025.100505","url":null,"abstract":"<div><div>The adaptability of fuel cell vehicles in extreme low-temperature environments remains a critical challenge urgently requiring breakthroughs in the transportation sector. As a core factor influencing low-temperature operational reliability, freeze/thaw cycles directly impact the performance stability and service life of fuel cells, and hold decisive significance for advancing the popularization and application of fuel cell vehicles in cold regions. This study investigates the degradation mechanisms of fuel cells subjected to freeze/thaw cycles under varying initial membrane dissolved water content and assembly force conditions. Building on three preliminary experiments-initial water content calibration, freezing time retardation analysis, and initial microstructure characterization of the catalytic layer and gas diffusion layer-a 100-h freeze/thaw test was conducted. Electrochemical impedance spectroscopy, cyclic voltammetry, and other characterization techniques were employed to assess the fuel cell degradation process. The degradation rate during freeze/thaw cycles was quantified using the distribution of relaxation times method and electrochemical active surface area. High-magnification optical microscopy and scanning electron microscopy were utilized to examine the microstructure of disassembled gas diffusion layers post-freeze/thaw cycles, offering insights into structural damage to both the catalytic layer and gas diffusion layer. Results reveal that higher assembly forces exacerbate gas diffusion layer degradation, leading to slower mass transport and increased mass transport resistance-with the distribution of relaxation times low-frequency peak rising by 202 % under a 13 N m assembly force after 5 cycles. Additionally, higher initial membrane dissolved water content slightly accelerates GDL degradation and significantly contributes to catalytic layer degradation, as evidenced by a 29 % reduction in electrochemical active surface area for 100 % initial water content after 5 cycles. The degradation mechanisms of fuel cells under freeze-thaw cycles revealed in this study provide crucial support for improving the low-temperature reliability of fuel cell vehicles in the transportation sector and promoting their commercialization and application in cold regions.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100505"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416083","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":"Towards real-world battery health intelligence: A review of machine learning advances and challenges in SOH estimation","authors":"Xing Shu ,&nbsp;Jiangwei Shen ,&nbsp;Fengxiang Guo ,&nbsp;Yonggang Liu ,&nbsp;Yuanjian Zhang ,&nbsp;Zheng Chen ,&nbsp;Hongqian Zhao","doi":"10.1016/j.etran.2025.100509","DOIUrl":"10.1016/j.etran.2025.100509","url":null,"abstract":"<div><div>Lithium-ion batteries have become the dominant power source in electric transportation due to their high energy density and long cycle life. Nevertheless, prolonged operation leads to irreversible degradation, and results in capacity fade and safety risks. Accurate estimation of state of health (SOH) is therefore critical for ensuring reliable electric vehicle operation and for guiding maintenance strategies. In recent years, extensive research has been devoted to SOH estimation, supported by both laboratory investigations and field applications. Unlike previous reviews that mainly focus on either laboratory data or algorithmic modeling, this review uniquely bridges the gap between lab-based methods and practical applications using real vehicle operational data by providing a comparative analysis of datasets, estimation methods, and application challenges. A systematic survey of recent advances is provided in lithium-ion battery SOH estimation. First, accelerated aging experiments under laboratory conditions and operational data acquisition in real-world scenarios are reviewed and compared. The extraction of health features, feature optimization, and dimensionality reduction techniques are elaborated. Second, the progress in modeling methods is summarized, including shallow neural networks, convolutional neural networks, recurrent neural networks, attention-based networks, and physics-informed networks. Third, SOH label acquisition methods and estimation approaches for real-world datasets are analyzed. Finally, three major challenges are discussed for improving SOH estimation accuracy in practice, including bridging the gap between laboratory and real-world conditions, achieving more reliable SOH labeling, and reducing the dependence on large-scale training data.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100509"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465208","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":"Atmosphere-regulated thermal runaway characteristics and multidimensional safety assessment of sodium-ion and lithium-ion batteries","authors":"Zhixiang Cheng,&nbsp;Zhiyuan Li,&nbsp;Yuxuan Li,&nbsp;Yin Yu,&nbsp;Chaoshi Liu,&nbsp;Zhenwei Wu,&nbsp;Peiyu Duan,&nbsp;Huang Li,&nbsp;Wenxin Mei,&nbsp;Qingsong Wang","doi":"10.1016/j.etran.2025.100475","DOIUrl":"10.1016/j.etran.2025.100475","url":null,"abstract":"<div><div>Understanding and quantifying the thermal runaway behavior of emerging battery chemistries is essential for ensuring safety in real-world applications. This study systematically investigates the thermal runaway characteristics of sodium-ion (SIB) and lithium-ion (LIB) batteries of comparable volumes under both air and inert gas environments. Experimental results show that under low-oxygen conditions, SIB and nickel–cobalt–manganese (NCM) cells exhibit substantial mitigation of thermal runaway severity, including over 35 % decrease in gas generation metrics, while lithium iron phosphate (LFP) cells remain largely unaffected. In gas composition analysis, NCM cells show significant decreases in CO₂/CO and O₂/N₂ ratios, whereas SIB and LFP display no notable compositional changes. Based on experimental data and literature, a multidimensional database of thermal runaway parameters is developed, incorporating metrics such as gas explosiveness, toxicity, and heat of combustion. Three classical multi-criteria evaluation methods—Technique for Order Preference by Similarity to Ideal Solution, Principal Component Analysis, and a median-based approach—are applied and compared. To address limitations arising from dimensional and variance scale differences among parameters, an expected contribution method is proposed to enable balanced and consistent scoring. Results demonstrate that this method enhances fairness and interpretability, particularly in scenarios with substantial scale disparities among variables arising from cross-battery systems. This work establishes a quantitative safety assessment framework that enables cross-platform comparisons and provides guidance for battery system design, risk zoning, and thermal mitigation strategies. The framework is broadly applicable to emerging battery chemistries and advances battery safety evaluation across diverse application environments.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100475"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145045875","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}