Etransportation最新文献

{"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":"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}

{"title":"Impact of shutdown operations on the recovery of reversible degradation in proton exchange membrane fuel cells","authors":"Ruitao Li ,&nbsp;Julong Zhou ,&nbsp;Naiyuan Yao ,&nbsp;Yuhan Zhou ,&nbsp;Weikang Lin ,&nbsp;Zishun Xu ,&nbsp;Jianbin Su ,&nbsp;Lei Shi ,&nbsp;Tiancai Ma","doi":"10.1016/j.etran.2025.100468","DOIUrl":"10.1016/j.etran.2025.100468","url":null,"abstract":"<div><div>In proton exchange membrane fuel cells, partial performance loss accumulated during long-term operation can be recovered through optimized operation or shutdown, a process known as reversible degradation. However, most existing studies focus on small-scale single cells and laboratory-scale test conditions, without adequately considering the constraints inherent to practical system-level operation. Therefore, investigating the influence of practically adjustable shutdown parameters on recovery effectiveness is crucial. Moreover, large-scale stacks exhibit spatial heterogeneity in degradation and recovery, both across cell positions and within individual cells. This heterogeneity plays a key role in identifying reversible degradation and formulating recovery strategies. In this study, accelerated stress tests were conducted on a full-size short stack under New European Driving Cycle conditions. Experimental variables included shutdown temperature, operating temperature, and purging methods, to evaluate their effects on recovery. Changes in stack consistency and electrochemically active surface area before and after recovery were analyzed. Results indicate that moderate retention of condensed water promotes ionomer rehydration and performance recovery, while uneven water distribution leads to spatial differences in recovery. Inter-cell and in-plane inconsistencies increase with current density, with voltage deviations exceeding 40 mV between cells and 20 mV within cells at 594 A. The outlet region exhibited weaker recovery consistency and greater sensitivity to load fluctuations, with response amplification reaching approximately 300 %. Cooling measures during recovery improved both steady-state performance and dynamic response. This work provides important insights into the optimization of shutdown parameters and spatial performance variation in large PEMFC stacks, supporting the development of improved operational strategies to enhance durability and efficiency in practical applications.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100468"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019421","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 state-of-the-art review on eVTOL thermal management: system architectures, key components and emerging technologies","authors":"Zhe Li ,&nbsp;Peng Xie ,&nbsp;Cheng Lin ,&nbsp;Guoyu Liu","doi":"10.1016/j.etran.2025.100480","DOIUrl":"10.1016/j.etran.2025.100480","url":null,"abstract":"<div><div>Electric vertical takeoff and landing aircraft (eVTOL) represent a transformative solution for modern transportation, offering high speed, low noise, and operational flexibility. However, the performance of their powertrains is highly temperature-sensitive, and their operating scenarios and mission profiles differ significantly from those of ground-based electric vehicles (EVs). In addition, cabin thermal regulation significantly affects energy consumption, thereby influencing the flight range. Consequently, an efficient thermal management system (TMS) is essential for eVTOL applications. This paper first reviews eVTOL powertrain architectures, followed by a systematic examination of the corresponding TMS architectures, including their operating principles, characteristics, and limitations. The thermal management requirements of key powertrain components are then analyzed, along with the review of relevant thermal management technologies. Moreover, emerging technologies applicable to eVTOLs are discussed, with an emphasis on their potential to enhance system performance. Finally, current research gaps are identified, and directions for future investigation are proposed. To the best of our knowledge, this is the first dedicated review of thermal management technologies for eVTOLs, aiming to clarify the state of the art, identify existing challenges, and provide valuable insights for researchers and industry practitioners.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100480"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096103","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-level passive-active thermal control for battery thermal runaway prevention and suppression in electric vehicles","authors":"Jiekai Xie ,&nbsp;Junlin Li ,&nbsp;Canbing Li ,&nbsp;Xinyan Huang ,&nbsp;Guoqing Zhang ,&nbsp;Xiaoqing Yang","doi":"10.1016/j.etran.2025.100467","DOIUrl":"10.1016/j.etran.2025.100467","url":null,"abstract":"<div><div>Resolving the contradiction between heat-dissipation during normal operation and thermal-insulation after thermal runaway (TR) is highly desirable for battery thermal safety system but remains challenges. Herein, a multi-leveled thermal control strategy, <em>i.e.</em>, passive cooling - active cooling - passive suppression - active suppression, has been proposed for TR prevention-suppression of the battery packs. The system is primarily designed by modular composite phase change material (CPCM), liquid cooling (LC) plates and aerogel plates (APs). Firstly, the passive cooling CPCM coordinated with active LC enables a suitable working temperature, low temperature gradient and low energy consumption of the battery pack under variable environments. Secondly, the modular design of the battery pack couples with the passive thermal-insulation effect of APs, successfully preventing TR from propagating to other modules. Thirdly, APs work synergistically with dynamic LC, greatly enhancing the directional heat-dissipation, and consequently, the TR propagation can be suppressed to the lowest level. By the flexible dynamic flow rate adjustment, the TR of large-scaled battery packs with different configurations of 4S12P, 6S8P, 8S6P and 12S4P can be successfully suppressed in the initially-triggered cell.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100467"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019420","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":"State-of-charge estimation over full battery lifespan under diverse fast-charging protocols: A lightweight base-error joint modeling framework","authors":"Ganglin Cao ,&nbsp;Shouxuan Chen ,&nbsp;Yuanfei Geng ,&nbsp;Shuzhi Zhang ,&nbsp;Yao Jia ,&nbsp;Rong Feng ,&nbsp;Yongjun Liu","doi":"10.1016/j.etran.2025.100474","DOIUrl":"10.1016/j.etran.2025.100474","url":null,"abstract":"<div><div>Accurate state-of-charge (SOC) online estimation during various multi-stage constant current (MCC) fast-charging protocols over battery entire lifespan holds significant importance. In this work, we develop a lightweight-training oriented data-driven base-error joint modeling framework to fill this research gap. Through deep learning-based initial-cycle data training and lightweight machine learning-based typical-cycle data training, we only extract approximately 1 % of whole battery data for data-driven base-error joint modeling. With consideration of SOC time-dependency, short-term Ampere-hour is further combined via a simple filter structure to guarantee final SOC estimation accuracy. The validation, derived from a public battery degradation dataset comprising 8 different MCC fast-charging protocols from 46 cells, demonstrates that our framework allows rapid data-driven base-error joint modeling with training time only about l min, where both average mean absolute error and average root mean square error of SOC estimation during various MCC fast-charging protocols over battery entire lifespan are roughly below 0.3 %. Our work, for the first time, reveals the possibility of joint data-driven model trained via extremely few data on accurate SOC online estimation with consideration of various MCC fast-charging protocols and battery degradation status, and also offers a pretty concise but efficient solution for multi-scenario battery aging diagnosis and voltage dynamics forecast. The code accompanying this work is available at <span><span>https://github.com/szzhang96/A-light-weighted-training-oriented-data-driven-base-error-joint-modeling-method-for-SOC-estimation</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100474"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010679","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":"Breaking the voltage plateau barrier: Slope-adaptive state-of-charge estimation for LFP batteries with temperature-aware hysteresis modeling","authors":"Lisen Yan ,&nbsp;Jun Peng ,&nbsp;Heng Li ,&nbsp;Zhiwu Huang ,&nbsp;Dirk Uwe Sauer ,&nbsp;Weihan Li","doi":"10.1016/j.etran.2025.100473","DOIUrl":"10.1016/j.etran.2025.100473","url":null,"abstract":"<div><div>The open-circuit voltage (OCV) hysteresis effect significantly complicates state-of-charge (SOC) estimation of <span><math><msub><mrow><mtext>LiFePO</mtext></mrow><mrow><mtext>4</mtext></mrow></msub></math></span> batteries. While prior research has focused on major-loop hysteresis between full charge and discharge, accurately modeling minor-loop hysteresis during partial charge/discharge remains a persistent challenge. This paper proposes a data-driven hysteresis model that incorporates historical SOC and temperature data, with which an adaptive SOC estimator is designed to accommodate slope variations in minor-loop hysteresis. The proposed model accurately captures complex voltage hysteresis across different charge/discharge paths and temperature conditions using deep long short-term memory neural networks trained on hysteresis test data. This OCV component is integrated into a second-order equivalent circuit model, achieving both high-precision battery modeling and computational efficiency. The model parameters are optimized effectively using a multistep parameter identification method enhanced by a meta-heuristic algorithm. The proposed SOC estimator dynamically adjusts its covariance matrices in response to voltage slope variations during the plateau, improving Kalman gain matching to eliminate cumulative errors and enhance accuracy. Extensive experimental results show that over 95% of samples achieve a mean absolute error of less than 0.56% across various usage scenarios. The proposed method outperforms two state-of-the-art methods by 46.2% and 45.7% in root mean square error, demonstrating fast convergence and robust estimation even within the voltage plateau.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100473"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219600","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":"Dynamic flight challenges in PEMFC-powered UAVs: Towards intelligent management and sustainable propulsion","authors":"Xikai Tu ,&nbsp;Jin Wu ,&nbsp;Zhiming Tao ,&nbsp;Chang Wen ,&nbsp;Zhengkai Tu","doi":"10.1016/j.etran.2025.100506","DOIUrl":"10.1016/j.etran.2025.100506","url":null,"abstract":"<div><div>Proton exchange membrane fuel cell (PEMFC)-powered unmanned aerial vehicles (UAVs) exhibit nonlinear and coupled behavior under dynamic flight conditions. To enable intelligent management, this study proposes an adaptive air stoichiometric ratio (ASR) strategy that dynamically responds to real-time variations in payload and acceleration. Although ASR optimization has been studied under steady-state conditions, its regulation under realistic UAV dynamics remains underexplored and experimentally unverified. We develop a coupled framework integrating UAV flight dynamics, an air-cooled PEMFC model, and mass–heat transfer multiphysics, and validate it through dynamic flight tests. Results show that optimal ASR varies significantly with operating conditions: with a 40 kg payload, ASR increases from 52 to 81 as acceleration changes from −0.6 to 0.6 m/s²; at 0.6 m/s², raising the payload from 25 to 40 kg increases ASR from 24 to 81. Optimal ASR regulation improves stack voltage by 0.170 V, reduces hydrogen consumption by 2.05 mg per 100 m of flight, lowers temperature by 18.32 %, and enhances efficiency, voltage uniformity, and temperature uniformity. Notably, ASR exhibits a nonlinear influence on performance: it improves markedly from 25 to 28 kg, remains stable between 28 and 31 kg, and rises again at 40 kg. Experimental validation (error &lt;1.1 %) confirms model accuracy and demonstrates the effectiveness of ASR optimization in PEMFC-powered UAVs. Beyond UAV applications, the proposed adaptive ASR strategy offers a pathway toward intelligent air management in fuel-cell propulsion systems, with direct relevance to emerging electric transportation modes such as urban air mobility vehicles, cargo drones, and hybrid-electric aircraft.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"26 ","pages":"Article 100506"},"PeriodicalIF":17.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416082","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}