Etransportation最新文献

{"title":"Oxygen invasion behavior of anodic porous transport layer in polymer electrolyte membrane water electrolyzer: lattice Boltzmann method simulation","authors":"Chenyang Xu,&nbsp;Jian Wang,&nbsp;Jianzhong Wang,&nbsp;Kun Yang,&nbsp;Wenbin Gao,&nbsp;Hao Wang","doi":"10.1016/j.etran.2024.100365","DOIUrl":"10.1016/j.etran.2024.100365","url":null,"abstract":"<div><div>The anode porous transport layer (PTL) is an important transport component of water and oxygen in polymer electrolyte membrane water electrolyzer (PEMWE), which plays a key role in the efficiency of hydrogen production. The three-dimensional (3D) pore structure of commercial sintered titanium (Ti) PTL is characterized by micro computed tomography (μ-CT). A 3D multiphase flow model of PTL is established based on lattice Boltzmann method (LBM). The influence mechanism of porosity, pore size, and thickness on oxygen invasion behavior in PTLs are systematically studied. The result shows that in commercial sintered Ti PTL, the growth rate of oxygen saturation decreases with transport process. When the porosity ranges from 20 % to 40 %, the dynamic transport of oxygen within the PTL exhibits a clear fingering behavior. When the porosity is 50 % and 60 %, the oxygen invasion rate in PTL is significantly accelerated. In addition, when the pore sizes are 3 and 6 μm, the transport process of oxygen is significantly hindered. The oxygen saturation curves with a pore size of 20 and 30 μm present the \"W\" form, which indicates that the local small pore throat structure will hinder the removal of oxygen. When the thickness is between 200 and 300 μm, the oxygen invasion process is hindered as the transport distance increases. The pore scale analysis of PTL structure optimization design provides a reference for the development of high-performance PEMWE.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"24 ","pages":"Article 100365"},"PeriodicalIF":15.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143923017","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":"Redox-active stabilizer-enhanced structural and thermal stability of Ni-rich cathodes via an economical blending strategy","authors":"Jinzhong Liu ,&nbsp;Jinyang Dong ,&nbsp;Meng Wang ,&nbsp;Na Liu ,&nbsp;Haoyu Wang ,&nbsp;Kang Yan ,&nbsp;Hongyun Zhang ,&nbsp;Xi Wang ,&nbsp;Rui Tang ,&nbsp;Yun Lu ,&nbsp;Qiongqiong Qi ,&nbsp;Yuefeng Su ,&nbsp;Feng Wu ,&nbsp;Lai Chen","doi":"10.1016/j.etran.2025.100428","DOIUrl":"10.1016/j.etran.2025.100428","url":null,"abstract":"<div><div>With the increasing demand for high-energy-density lithium-ion batteries, enhancing the structural and thermal stability of nickel-rich cathode materials has become imperative for fulfilling the performance prerequisites for diverse applications. Nevertheless, nickel-rich cathodes frequently experience structural deterioration and thermal instability, particularly during high-voltage cycling. To address these obstacles, we propose an innovative and economically viable blending strategy by incorporating 10 wt% lithium iron phosphate (LiFePO₄, LFP) as a “redox-active stabilizer” into layered NCM811. LFP, characterized by its robust phosphorus-oxygen covalent bonds, augments the structural and thermal stability of NCM811, while preserving high energy density and alleviating mechanical strain during cycling. The NCM-10 %LFP blended cathode exhibited outstanding electrochemical performance, attaining capacity retention of 65.1 % at 0.2C and 71.2 % at 1C after 200 cycles. Furthermore, the thermal stability of the blended cathode is markedly enhanced, with the initiation temperature of thermal runaway postponed. This investigation provides novel perspectives on the interfacial interactions between LFP and NCM811 and presents a scalable, cost-effective solution for the development of high-performance cathode materials with increased safety and durability for advanced lithium-ion batteries.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"24 ","pages":"Article 100428"},"PeriodicalIF":15.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143902248","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":"Characteristics and generation mechanism of ejecta-induced arc for lithium-ion battery during thermal runaway","authors":"Yue Zhang ,&nbsp;Ping Ping ,&nbsp;Xiantong Ren ,&nbsp;Wei Gao ,&nbsp;Depeng Kong ,&nbsp;Xiaokang Yin","doi":"10.1016/j.etran.2025.100429","DOIUrl":"10.1016/j.etran.2025.100429","url":null,"abstract":"<div><div>As the widespread adoption of lithium-ion battery, the incidence of electrical faults is on the rise. While arc faults are commonly associated with loose connectors or damaged insulation, their potential initiation during battery ejection represents a significant and unaddressed research gap in the field of battery safety. In this study, the battery was heated to venting to investigate the characteristics and mechanism of ejecta-induced arc. The results show that the arc can be induced at voltage of 50 V and above under 3 mm and 5 mm electrode spacing, while the critical voltage ranges from 200 V to 400 V at 7 mm spacing. The number of arc events increase if the ejected pieces stuck on the electrode surface since it is equivalent to reduce the electrode spacing. Through the analysis of the electrical characteristics of each arc, three distinct arcing modes are identified: particles dominant, pieces dominant, and combination. Based on the measured resistivity of battery ejecta and resistance estimation of particles dominant arc, the pieces play a more important role than particles in the initiation of ejecta-induced arc. Furthermore, the safety boundary against ejecta-induced arc is proposed based on the critical electric field strength, and the safe electrode spacings for typical voltage of 400 V, 800 V, and 1500 V are 9.9 mm, 14.0 mm, and 19.2 mm, respectively. The results are expected to provide valuable guidance in safety design of lithium-ion battery systems.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"24 ","pages":"Article 100429"},"PeriodicalIF":15.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143903502","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":"Corrigendum to “Towards integrated thermal management systems in battery electric vehicles: A review” [eTransportation 24 (2025) 100396]","authors":"Xiaoya Li,&nbsp;Ruzhu Wang","doi":"10.1016/j.etran.2025.100413","DOIUrl":"10.1016/j.etran.2025.100413","url":null,"abstract":"","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"24 ","pages":"Article 100413"},"PeriodicalIF":15.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143923018","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":"Comprehensive performance analysis of electric vehicle advanced cabin moisture-thermal coupling management control strategies based on transcritical CO2 cycle","authors":"Anci Wang ,&nbsp;Qiang Li ,&nbsp;Dinghua Hu ,&nbsp;Fan Jia ,&nbsp;Xiang Yin ,&nbsp;Feng Cao","doi":"10.1016/j.etran.2025.100423","DOIUrl":"10.1016/j.etran.2025.100423","url":null,"abstract":"<div><div>The development of an advanced cabin moisture-thermal coupling management system, along with its operation dynamic control strategy, is essential for ensuring passenger comfort, driving safety, and the driving range of electric vehicles. Based on the transcritical CO₂ cycle, an independent thermal management (ITM) system and two (the single-stage throttling (SST) and double-stage throttling (DST)) moisture-thermal coupling management systems are proposed. First, an anti-fog evaluation standard is established, and regions with different controls are defined across the winter operating conditions. Subsequently, the thermodynamic characteristics are analyzed, the SST moisture-thermal coupling management cycle features an optimal discharge pressure that minimizes both power consumption and cabin humidity. In contrast, the cabin humidity in the DST cycle is regulated by intermediate pressure, which has both upper and lower limits. The optimal discharge pressure increases, while the minimum intermediate pressure decreases with ambient temperature. Furthermore, a performance comparison of two moisture-thermal coupling management cycles is conducted. From a moisture management perspective, the SST cycle's moisture extraction rate and specific moisture extraction rate are significantly improved by 7 and 12.5 times, respectively. However, the DST cycle's COP is superior. Given that passenger comfort and driving safety take precedence over energy efficiency, the SST cycle is deemed the more suitable choice. Lastly, the dynamic response characteristics of the SST cycle are investigated using the WLTC. Moreover, the impact of the SST cycle on the driving range is analyzed. The winter driving range of the SST cycle is slightly lower compared to the ITM cycle, but it increases by approximately 5.17 % compared to the traditional PTC thermal management system. This study provides valuable insights into the dynamic characteristics of efficient cabin energy management systems in electric vehicles and introduces a novel approach for multi-objective coupling control during winter driving.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"25 ","pages":"Article 100423"},"PeriodicalIF":15.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068161","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-physics simulation and risk analysis of internal thermal runaway propagation in lithium-ion batteries","authors":"Yan Ding ,&nbsp;Li Lu ,&nbsp;Huangwei Zhang","doi":"10.1016/j.etran.2025.100427","DOIUrl":"10.1016/j.etran.2025.100427","url":null,"abstract":"<div><div>This study investigates internal thermal runaway propagation (TRP) mechanism in lithium-ion batteries (LIBs) triggered by hotspots, focusing on the TRP dynamics and thermal interactions between internal short circuits (ISC) and side reactions within the TRP front. An integrated electrical-electrochemical-thermal-chemical model, incorporating a novel ISC model, is developed within the in-house <strong><em>BatteryFOAM</em></strong> solver to simulate global thermal runaway initiation and TRP behaviors. A new TRP front multi-zone model is built to analyze the coupling between heat conduction, ISC-driven ignition, and side reactions. The results show that the TRP occurs when the separator melt failure temperature (<span><math><mrow><msub><mi>T</mi><mrow><mi>s</mi><mi>e</mi><mi>p</mi></mrow></msub></mrow></math></span>) is reached before the maximum temperature gradient, allowing ISC Joule heating to maintain a high temperature gradient propagating from the hotspot to the normal zone. Therefore, a first-ever dimensionless risk coefficient (<span><math><mrow><mi>f</mi></mrow></math></span>) is introduced to quantify the balance between heat generation and dissipation, identifying high-risk TRP fronts where <span><math><mrow><mi>f</mi></mrow></math></span> ranges from 1 to 1e5, with cathode reactions and electrolyte decomposition dominating TRP acceleration. Model validation against the experiments confirms the predictive accuracy. Simulations demonstrate a TRP velocity of 7.5 mm/s, a width of 2.8 mm, and a maximum temperature of 690 K. Notably, the TRP velocity is, for the first time, revealed to be correlated with the square root of the thermal diffusivity, and an equation linking velocity with <span><math><mrow><msub><mi>T</mi><mrow><mi>s</mi><mi>e</mi><mi>p</mi></mrow></msub></mrow></math></span> is derived to guide LIB safety implementations. This study provides quantitative insights for designing safer LIBs, particularly in electric vehicles and large-scale energy storage.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"24 ","pages":"Article 100427"},"PeriodicalIF":15.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143873955","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 digitized electrochemical power source for electric vehicles","authors":"Jiangong Zhu ,&nbsp;Wentao Xu ,&nbsp;Siyi Tao ,&nbsp;Jixiang Cai ,&nbsp;Yudong Shen ,&nbsp;Mengshu Tian ,&nbsp;Yi Jiang ,&nbsp;Bo Jiang ,&nbsp;Xueyuan Wang ,&nbsp;Wolfgang Schade ,&nbsp;Xuezhe Wei ,&nbsp;Haifeng Dai","doi":"10.1016/j.etran.2025.100426","DOIUrl":"10.1016/j.etran.2025.100426","url":null,"abstract":"<div><div>Electrochemical power sources play a critical role in electric vehicles (EVs) for green transportation. The intrinsic reaction mechanisms, and multiphysics and multiscale characteristics of electrochemical power sources result in strong nonlinearity, time variation, and spatial distribution during operation, which presents challenges to reliable management. This review takes the lithium-ion batteries as the object, by reviewing the state-of-the-art studies and development trends from aspects of modeling, measurement, and management, summarizing that the developments of multiphysics and multiscale models are necessary for advanced battery design, measurement parameter design, and control strategy design; high precision and multi-dimensional parameter measurements are trending to be deployed on board by utilizing on-board sensors; local management moves towards the integration of local and cloud-based management based on high-performance computing and long-term storage for battery data throughout the battery whole life cycle. To integrate the development of advanced technologies on the EV power source systems, therefore, the architecture of a digitized electrochemical power source including modeling, digital measurement, and management is proposed, which together forms a pathway towards the stability and reliability requirements of lithium-ion batteries facilitating the development of electrochemical power source application scenarios, e.g., EVs and energy storage systems.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"24 ","pages":"Article 100426"},"PeriodicalIF":15.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143882560","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":"Performance investigation of the cascade heat pump system with waste heat recovery for electric vehicle thermal management systems on energy, economic and environmental impact","authors":"Hongseok Choi ,&nbsp;Jaehyun Song ,&nbsp;Sangwook Lee ,&nbsp;Yongjoo Jun ,&nbsp;Hoseong Lee","doi":"10.1016/j.etran.2025.100422","DOIUrl":"10.1016/j.etran.2025.100422","url":null,"abstract":"<div><div>This study addresses the inefficiencies of traditional EV thermal management systems that use a single compressor for both battery and cabin thermal needs. This configuration often results in inefficient energy utilization due to the differing thermal demands of the battery and cabin. To address these challenges, a cascade heat pump system was proposed, featuring two compressors and two independent refrigerant cycles to manage battery and cabin thermal loads separately. Additionally, the system reutilized waste heat for cabin heating under winter conditions. A simulation model, validated with experimental data, was developed to evaluate energy consumption under various scenarios, including diverse charging conditions and driving cycles. The results demonstrated that the cascade system significantly reduced energy consumption compared to conventional single-compressor systems. During battery charging, adaptive compressor control based on temperature achieved an average energy reduction of 50.2 % in summer and 25.9 % in winter. During electric vehicle operation, the cascade system consistently reduced total energy consumption across all driving cycles, improving driving range efficiency from 4.33 to 6.15 km/kWh under summer NEDC conditions. Over a 10-year period, the reduced energy consumption translated to a 16.6 % economic benefit and a 23.6 % reduction in CO₂ emissions. These findings highlight the cascade heat pump system's ability to optimize energy usage in both summer and winter, offering enhanced economic and environmental benefits for electric vehicles.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"24 ","pages":"Article 100422"},"PeriodicalIF":15.0,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143859201","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":"Representative battery load profile synthesis leveraging multi-objective optimization heuristics","authors":"Konrad Katzschke ,&nbsp;Tamás Kurczveil ,&nbsp;Andreas Rausch","doi":"10.1016/j.etran.2025.100419","DOIUrl":"10.1016/j.etran.2025.100419","url":null,"abstract":"<div><div>Automotive high-voltage batteries show distinct reactions depending on their concurrent states of demanded power, temperature and <span><math><mrow><mi>S</mi><mi>o</mi><mi>C</mi></mrow></math></span>. To aid development, representative load profiles are frequently derived. Besides velocity-based cycles, literature also proposes the generation of electrical power trajectories. However, current methods fail to represent simultaneous thermo-electrical usage dynamics. Moreover, fitness functions based on highly aggregated parameters do not account for complex battery dynamics. This work presents a methodology to synthesize coupled <span><math><mi>P</mi></math></span>, <span><math><mi>T</mi></math></span>, and <span><math><mrow><mi>S</mi><mi>o</mi><mi>C</mi></mrow></math></span> trajectories. First, MCMC simulation derives an optimal <span><math><mrow><mi>S</mi><mi>o</mi><mi>C</mi></mrow></math></span> discharge stroke chain. Next, multiple stroke realizations are obtained by concatenating sequentially constrained micro-trips. A genetic algorithm then discovers feasible solutions to the related combinatorial optimization problem. Representativity is measured using the earth mover’s distance between signal distributions. Final profiles are selected from a Pareto front, allowing for the prioritization of Markov- or signal-related fitness. We conclude that applying the scale reduction factor with a threshold of <span><math><mrow><mover><mrow><mi>R</mi></mrow><mrow><mo>ˆ</mo></mrow></mover><mo>≤</mo><mn>1</mn><mo>.</mo><mn>01</mn></mrow></math></span> yields suitable length estimations of <span><math><mrow><mi>S</mi><mi>o</mi><mi>C</mi></mrow></math></span> stroke chains. The general introduction of an optimization step enables mean fitness improvement of up to <span><math><mrow><mn>40</mn><mspace></mspace><mstyle><mtext>%</mtext></mstyle></mrow></math></span> compared to sole MCMC sampling. 1D and 2D error function designs yield similar average fitness, while the latter demonstrates to deliver a broader solution variety. Our framework serves as a versatile base for individual battery applications.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"24 ","pages":"Article 100419"},"PeriodicalIF":15.0,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855705","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":"Deep learning-based inverse prediction of side pole collision conditions of electric vehicle","authors":"Chenghao Ma,&nbsp;Ziao Zhuang,&nbsp;Bobin Xing,&nbsp;Yong Xia,&nbsp;Qing Zhou","doi":"10.1016/j.etran.2025.100421","DOIUrl":"10.1016/j.etran.2025.100421","url":null,"abstract":"<div><div>To improve safety of electric vehicles under side pole collisions, accident reconstruction and failure risk prediction on battery cell are essential. Accident reconstruction and analysis is complex due to structural nonlinearities and vehicle rotation during collision. Such task becomes more challenging due to the ill-posedness of this inverse problem. This study proposed a deep-learning based method to inversely predict the collision conditions when only the deformation of battery pack exterior structure is available. Battery cell deformation was also predicted to assess the accident severity. To build the dataset, a large number of finite element simulations were run at pack level. Compared to the comprehensive coverage of collision condition domain, the collision response domain inevitably exhibits poor filling, leading to non-uniqueness in inverse prediction. To address this, the model was trained with pre- and post-collision images of the side structure. A convolutional neural network integrated with residual network (ResNet) was applied to improve model performance. The amount of input feature information and the network structure were thoroughly discussed. The model also demonstrated good interpretability and robustness, maintaining stable performance with added noise. This proposed approach would become an effective tool for analyzing collision scenarios where limited information is available.</div></div>","PeriodicalId":36355,"journal":{"name":"Etransportation","volume":"24 ","pages":"Article 100421"},"PeriodicalIF":15.0,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838496","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}