Etransportation最新文献_第3页

Optimal economic integrated thermal management of battery and cabin for connected electric vehicles considering battery degradation 考虑电池退化的网联电动汽车电池与驾驶室综合热管理经济优化

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 Epub Date: 2025-12-31 DOI: 10.1016/j.etran.2025.100540

Qian Ma , Yan Ma , Jinwu Gao , Hong Chen

The integrated thermal management system (ITMS) for the battery and cabin is essential to improve thermal safety, energy efficiency, battery lifespan, and passenger comfort in connected electric vehicle (CEV). The ITMS consumes considerable energy to maintain battery and cabin temperatures in the optimal range, which severely reduces the CEV’s driving range. To solve the ITMS optimization problem for CEV and achieve eco-cooling, this article proposes a two-stage optimization strategy for ITMS based on multi-horizon economic nonlinear model predictive control (TS-MH-ENMPC), which considers the total economic cost of cooling system energy consumption and battery degradation. Firstly, a control-oriented nonlinear ITMS model is developed to predict the battery and cabin temperature changes. Then, a two-stage cooling optimization strategy based on economic nonlinear model predictive control (MPC) is proposed to achieve optimal driving economy, which divides the ITMS into fast cooling stage and temperature maintenance stage with different cooling objectives. Finally, to address the multi-timescale problem of slow dynamic response in thermal system and fast response in power transfer, a multi-prediction horizon MPC framework is introduced to fully utilize the intelligent transportation system (ITS) information to achieve optimal economic performance over long prediction horizon, which solves the optimization problem of the integrated system with dynamic responses at different time scales and reduces the computational burden. The simulation results under various conditions show that the proposed method reduces the total economic cost of energy consumption and battery degradation. And a sensitivity analysis is conducted on ambient temperatures, battery prices, and electricity prices. Compared to the traditional MPC, rule-based, the total economic cost of the TS-MH-ENMPC is reduced by 5.24% and 7.09%, and the driving distance is increased by 3.03% and 6.65%. The co-simulation results on real-world traffic data show that the proposed method improves driving economy and thermal performance under preview information uncertainty and model mismatch.

用于电池和驾驶室的集成热管理系统（ITMS）对于提高互联电动汽车（CEV）的热安全性、能效、电池寿命和乘客舒适度至关重要。ITMS消耗了大量的能量来保持电池和座舱温度在最佳范围内，这严重降低了CEV的行驶里程。为了解决电动汽车ITMS优化问题，实现生态冷却，本文提出了一种考虑冷却系统能耗和电池退化总经济成本的基于多水平经济非线性模型预测控制（TS-MH-ENMPC）的两阶段ITMS优化策略。首先，建立了面向控制的非线性ITMS模型来预测电池和舱室温度的变化。然后，提出了一种基于经济非线性模型预测控制（MPC）的两阶段冷却优化策略，将ITMS分为快速冷却阶段和温度维持阶段，并根据不同的冷却目标实现最优的驾驶经济性。最后，针对热力系统动态响应慢、输电系统动态响应快的多时间尺度问题，引入多预测层MPC框架，充分利用智能交通系统（ITS）信息实现长预测层的最优经济性能，解决了不同时间尺度下综合系统动态响应的优化问题，减少了计算量。各种条件下的仿真结果表明，该方法降低了能量消耗和电池退化的总经济成本。并对环境温度、电池价格、电价进行敏感性分析。与基于规则的传统MPC相比，TS-MH-ENMPC的总经济成本分别降低了5.24%和7.09%，行驶距离分别增加了3.03%和6.65%。实际交通数据的联合仿真结果表明，该方法在预览信息不确定和模型不匹配的情况下提高了驾驶经济性和热性能。

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引用次数: 0

Optimization of pulsating spray cooling for enhanced air-cooled radiator performance in fuel cell vehicles: An experimental and RSM study 优化脉动喷雾冷却以提高燃料电池汽车风冷散热器性能：实验和RSM研究

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 Epub Date: 2025-11-26 DOI: 10.1016/j.etran.2025.100517

Rajendran Prabakaran, M Mohamed Souby, Sung Chul Kim

This study proposes a pulsating spray cooling (PSC) to enhance the performance of an air-cooled radiator (ACR) in a fuel cell vehicle (FCV). It explores the influence of duty cycle (DC) on heat dissipation and spray performance using both experimental methods and response surface methodology (RSM). Results revealed that employing PSC with a lower DC (<40 %) caused greater fluctuations in both heat dissipation and coolant outlet temperature, indicating it is unsuitable for ACR. Conversely, non-optimized PSC with an 80 % DC demonstrated performance comparable to continuous spray cooling, achieving up to 75.5 % enhancement in heat dissipation compared to air cooling. Furthermore, spray efficiency increased from 8.4 % to 53.5 % as the DC decreased from 100 % to 20 %. In addition, spray pump power and water consumption were significantly reduced by up to 80 %. Importantly, the threshold limit of spray flow rate was experimentally determined to be 0.60 L/min. RSM optimization was then conducted to identify the optimal PSC conditions that balance thermal and spray performance. Spray flow rate, interval, and pulse duration were selected for optimization due to their key influence on heat dissipation, water use, and pump power in PSC system. The optimal conditions obtained were a spray flow rate of 0.522 L/min, a spray interval of 56.72 s, and a continuous spray duration of 10 s. Under these optimized conditions, the PSC-coupled ACR achieved a heat dissipation rate of 5.47 kW, a spray efficiency of 46.89 %, spray pump power of 2.62 W, and water consumption of 5.25 L/h. Moreover, the optimized water consumption was within the theoretical water production capacity (up to 10.6 L/h) of a real PEM-FC vehicle (up to 295 kW). Thus, the proposed PSC approach offers a promising solution for enhancing stack cooling performance using available water resources from the fuel cell itself, making it a viable option for future FCVs.

为了提高燃料电池汽车（FCV）气冷散热器（ACR）的性能，提出了脉动喷雾冷却（PSC）技术。它探讨了占空比（DC）对散热和喷雾性能的影响，采用实验方法和响应面方法（RSM）。结果表明，采用较低DC （< 40%）的PSC会引起更大的散热和冷却剂出口温度波动，表明不适合ACR。相反，非优化的80% DC的PSC表现出与连续喷雾冷却相当的性能，与空气冷却相比，散热能力提高了75.5%。此外，当DC从100%降低到20%时，喷雾效率从8.4%提高到53.5%。此外，喷雾泵的功率和用水量显著降低高达80%。重要的是，实验确定了喷雾流量的阈值限制为0.60 L/min。然后进行RSM优化，以确定平衡热和喷涂性能的最佳PSC条件。由于喷雾流量、间隔和脉冲持续时间对PSC系统的散热、用水和泵功率有关键影响，因此选择了喷雾流量、间隔和脉冲持续时间进行优化。得到的最佳条件为喷雾流量0.522 L/min，喷雾间隔56.72 s，连续喷雾时间10 s。在此优化条件下，psc耦合ACR的散热率为5.47 kW，喷雾效率为46.89%，喷雾泵功率为2.62 W，耗水量为5.25 L/h。此外，优化后的用水量在实际PEM-FC车辆（最高295 kW）的理论产水能力（最高10.6 L/h）范围内。因此，所提出的PSC方法提供了一个很有前途的解决方案，可以利用燃料电池本身的可用水资源来提高堆冷却性能，使其成为未来燃料电池汽车的可行选择。

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引用次数: 0

Towards intelligent online diagnosis and degradation prognostics of lithium-ion batteries: A mechanism–data fusion approach 迈向锂离子电池的智能在线诊断和退化预测：一种机制-数据融合方法

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 Epub Date: 2025-11-28 DOI: 10.1016/j.etran.2025.100513

Shilong Guo , Yaxuan Wang , Lei Zhao , Junfu Li , Zhenbo Wang

Lithium-ion batteries experience complex degradation governed by multiple interacting mechanisms, posing challenges for real-time aging-mode identification. To overcome this issue, we propose a mechanism–data fusion framework that couples an extended single-particle model (SPM) with a multi-task learning (MTL) architecture. The electrochemical model explicitly incorporates solid–electrolyte interphase (SEI) growth and lithium plating side reactions, and employs a multi-swarm cooperative adaptive particle swarm optimization (MSCPSO) algorithm to achieve accurate parameter identification across different temperatures and C-rates. A three-branch MTL framework is then constructed to jointly predict key degradation indicators—including the loss of lithium inventory (LLI), loss of active material (LAM), SEI and plating layer thicknesses, and plating-induced capacity loss—while also classifying the occurrence of lithium plating. Experimental validation demonstrates strong physical consistency and robustness of the proposed framework under various operating conditions. Among the tested architectures, the MT-LSTM model exhibits the best overall performance, achieving a lithium-plating detection accuracy of 99.63 % and an R² exceeding 0.97 for multi-target regression tasks. This unified and scalable framework enables quantitative identification of multiple degradation mechanisms directly from charge–discharge data, offering a practical, real-time, and physically interpretable tool for next-generation battery health management systems.

锂离子电池的老化过程是由多种相互作用机制控制的，这给实时老化模式识别带来了挑战。为了克服这一问题，我们提出了一种机制-数据融合框架，该框架将扩展单粒子模型（SPM）与多任务学习（MTL）架构相结合。该电化学模型明确地考虑了固电解质间相（SEI）生长和镀锂副反应，并采用多群协同自适应粒子群优化（MSCPSO）算法实现了在不同温度和c -速率下的准确参数识别。然后构建了一个三分支MTL框架，共同预测关键降解指标，包括锂库存损失（LLI）、活性物质损失（LAM）、SEI和镀层厚度，以及镀引起的容量损失，同时对锂镀的发生进行分类。实验验证表明，该框架在各种操作条件下具有较强的物理一致性和鲁棒性。在测试的体系结构中，MT-LSTM模型表现出最佳的综合性能，在多目标回归任务中，其镀锂检测准确率达到99.63%，R2超过0.97。这种统一且可扩展的框架可以直接从充放电数据中定量识别多种退化机制，为下一代电池健康管理系统提供实用、实时和物理可解释的工具。

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引用次数: 0

Unveiling thermal risks of presumed safe lithium iron phosphate batteries 揭示假定安全的磷酸铁锂电池的热风险

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 Epub Date: 2025-12-24 DOI: 10.1016/j.etran.2025.100531

Dian Zhang , Kai Chen , Xin Shen , Tao Wang , Yuan Ma , Yiren Zhong , Xuning Feng , Yuping Wu , Xin-Bing Cheng

LiFePO₄ batteries underpin global decarbonization efforts due to their intrinsic safety and low cost. However, emerging fire incidents in grid-scale storage demand reevaluation of their thermal stability. In contrast to the extensive focus on the stability P-O bond in PO₄, we reveal a previously overlooked gas-phase failure mechanism: delithiated LiFePO₄ cathodes undergo reductive decomposition (>600 °C) under H₂ generated during thermal runaway, forming FeP/Fe₂P and accelerating energy release. Crucially, this reaction is absent in inert atmospheres and intensifies with delithiation and battery capacity. By replacing carbonate electrolytes (H₂ source) and implementing ceramic separators (mimicking solid-state barriers), we suppress LiFePO₄ decomposition even at 800 °C. This work redefines LiFePO₄ safety paradigms, emphasizing large-system risks driven by gas-cathode interactions, and provides actionable strategies to enhance grid-storage resilience.

LiFePO4电池因其固有的安全性和低成本而支撑着全球的脱碳努力。然而，电网规模储能系统中出现的火灾事件要求对其热稳定性进行重新评估。与广泛关注PO4中P-O键的稳定性相反，我们揭示了一个以前被忽视的气相破坏机制：在热失控过程中产生的H2作用下，稀薄的LiFePO4阴极发生还原性分解（>600℃），形成FeP/Fe2P并加速能量释放。关键是，这种反应在惰性气氛中不存在，并随着电池容量的减少而加剧。通过取代碳酸盐电解质（H2源）和采用陶瓷分离器（模拟固态屏障），即使在800°C下，我们也能抑制LiFePO4的分解。这项工作重新定义了LiFePO4的安全范式，强调了气阴极相互作用驱动的大系统风险，并提供了增强电网存储弹性的可行策略。

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引用次数: 0

Passenger-aware reinforcement learning for efficient and robust energy management of fuel cell buses 基于乘客感知强化学习的燃料电池客车高效鲁棒能量管理

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 Epub Date: 2025-12-28 DOI: 10.1016/j.etran.2025.100537

Chunchun Jia , Wei Liu , K.T. Chau , Hongwen He , Jiaming Zhou , Songyan Niu

Energy management strategies (EMSs) are essential for enhancing the efficiency, durability, and economic viability of fuel cell buses (FCBs). However, existing EMSs typically rely on fixed vehicle loads or idealized passenger assumptions, while neglecting the dynamic variations in passenger number and composition. This simplification introduces biased power demand distributions, underestimates the impact of human-occupancy heat loads under hot-weather conditions on air-conditioning system (ACS) energy use, and ultimately hinders the reproducibility of reported energy savings in real-world operation. To address these limitations, this study proposes a passenger-aware collaborative EMS aimed at enhancing the driving economy of FCBs under hot-weather conditions. Distinct from prior approaches, this study leverages a dual-source passenger perception framework that fuses video recognition with electronic card swiping data to obtain reliable real-time estimates of both passenger count and gender distribution. Gender-dependent body mass differences and heterogeneous metabolic heat generation are systematically integrated into the EMS framework, ensuring accurate modeling of passenger-induced variations in vehicle mass and cabin thermal load. Within this framework, the twin delayed deep deterministic policy gradient algorithm achieves the coordinated control of the fuel cell output power and the ACS cooling capacity. Extensive evaluations under real-world driving cycles and surveyed passenger datasets demonstrate the superiority of the proposed EMS. Compared with state-of-the-art baselines, the proposed method achieves at least a 0.62 % reduction in ACS energy consumption and a 2.11 % reduction in overall operational costs, without compromising cabin comfort. Importantly, in a representative scenario with 40 passengers, this method improves driving economy by 0.92–1.87 % over a gender-agnostic baseline at male passenger proportions of 0 %, 50 %, or 100 %, confirming the practical significance of incorporating passenger information. Given that urban buses operate continuously and costs scale near-linearly with energy and degradation, even modest percentage improvements over fleet-scale deployments and vehicle lifetimes can yield meaningful economic benefits.

能源管理策略（ems）对于提高燃料电池客车（fcb）的效率、耐久性和经济可行性至关重要。然而，现有的EMSs通常依赖于固定的车辆负载或理想化的乘客假设，而忽略了乘客数量和组成的动态变化。这种简化引入了有偏差的电力需求分布，低估了炎热天气条件下人类居住热负荷对空调系统（ACS）能源使用的影响，并最终阻碍了实际运行中报告的节能的可重复性。为了解决这些限制，本研究提出了一种乘客意识的协同EMS，旨在提高高温天气条件下fcb的驱动经济性。与之前的方法不同，本研究利用了一个双源乘客感知框架，将视频识别与电子刷卡数据融合在一起，以获得可靠的乘客数量和性别分布的实时估计。性别相关的身体质量差异和异质性代谢热产生被系统地整合到EMS框架中，确保准确建模乘客引起的车辆质量和客舱热负荷变化。在此框架下，双延迟深度确定性策略梯度算法实现了燃料电池输出功率与ACS制冷量的协调控制。在真实驾驶循环和调查乘客数据集下的广泛评估证明了所提出的EMS的优越性。与最先进的基线相比，所提出的方法在不影响客舱舒适度的情况下，至少减少了0.62%的ACS能耗和2.11%的总体运营成本。重要的是，在40名乘客的代表性场景中，该方法在男性乘客比例为0%、50%或100%的情况下，比性别不可知的基线提高了0.92 - 1.87%的驾驶经济性，证实了纳入乘客信息的实际意义。考虑到城市公交车持续运行，成本与能源和环境退化几乎成线性关系，即使是在车队规模部署和车辆使用寿命上的适度改进，也能产生有意义的经济效益。

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引用次数: 0

A non-intrusive integration of wireless chargers into electric vehicles: 95.60 % dc-dc efficiency at 0.51 LD-to-CL ratio with on-vehicle demonstration 将无线充电器非侵入式集成到电动汽车中：95.60%的dc-dc效率，ld - cl比为0.51，车载演示

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 Epub Date: 2026-01-15 DOI: 10.1016/j.etran.2026.100547

Songyan Niu , Wei Liu , Chang Liu , Chunchun Jia , Marco Liserre , Kwok Tong Chau

Wireless electric vehicle charging (WEVC) is recognized as a promising technology to enhance user convenience and support autonomous mobility. Yet, the development of WEVC systems may face compatibility issues, potential intrusion into EV electronics, and privacy concerns when directly interfacing with the batteries. Moreover, under the large power transmission distance imposed by high-clearance EVs, the systems may fail to interoperate, especially when misalignments between transmitter and receiver are considered and the allowed installation space in EVs is limited. To address these challenges, this work proposes a non-intrusive framework of systems that target the onboard charger, enabling their seamless integration into EVs with a coupler that remains efficient under the severe coupling constraints. Sensitivity analysis and multi-objective optimization are first applied to identify dominant geometric parameters and balance efficiency, misalignment tolerance, and material usage. On this basis, a parasitic-aware circuit model is established to capture interlayer capacitance effects inherent to dual-layer coils. Guided by this model, a winding method is proposed to reduce voltage differences between layers, thereby minimizing dielectric losses, while an additional spacer design further reduces losses by suppressing parasitic capacitance at its source. A 3.17 kW WEVC prototype is built and installed on a commercial autonomous electric shuttle, demonstrating 95.60 % dc–dc efficiency under aligned operation and 92.64 % efficiency under 112.5 mm lateral misalignment. These outcomes confirm the practicality of the framework and system design, providing a scalable pathway for safe and compatible deployment of WEVC in real EV fleets.

无线电动汽车充电（WEVC）被认为是一种很有前途的技术，可以提高用户的便利性，支持自动驾驶。然而，WEVC系统的开发可能会面临兼容性问题，潜在的入侵电动汽车电子设备，以及直接与电池连接时的隐私问题。此外，在高间隙电动汽车的大功率传输距离下，系统可能无法实现互操作，特别是考虑发射器和接收器的不对准以及电动汽车允许的安装空间有限的情况下。为了应对这些挑战，本研究提出了一种针对车载充电器的非侵入式系统框架，使其能够通过耦合器无缝集成到电动汽车中，并在严格的耦合约束下保持高效。灵敏度分析和多目标优化首先用于确定主要几何参数和平衡效率、不对准公差和材料使用。在此基础上，建立了一个寄生感知电路模型来捕捉双层线圈固有的层间电容效应。在该模型的指导下，提出了一种绕组方法来减小层之间的电压差，从而最小化介电损耗，而额外的间隔设计通过抑制寄生电容的源进一步降低损耗。一个3.17 kW的WEVC样机被建造并安装在商用自动电动穿梭上，在对准运行下显示出95.60%的dc-dc效率，在112.5 mm横向不对准下显示出92.64%的效率。这些结果证实了框架和系统设计的实用性，为在真实的电动汽车车队中安全兼容地部署WEVC提供了可扩展的途径。

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引用次数: 0

Photonic surface engineering of conductive additives via flash lamp annealing for interfacial stabilization and homogeneous electron pathways in all-solid-state batteries 基于闪光灯退火的全固态电池界面稳定和均匀电子通路导电添加剂的光子表面工程

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 Epub Date: 2025-12-31 DOI: 10.1016/j.etran.2025.100538

Yeseung Lee , Seungwoo Lee , Jaeik Kim , Jinwoo Jeong , Seungmin Han , Jinhee Jung , Joonhyeok Park , Jooheon Sun , Jong Sung Jin , Ji Yeong Sung , Ungyu Paik , Taeseup Song

All-solid-state batteries (ASSBs) are emerging as the next-generation batteries due to their high safety and high energy density. However, sulfide-based solid electrolytes (SEs) suffer from undesirable side reactions with carbon conductive additives (CAs), as well as from the inhomogeneous distribution of CAs, both of which accelerate sluggish Li-ion kinetics and capacity fading, thereby limiting their practical applications. Here, we introduce an ultrafast and scalable flash lamp annealing (FLA) process that reduces oxygen-containing functional groups from vapor-grown carbon fiber (VGCF) and modifies its surface properties, thereby weakening inter-fiber cohesive forces. This surface functionality directly promotes more uniform distribution of the modified VGCF (F-VGCF) within the dry-processed cathode and enables the formation of a continuous electron percolation network. The improved microstructural homogeneity not only enhances electronic pathways but also suppresses SE decomposition at the CA/SE interface, thereby enhancing interfacial stability. As a result, ASSBs employing NCM/F-VGCF cathode exhibit a higher reversible capacity of 5.7 mAh cm⁻² at 0.1C compared to those with NCM/bare VGCF cathode and maintain stable cycle retention of 71.5 % at 0.3C after 160 cycles (areal capacity of 7.5 mAh cm⁻²). The FLA process provides an ultrafast and cost-effective strategy for the surface modification of CA, enabling a scalable and commercially viable approach for high-performance ASSBs.

全固态电池（assb）由于具有高安全性和高能量密度等优点，正在成为新一代电池。然而，硫化物基固体电解质（SEs）与碳导电添加剂（CAs）存在不良的副反应，并且ca的分布不均匀，这两者都加速了锂离子的缓慢动力学和容量衰退，从而限制了它们的实际应用。在这里，我们介绍了一种超快速和可扩展的闪光灯退火（FLA）工艺，该工艺减少了蒸汽生长碳纤维（VGCF）中的含氧官能团，并改变了其表面性质，从而削弱了纤维间的凝聚力。这种表面功能直接促进了改性VGCF （F-VGCF）在干法阴极中的更均匀分布，并能够形成连续的电子渗透网络。改善的微观结构均匀性不仅增强了电子路径，而且抑制了CA/SE界面上SE的分解，从而提高了界面的稳定性。结果表明，与NCM/裸VGCF阴极相比，采用NCM/F-VGCF阴极的assb在0.1C下具有更高的5.7 mAh cm - 2的可逆容量，并且在0.3C下循环160次后保持71.5%的稳定循环保留率（面积容量为7.5 mAh cm - 2）。FLA工艺为CA的表面改性提供了一种超快速和经济的策略，为高性能assb提供了一种可扩展和商业上可行的方法。

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引用次数: 0

Total cost of ownership of vehicle electrification and fuel switching options for light-duty and heavy-duty vehicles 轻型和重型车辆电气化和燃料转换选项的总拥有成本

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 Epub Date: 2025-11-13 DOI: 10.1016/j.etran.2025.100512

Kwang Hoon Baek , Xinyi Wu , Yan Zhou , Ram Vijayagopal , Namdoo Kim , Amgad Elgowainy

Projecting the transition from combustion engines to battery-based powertrains is complex becuase it involves numerous interdependent decisions. This study estimates total cost of ownership (TCO) to assess the economic viability of powertrain electrification, focusing exclusively on advances in vehicle and fuel technologies. Under two bounding technology-progress scenarios, we develop vehicle designs and fuel cost trajectories, which serve as inputs to TCO projections for selected classes from 2021 to 2050.

We analyzed a small sport utility vehicle (SUV) to represent the light-duty vehicle (LDV) sector, and four medium- and heavy-duty vehicle (MHDV) classes: Class 6 box delivery, Class 8 drayage, Class 8 long-haul, and Class 8 transit bus. For each class, we compared the TCO of battery electric vehicles (BEVs) and fuel cell hybrid electric vehicles (FCHEVs) against conventional internal combustion engine vehicles (ICEVs).

The results show that modern ICEVs generally have lower TCO; however, BEVs and FCHEVs could match or have lower TCOs than ICEVs over time, depending on technological progress. In LDVs, BEV300 is projected to deliver the lowest TCO by 2050, particularly under the high-progress scenario. In MHDVs, both BEVs and FCHEVs could become more cost-competitive than ICEVs by 2050 in the high-progress case.

Beyond these results, the findings suggest further investigation is warranted for BEV charging infrastructure, FCHEV hydrogen refueling infrastructure, and MHDV charging strategies. These factors could reduce the fuel-cost share of TCO and enhance the competitiveness of BEVs and FCHEVs relative to ICEVs.

规划从内燃机向电池动力系统的过渡是复杂的，因为它涉及许多相互依存的决策。本研究通过估算总拥有成本（TCO）来评估动力总成电气化的经济可行性，重点关注车辆和燃料技术的进步。在两种边界技术进步情景下，我们开发了车辆设计和燃料成本轨迹，作为2021年至2050年选定类别的TCO预测的输入。我们分析了代表轻型车辆（LDV）领域的小型运动型多用途车（SUV），以及四种中型和重型车辆（MHDV）类别：第6类箱子运输，第8类运输，第8类长途和第8类运输巴士。对于每个类别，我们比较了纯电动汽车（bev）和燃料电池混合动力汽车（FCHEVs）与传统内燃机汽车（icev）的总拥有成本（TCO）。结果表明，现代icev总体上具有较低的TCO；然而，随着时间的推移，纯电动汽车和电动汽车的tco可能会与电动汽车相当，或者低于电动汽车，这取决于技术进步。在ldv中，BEV300预计到2050年将提供最低的总拥有成本，特别是在高进度情景下。在高速发展的情况下，到2050年，纯电动汽车和氢燃料电池汽车都将比电动汽车更具成本竞争力。除了这些结果之外，研究结果还表明，有必要对纯电动汽车充电基础设施、FCHEV氢燃料补给基础设施和MHDV充电策略进行进一步调查。这些因素可以降低总成本的燃料成本份额，提高纯电动汽车和氢燃料汽车相对于内燃机汽车的竞争力。

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引用次数: 0

Interpretable image based modeling of EV battery degradation from cumulative operational patterns 基于累积操作模式的电动汽车电池退化可解释图像建模

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 Epub Date: 2025-12-31 DOI: 10.1016/j.etran.2025.100539

Sangryuk Lee, Dongho Han, Taebin Ha, Taeyoon Kim, Jonghoon Kim

With the advent of the big-data era, the explosive growth of electric vehicle (EV) operational data and diverse driving patterns has resulted in complicated battery degradation mechanisms, exposing the limitations of conventional raw-data-based approaches in large-scale system management. To address this challenge, this study proposed a cumulative operational pattern image-generation technique that integrates current and state-of-charge (SOC) information. To simulate actual EV data, six different driver cases were selected, and their data were analyzed to develop a five-step process that compresses variations in current patterns and SOC intervals into RGB values. As data continued to be collected, the colors of the image accumulated to ultimately generate a cumulative operational pattern image. This approach effectively reduces the massive volume of raw data while visually preserving the operational characteristics of the battery. The generated cumulative operational pattern images were then utilized in a convolutional neural network (CNN)-long short-term memory (LSTM) model to quantitatively estimate battery degradation indices, specifically global loss of active material (

G_{L L I}

) and global loss of lithium inventory (

G_{L A M}

), thereby validating the effectiveness of the proposed image-generation technique. Furthermore, the gradient-weighted class activation mapping (Grad-CAM) technique was applied to visually interpret how the model utilized SOC intervals and current patterns for degradation estimation, confirming the validity and potential scalability of the proposed approach. These results suggest new research directions and potential applications for the efficient management of data in large-scale EV systems and establishment of operational strategies.

随着大数据时代的到来，电动汽车运行数据的爆炸式增长和驾驶模式的多样化，导致电池退化机制复杂，暴露出传统基于原始数据的方法在大规模系统管理中的局限性。为了应对这一挑战，本研究提出了一种集成当前和充电状态（SOC）信息的累积操作模式图像生成技术。为了模拟实际的电动汽车数据，研究人员选择了6个不同的驾驶案例，并对其数据进行了分析，从而开发了一个五步流程，将当前模式和SOC间隔的变化压缩为RGB值。随着数据的不断收集，图像的颜色不断累积，最终生成累积的操作模式图像。这种方法有效地减少了大量的原始数据，同时在视觉上保留了电池的操作特性。然后将生成的累积操作模式图像用于卷积神经网络（CNN）长短期记忆（LSTM）模型，定量估计电池退化指标，特别是活性物质的全局损失（GLLI）和锂库存的全局损失（GLAM），从而验证所提出的图像生成技术的有效性。此外，应用梯度加权类激活映射（Grad-CAM）技术直观地解释了该模型如何利用SOC间隔和当前模式进行退化估计，从而证实了所提出方法的有效性和潜在的可扩展性。这些结果为大规模电动汽车系统数据的高效管理和运营策略的制定提供了新的研究方向和应用前景。

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引用次数: 0

Life cycle assessment of lithium-ion and secondary batteries: A comparative analysis on environmental impacts and graphite recycling 锂离子电池与二次电池生命周期评价：环境影响与石墨回收的对比分析

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 Epub Date: 2025-11-18 DOI: 10.1016/j.etran.2025.100514

Faiza Arshad , Muhammad Usman Azam , Nagesh Manurkar , Fengling Zhang , Bushra Sana Idrees , Ali Ahmad , Liqianyun Xu , Feng Wu , Renjie Chen , Li Li

The production of electric vehicles as an alternative to fossil–fuel–based transportation necessitates a comprehensive understanding of the environmental impacts associated with rechargeable batteries. This study performs a life cycle assessment (LCA) to compare the environmental impacts of four emerging and commercial battery types including lithium–sulfur (Li–S), magnesium–sulfur (Mg–S), sodium-ion (Na-ion), and nickel–metal hydride (NiMH) with a particular focus on their production and recycling phases. Key ecological indicators such as greenhouse gas (GHG) emissions, land use, nuclear energy demand, and a broad range of impact categories were analyzed. Results show that Mg–S batteries demonstrate the lowest environmental footprint and highest robustness across multiple impact categories, whereas NiMH batteries contribute the most to GHG emissions and nuclear energy demand. A comparative analysis of cathode material systems for lithium-ion batteries (LIBs) further emphasizes the disproportionate environmental burden posed by cathode production. The findings also suggest that the material innovation, particularly in the cathode and anode design along with optimization of recycling processes, is essential for reducing the ecological footprint of battery technologies and achieving low-carbon mobility goals.

生产电动汽车作为化石燃料交通工具的替代品，需要全面了解与可充电电池相关的环境影响。本研究进行了生命周期评估（LCA），以比较四种新兴和商用电池类型的环境影响，包括锂硫电池（Li-S）、镁硫电池（Mg-S）、钠离子电池（Na-ion）和镍氢电池（NiMH），并特别关注它们的生产和回收阶段。分析了温室气体（GHG）排放、土地利用、核能需求等关键生态指标和广泛的影响类别。结果表明，Mg-S电池在多种影响类别中表现出最低的环境足迹和最高的稳健性，而镍氢电池对温室气体排放和核能需求的贡献最大。锂离子电池正极材料系统的对比分析进一步强调了阴极生产造成的不成比例的环境负担。研究结果还表明，材料创新，特别是阴极和阳极设计以及回收过程的优化，对于减少电池技术的生态足迹和实现低碳移动目标至关重要。

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引用次数: 0