Etransportation最新文献_第3页

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 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

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 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

In-situ analysis and estimation of temperature distribution for large-format lithium-ion batteries based on distributed optical fiber sensors 基于分布式光纤传感器的大尺寸锂离子电池温度分布的原位分析与估计

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 DOI: 10.1016/j.etran.2025.100425

Xiaoqiang Zhang, Yuhao Zhu, Linfei Hou, Jingyu Hu, Yunlong Shang

Real-time monitoring and estimation of temperature distribution are crucial for the safe operation of batteries. Conventional temperature monitoring techniques, such as thermocouples and infrared thermography, typically provide point-based measurements. In contrast, distributed optical fiber sensors (DOFSs) enable continuous and high-resolution spatial monitoring. Additionally, current model-based temperature estimation often assumes uniform surface convection coefficients and relies on sparse temperature data for validation. These limitations lead to significant inaccuracies in characterizing the inherent non-uniform and asymmetric temperature distributions of large-format batteries. To address these challenges, this study presents an S-shaped DOFS layout for in-situ monitoring of an 81.4 Ah pouch lithium-ion battery at 0.5C–1.5C rates, with a 1.28 mm spatial resolution. Furthermore, a multi-domain thermal boundary modeling framework is proposed, which accounts for localized heat convection variations. Experimental validation confirms the model's accuracy, achieving a maximum root mean square error of 0.47 °C. Though validated only on a single-cell, this work offers a sensing-modeling-estimation framework for battery thermal management in electric vehicle packs and energy storage systems.

温度分布的实时监测和估计对电池的安全运行至关重要。传统的温度监测技术，如热电偶和红外热成像，通常提供基于点的测量。相比之下，分布式光纤传感器（dofs）可以实现连续和高分辨率的空间监测。此外，目前基于模型的温度估计通常假设均匀的表面对流系数，并依赖于稀疏的温度数据进行验证。这些限制导致表征大尺寸电池固有的不均匀和不对称温度分布的显著不准确性。为了解决这些挑战，本研究提出了一种s形DOFS布局，用于在0.5C-1.5C速率下对81.4 Ah袋式锂离子电池进行原位监测，空间分辨率为1.28 mm。在此基础上，提出了考虑局域热对流变化的多域热边界建模框架。实验验证证实了模型的准确性，最大均方根误差为0.47°C。虽然仅在单个电池上进行了验证，但这项工作为电动汽车电池组和储能系统的电池热管理提供了一个传感建模估计框架。

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引用次数: 0

Patterned amphiphilic transport porous layer of reversible fuel cell for high round-trip efficiency 可逆燃料电池高往返效率的图像化两亲性输运多孔层

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 DOI: 10.1016/j.etran.2025.100534

Yun Wang , YanFeng Hai , Kathryn Coletti , Michael Pien , Zheng Guan , Tianyu Zhang

Unitized reversible fuel cells (RFCs) are superior to individual water electrolyzer and hydrogen fuel cell in terms of cost, space, and volume, which require further advancement for high round-trip efficiency (RTE) in energy storage applications. In this study, we report an RFC based on patterned amphiphilic porous materials, dual-layered cathode catalyst layer, and proton exchange membranes (PEM), which achieves a high RTE that beats the US DOE 2020 status. The amphiphilic porous transport layer (PTL) contains patterned hydrophilic and hydrophobic micro-pathways for liquid water and oxygen transport, respectively, which is fabricated based on sintered Titanium powders using advanced laser patterning. The RFC achieves a record RTE of 52.8 % for fuel cell (FC) mode of power generation under 0.5 A/cm² and electrolysis cell (EC) mode of hydrogen production under 1 A/cm². A three-dimensional (3D) RFC model that treats PTL as two distinct domains is established to examine detailed liquid water distribution, showing a low (<15 %) and high (>85 %) liquid water saturation in the PTL in the FC and EC modes under 0.5 and 1 A/cm², respectively. This study makes major contributions to novel PTL materials, CL fabrication, and RFC modeling for high RTEs.

组合式可逆燃料电池（rfc）在成本、空间和体积上都优于单体水电解槽和氢燃料电池，但在储能应用中要实现高往返效率（RTE）还需进一步发展。在这项研究中，我们报告了一种基于图案化两亲性多孔材料、双层阴极催化剂层和质子交换膜（PEM）的RFC，该RTE达到了超过美国DOE 2020标准的高RTE。两亲性多孔输运层（PTL）分别包含液态水和液态氧输运的亲水和疏水微通道。在0.5 a /cm2的燃料电池（FC）发电模式和1 a /cm2的电解电池（EC）制氢模式下，RFC实现了创纪录的52.8%的RTE。建立了一个三维（3D） RFC模型，将PTL作为两个不同的域来研究详细的液态水分布，显示在0.5和1 A/cm2的FC和EC模式下，PTL中液态水饱和度分别为低（< 15%）和高（> 85%）。本研究对新型PTL材料、CL制造和高rte的RFC建模做出了重大贡献。

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引用次数: 0

A multi-fluid prediction model of anode gas recirculation ejector for real-time control of fuel cell vehicles under overall operating modes 用于燃料电池汽车整体工况下阳极气体再循环喷射器实时控制的多流体预测模型

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 DOI: 10.1016/j.etran.2026.100545

Yajie Song , Chen Wang , Lei Wang , Xinli Wang , Lei Jia , Qinhe Wang

The real-time control of the ejector-driven anode multi-fluid gas recirculation system (AGRS) is a challenging task under both critical and subcritical operating modes of proton exchange membrane fuel cell (PEMFC) for vehicles. In this paper, a concise performance prediction model for multi-fluid ejectors with a non-iterative solution is established under overall operating modes. The characteristic points (critical recirculation ratio ω_∗, critical back pressure p_c∗, and reflux pressure p_cb) are expressed as three linear equations with six lumped parameters (k₁-k₆), which can be easily identified by the least squares method. Then, the subcritical recirculation ratio (ω_sub) is approximated as a quadratic function of p_c by integrating p_c∗, p_cb, and ω_∗. The feasibility and accuracy of the proposed model are validated using literature data, with additional H₂ testing result and comparison to traditional models. The model's real-time applicability is also examined. The relative errors of the p_c∗, p_cb, and ω_∗ are less than −2.89%, 1.11%, and 1.60%, indicating the high prediction accuracy of the characteristic points. Besides, the average relative errors of the ω_sub and outlet temperature (T_c) are 9.43% and 0.64%, respectively. The comparison results show that the proposed model outperforms the traditional models in structural characteristics and prediction accuracy under overall modes. Additionally, a formula of k₁-k₆ consists of two geometric variables (D_nt and D₃) is derived, which is convenient to use in practice. Finally, the established ejector model is also integrated into AGRS, and its dynamic response is analyzed. The proposed model is helpful for the real-time control of the ejector-driven AGRS in fuel cell vehicles, and can provide guidance for the design and optimization of hydrogen ejectors.

在车用质子交换膜燃料电池（PEMFC）临界和亚临界工况下，喷射器驱动阳极多流体气体再循环系统（AGRS）的实时控制是一项具有挑战性的任务。本文建立了多流体喷射器总体工作模式下的简洁非迭代性能预测模型。特征点（临界再循环比ω *，临界背压pc *和回流压力pcb）表示为具有六个集总参数（k1-k6）的三个线性方程，可以很容易地通过最小二乘法识别。然后，亚临界再循环比（ωsub）通过对pc *、pcb和ω *的积分近似为pc的二次函数。利用文献数据验证了该模型的可行性和准确性，并与传统模型进行了H2检验和比较。并对模型的实时性进行了检验。pc∗、pcb和ω∗的相对误差分别小于- 2.89%、1.11%和1.60%，表明特征点的预测精度较高。ωsub和出口温度（Tc）的平均相对误差分别为9.43%和0.64%。对比结果表明，该模型在整体模态下的结构特征和预测精度均优于传统模型。此外，还推导出了由两个几何变量（Dnt和D3）组成的k1-k6的公式，便于在实践中使用。最后，将建立的喷射器模型集成到AGRS中，对其动态响应进行了分析。该模型有助于燃料电池汽车喷射器驱动AGRS的实时控制，并可为氢气喷射器的设计与优化提供指导。

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引用次数: 0

Quantitative diagnosis of hydrogen crossover in fuel cell: based on the hydrogen concentration cell 燃料电池氢交叉的定量诊断：基于氢浓度电池

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 DOI: 10.1016/j.etran.2026.100543

Yangyang Ma , Sida Li , Xueyuan Wang , Shulin Zhou , Zhiyuan Chen , Hao Yuan , Penglong Bao , Yabo Wang , Guofeng Chang , Haifeng Dai , Xuezhe Wei

Timely and efficient hydrogen crossover diagnosis is crucial for improving the performance, durability, and safety of proton exchange membrane fuel cell (PEMFC). However, most existing diagnostic methods are complicated to operate, time-consuming, costly, and necessitate complex data processing. There are almost no studies that can achieve hydrogen crossover diagnosis in seconds without requiring additional equipment other than conventional fuel cell testing bench. To address this gap, a novel quantitative diagnostic method of hydrogen crossover based on the hydrogen concentration cell is proposed. Specifically, the essence of the open circuit voltage (OCV) arising from the hydrogen concentration cell formed by hydrogen crossover phenomenon is thoroughly investigated via Nernst equation, to propose this novel quantitative diagnostic method. This novel quantitative diagnostic method requires only three parameters: OCV, cathode flow rates, and fuel cell temperature, to rapidly achieve quantitative diagnosis of hydrogen crossover current. After conducting 228 trials, the proposed novel quantitative diagnostic method demonstrated a maximum relative error and a mean absolute percentage error (MAPE) of 4.89 % and 2.54 %, when compared to the validated and reliable potential step method (PSM), fully verifying its repeatability and accuracy. This novel method can achieve quantitative diagnosis of hydrogen crossover in seconds on any conventional fuel cell testing bench, with high cost-effective and simple data processing. It will provide a powerful tool for quality control, optimization design, periodic diagnosis, and aging assessment of fuel cell.

及时有效的氢交叉诊断对于提高质子交换膜燃料电池（PEMFC）的性能、耐久性和安全性至关重要。然而，大多数现有的诊断方法操作复杂，耗时，昂贵，并且需要复杂的数据处理。除了传统的燃料电池测试平台，几乎没有研究可以在不需要额外设备的情况下在几秒钟内完成氢交叉诊断。为了解决这一问题，提出了一种基于氢浓度电池的氢交叉定量诊断方法。具体而言，通过能斯特方程深入研究了氢交叉现象形成的氢浓缩池产生的开路电压（OCV）的本质，提出了这种新的定量诊断方法。这种新型的定量诊断方法只需要三个参数：OCV、阴极流速和燃料电池温度，即可快速实现氢交叉电流的定量诊断。经过228次试验，与已验证可靠的电位阶跃法（PSM）相比，该方法的最大相对误差和平均绝对百分比误差（MAPE）分别为4.89%和2.54%，充分验证了其重复性和准确性。该方法可在任何常规燃料电池试验台上，在数秒内实现氢交叉的定量诊断，具有成本效益高、数据处理简单等优点。它将为燃料电池的质量控制、优化设计、定期诊断和老化评估提供有力的工具。

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引用次数: 0

Fabrication technologies of free-standing thin lithium metal anode for high energy density lithium batteries 高能量密度锂电池独立式薄锂金属负极制造技术

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 DOI: 10.1016/j.etran.2025.100535

Xulai Yang , Mengqin Tao , Fei Zhou , Qian Huang

Lithium metal anodes (LMAs) have garnered substantial attention owing to their extraordinarily high theoretical specific capacity and extremely low redox potential. The development of practical lithium metal batteries (LMBs) necessitates LMAs with controllable thickness and free-standing characteristics to maximize energy density and electrochemical performance. This review systematically summarized advanced fabrication technologies for free-standing thin LMAs, including mechanical rolling, physical vapor deposition, chemical thinning, and electrodeposition, while analyzing their respective strengths, limitations, and scalability. It highlighted that constructing lithium-based composite anodes, by integrating Li metal with conductive, dielectric, or conductive-dielectric gradient scaffolds, represented an effective strategy to overcome the intrinsic drawbacks of pure LMAs. Specifically, conductive scaffolds (metal-, carbon-, or metal-carbon-based) regulate electron/ion transport and reduce local current density; dielectric scaffolds with polar functional groups homogenize Li⁺ flux; and gradient scaffolds enable “bottom-up” Li deposition. These mechanisms synergistically suppress dendrite growth and mitigate volume changes to some extent. Under practical conditions, the review evaluated the performance of composite anodes in terms of cycling stability, Li utilization efficiency, and compatibility with high-loading cathodes. Finally, it outlined future directions for scaling up thin LMAs, emphasizing the need for simulation calculation, intelligent manufacturing and intelligent battery technology to bridge the gap between laboratory research and industrial applications.

锂金属阳极由于具有极高的理论比容量和极低的氧化还原电位而引起了人们的广泛关注。实用锂金属电池（lmb）的发展需要具有可控厚度和独立特性的lma，以最大限度地提高能量密度和电化学性能。本文系统地总结了独立薄型LMAs的先进制造技术，包括机械轧制、物理气相沉积、化学减薄和电沉积，并分析了各自的优势、局限性和可扩展性。研究强调，通过将锂金属与导电、介电或导电-介电梯度支架相结合，构建锂基复合阳极是克服纯LMAs固有缺陷的有效策略。具体来说，导电支架（金属基，碳基或金属碳基）调节电子/离子传输并降低局部电流密度；具有极性官能团的介质支架使Li+通量均匀化；梯度支架可以实现“自下而上”的锂沉积。这些机制在一定程度上协同抑制枝晶生长和减轻体积变化。在实际条件下，从循环稳定性、锂利用效率以及与高负荷阴极的相容性等方面对复合阳极的性能进行了评价。最后，概述了未来扩大薄型lma的方向，强调需要模拟计算、智能制造和智能电池技术来弥合实验室研究与工业应用之间的差距。

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引用次数: 0

Multi-fault diagnosis strategy based on sliding mode enhanced carrier decision of the aging IPMSM for the electric rail transit 基于滑模的多故障诊断策略增强了电气化轨道交通老化IPMSM的载波决策

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 DOI: 10.1016/j.etran.2025.100536

Shicai Yin , Xiang Li , Jinqiu Gao , Yaofei Han

The interior permanent magnet synchronous motor (IPMSM) is the core of the traction drive system (TDS) in electric rail transit. Its aging faults can lead to reduced train power, wheelset-rail oscillations, and even trigger secondary failures that affect passenger safety. Existing diagnostic strategies often require additional observers, complex signal injection, or large volumes of fault data, which either reduce the reliability during train operation or make deployment challenging within the safety-oriented framework of train operations. This paper proposes a multi-fault diagnosis strategy (MFDS) based on sliding mode enhanced carrier decision (SMECD). The SMECD integrates existing onboard control signals of electric rail transit as fault carriers, eliminating the need for additional hardware and ensuring reliable onboard deployment capabilities. In addition, an aging fault injection model (AFIM) is proposed, which integrates diverse aging faults. The AFIM can replicate the aging faults of the IPMSM caused by frequent switching of different operating conditions in the TDS, ensuring the application validation of the MFDS. The experimental results show that the MFDS can accurately locate different aging faults, thereby providing predictive maintenance guidance for rail transit operations. Compared to traditional diagnostic strategies, the MFDS does not require additional observers or sensors to monitor the aging parameters of the IPMSM in the TDS, offering a lightweight and easily deployable diagnostic strategy for the entire lifecycle of train operations, thus enhancing the safety and reliability of electric rail transit.

内置式永磁同步电动机是轨道交通牵引传动系统的核心。它的老化故障会导致列车功率降低，轮轨振荡，甚至引发影响乘客安全的二次故障。现有的诊断策略通常需要额外的观察者、复杂的信号注入或大量的故障数据，这要么降低了列车运行期间的可靠性，要么使部署在以列车运行为导向的安全框架内具有挑战性。提出了一种基于滑模增强载波决策的多故障诊断策略（MFDS）。SMECD集成了现有的电力轨道交通车载控制信号作为故障载体，消除了对额外硬件的需求，并确保了可靠的车载部署能力。此外，提出了一种集成多种老化故障的老化故障注入模型（AFIM）。AFIM可以复制由于TDS中不同工况频繁切换而导致的IPMSM老化故障，保证了MFDS的应用有效性。实验结果表明，MFDS能够准确定位不同类型的老化故障，为轨道交通运营提供预测性维修指导。与传统的诊断策略相比，MFDS不需要额外的观察者或传感器来监测TDS中IPMSM的老化参数，为列车运行的整个生命周期提供了一种轻量级且易于部署的诊断策略，从而提高了电力轨道交通的安全性和可靠性。

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引用次数: 0

System-level integration of electric transportation in smart grids: An aggregator-centric review of control architectures, optimization algorithms, and business models 智能电网中电力运输的系统级集成：以集成商为中心的控制体系结构、优化算法和商业模型综述

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 DOI: 10.1016/j.etran.2025.100542

MohammadAmin Mahjoubnia , Taher Niknam , Ali Taghavi , Hamed Heydari-Doostabad

The rapid electrification of transportation has accelerated electric vehicle (EV) adoption. Projections indicate that EVs will account for 50% of new car sales by 2035. However, uncoordinated EV charging poses substantial challenges to power system stability. It can increase peak demand (20–40%) and accelerate aging of distribution infrastructure. Vehicle-to-Everything (V2X) technologies, encompassing unidirectional smart charging and bidirectional Vehicle-to-Grid (V2G), offer potential solutions, with studies demonstrating up to 60% peak demand reduction and high renewable utilization. However, widespread adoption is hindered by system-level integration barriers.

This systematic review adopts an aggregator-centric framework, positioning the aggregator as key coordinator for technical optimization, economic viability, and user engagement. Unlike prior reviews focusing on isolated aspects such as algorithms, markets, or user behavior, this study synthesizes 140 articles (from 492 retrieved, 2019–2025) through dual-query searches in Scopus and IEEE Xplore, with bibliometric co-occurrence analysis. Seven research clusters were identified, spanning optimization methods, AI, grid services, renewable integration, user behavior, peak management, and market mechanisms.

The review identifies inter-dependencies among control architectures (centralized to decentralized), optimization strategies (mathematical programming to deep reinforcement learning), grid services (peak shaving to resilience), and user considerations (e.g., battery degradation). Key insights demonstrate the aggregator plays a multi-faceted role in balancing grid stability, market participation, and user adoption, with grid capacity limitations potentially reducing V2G effectiveness by 50–70%.

Finally, the review proposes a roadmap emphasizing adaptive control architectures, explainable AI, standardized communication protocols, user-centric interfaces, and sustainable business models to overcome barriers and enable scalable, interoperable V2X ecosystems.

交通运输的快速电气化加速了电动汽车的普及。预测显示，到2035年，电动汽车将占到新车销量的50%。然而，电动汽车充电不协调给电力系统的稳定性带来了巨大挑战。它会增加高峰需求（20-40%），并加速配电基础设施的老化。车辆到一切（V2X）技术，包括单向智能充电和双向车辆到电网（V2G），提供了潜在的解决方案，研究表明，峰值需求减少高达60%，可再生能源利用率高。然而，广泛采用受到系统级集成障碍的阻碍。本系统综述采用以聚合器为中心的框架，将聚合器定位为技术优化、经济可行性和用户参与的关键协调器。与以往的综述不同，本研究主要关注算法、市场或用户行为等孤立方面，通过在Scopus和IEEE Xplore中进行双查询搜索，并进行文献计量共现分析，综合了140篇文章（来自2019-2025年检索的492篇文章）。确定了七个研究集群，涵盖优化方法、人工智能、电网服务、可再生能源整合、用户行为、峰值管理和市场机制。该评论确定了控制体系结构（集中式到分散式）、优化策略（数学规划到深度强化学习）、电网服务（调峰到弹性）和用户考虑（例如电池退化）之间的相互依赖关系。关键见解表明，聚合器在平衡电网稳定性、市场参与和用户采用方面发挥着多方面的作用，而电网容量限制可能会使V2G效率降低50-70%。最后，该综述提出了一个路线图，强调自适应控制架构、可解释的人工智能、标准化通信协议、以用户为中心的界面和可持续的商业模式，以克服障碍，实现可扩展、可互操作的V2X生态系统。

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引用次数: 0

Research progress on loss calculation, temperature monitoring and thermal management technology of electric drive assembly: A comprehensive review 电传动组件损耗计算、温度监测及热管理技术研究进展综述

IF 17 1区工程技术 Q1 ENERGY & FUELS

Etransportation

Pub Date : 2026-01-01 DOI: 10.1016/j.etran.2025.100541

Peng Tang, Zhiguo Zhao, Jianyu Yang, Wenbo Fan

The development of efficient and compact electric drive assembly (EDA) is treated as a crucial pathway to enhance the energy-saving potential of electric vehicles while effectively reducing carbon emissions. However, serious thermal management issues have surfaced under intricate operating conditions as a result of the growing integration of EDA. EDA's key parts like motors and inverters can quickly deteriorate due to extreme overheating. Thus, one crucial way to guarantee EDA's thermal safety is to monitor its thermal state under varied operating conditions and carry out efficient regulation. Actually, the research advances and shortcomings of EDA loss, thermal monitoring, and thermal management are not well summarized in the literature at present. Moreover, the sustainable development of EDA effective thermal management technology is thus promoted by evaluating and summarizing the current research accomplishments, which helps to comprehend the current technological level and its limitations in practical applications. First, this paper proposed a systematic development and closed-loop optimization framework for EDA thermal monitoring and active thermal management strategies, and conducts a comprehensive analysis and review of EDA loss calculation, thermal monitoring, and active and passive thermal management methods. Second, a thorough examination and comparison of the data reveals that the hybrid cooling approach, the mechanism and the data-driven fusion prediction method all perform optimally when compared to other methods now in use. However, their practical application still needs to overcome limitations such as the unclear thermal failure mechanism in extreme environments, limited edge sensing, insufficient computing power of automotive-grade chips, and the lack of testing standards. Finally, the challenges faced by EDA thermal monitoring and efficient thermal management methods in practical application are discussed. Additionally, its application directions are highlighted, including: large-scale standardized application, construction of intelligent monitoring-early warning-collaborative prevention and control framework, cloud-edge big data integration, and multi-scenario smart and reliable application.

开发高效、紧凑的电驱动总成是提高电动汽车节能潜力、有效降低碳排放的重要途径。然而，由于EDA的日益集成，在复杂的操作条件下，严重的热管理问题已经浮出水面。EDA的关键部件，如电机和逆变器，会因极度过热而迅速恶化。因此，对不同工况下的热状态进行监测并进行有效调控，是保证EDA热安全的重要途径之一。实际上，目前文献对EDA损耗、热监测、热管理等方面的研究进展和不足并没有很好的总结。通过对当前研究成果的评价和总结，促进EDA有效热管理技术的可持续发展，有助于了解当前的技术水平及其在实际应用中的局限性。首先，本文提出了EDA热监测和主动热管理策略的系统开发和闭环优化框架，并对EDA损耗计算、热监测以及主动和被动热管理方法进行了全面的分析和综述。其次，通过对数据的全面检查和比较，表明混合冷却方法、机制和数据驱动的聚变预测方法与目前使用的其他方法相比都具有最佳性能。但其实际应用仍需克服极端环境下热失效机制不明确、边缘感知受限、汽车级芯片计算能力不足、缺乏测试标准等限制。最后，讨论了EDA热监测和高效热管理方法在实际应用中面临的挑战。重点介绍了其应用方向，包括：规模化标准化应用、智能监控-预警-协同防控框架建设、云边缘大数据融合、多场景智能可靠应用等。

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引用次数: 0