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Green Energy and Intelligent Transportation
Scopus
ISSN 2773-1537 · Elsevier · 175 artikel di indeks
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Artikel Jurnal
Fusing coupled degradation mechanisms with machine learning: A multi-fidelity framework for lithium-ion battery lifespan prediction
Accurate prediction of battery remaining useful life (RUL) is critical for safety enhancement and service extension. However, conventional model-based methods suffer from computational complexity, while data-driven methods struggle with inadequate mechanistic interpretability and prohibitive data…
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Artikel Jurnal
Selective knowledge distillation-based domain adaptation framework towards edge computing fault Diagnosis for high-speed train bogie
Edge deployment of deep learning models for high-speed train bogie fault diagnosis is challenged by computational constraints and cross-domain diagnostic requirements under varying operational conditions. This paper proposes a selective knowledge distillation-based domain adaptation framework…
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Artikel Jurnal
Li-ion battery swelling force: Multiphysics coupling modeling and in-situ quantification for safety enhancement
Lithium-ion batteries typically exist in modular configurations, where individual cells are subjected to mechanical constraints upon assembled into groups. During charging, volume expansion of lithium-ion batteries induces substantial internal pressure within the battery pack, a phenomenon whose…
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Artikel Jurnal
Automating the estimation of turning movement rates at multilane roundabouts using unmanned aerial vehicles and deep learning
Estimating turning movement rates (TMRs) at multilane roundabouts is more complex than that at conventional intersections due to the vehicle maneuvers and the difficulty of tracking each vehicle through the roundabout. Traditional data collection methods often fail to capture these interactions…
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Artikel Jurnal
Real-world vehicle charging duration prediction based on transfer learning with SENet-CNN-Transformer Model
Charging duration, defined as the duration required to charge from current to target state of charge, critically determines user experience enhancement. Accurate charging duration prediction faces significant technical challenges, primarily stemming from two issues: the scarcity of real-world…
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Artikel Jurnal
A novel active equalization scheme for lithium-ion batteries using path planning
A novel equalization topology based on flexible reconfigurable is proposed to solve the cell inconsistency issues. This topology offers exceptional flexibility, enabling the operation of multiple equalization modes. The equalization topology is abstracted as a directed graph and an energy transfer…
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Artikel Jurnal
Model-based structural isolation of concurrent electro-thermal faults for eVTOL battery systems
Battery fault diagnosis is a prerequisite for safety certification to electric vertical take-off and landing (eVTOL) aircraft. Unlike ground vehicles, eVTOL systems operate under a zero-failure tolerance regime, as even minor battery anomalies can compromise flight safety. However, existing…
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Artikel Jurnal
Feature-enhanced ensemble learning for accurate capacity estimation of lithium-ion batteries using partial discharging segments in initial stage based on second-order voltage derivatives
Accurate and rapid capacity estimation is essential for efficient battery management in industrial settings particularly for cell grading, pack assembly, and second-life screening where throughput, cost, and energy efficiency are paramount. Conventional approaches require complete discharge cycles…
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Artikel Jurnal
An efficient feature search approach for robust state of health estimation of Li-ion battery
Accurate state of health (SOH) estimation is fundamental in battery prognostics and health management. Existing estimation methods often rely on manually selected features, limiting their generalizability and robustness due to subjective bias. This paper proposes an efficient feature search method…
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Artikel Jurnal
Integrated bidirectional electric vehicle battery network for sustainable communities: A planning framework
The transition towards sustainable and net-zero energy communities has become imperative in addressing the challenges of climate change and ensuring a resilient energy future. This work proposes an innovative planning framework through the development of an integrated bidirectional electric vehicle…
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Artikel Jurnal
Deep learning-driven CNN model for detection and classification of dynamic obstacles
In recent years, advancements in autonomous driving technologies have shown significant potential to improve road safety, although their current impact remains a subject of ongoing research and debate. At the core of this improvement is obstacle detection, a crucial element for ensuring the…
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Artikel Jurnal
Dynamic range compression dual-domain attention network for tunnel extreme exposure image enhancement in transportation visual systems
The rapid expansion of road transportation infrastructure has led to an increased prevalence of tunnel scenarios, which are often characterized by extreme lighting conditions. These “black hole” and “white hole” effects, caused by stark brightness contrasts between tunnel entrances and interiors…
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Artikel Jurnal
Innovative solid-state battery fabrication and interface engineering for sustainable transportation and green energy systems
Lithium-ion solid-state batteries (SSBs) play a key role in the next-generation battery technology. This work compares the characteristics and fabrication procedures of sulfide-based and oxide-based solid electrolytes (SEs). Since ionic conductivity is a critical factor in battery performance, we…
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Artikel Jurnal
Configuration and parameter Design of electrified propulsion systems for three-dimensional Transportation: A comprehensive review
The design of electrified propulsion systems, including their configuration and parameter layers, is crucial to overall vehicle performance. However, with the electrification of three-dimensional transportation (TDT) (air, ground, and sea) and net-zero emission requirements, new challenges and…
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Artikel Jurnal
Uncertainty quantification-based framework for predicting degradation trends of proton exchange membrane fuel cell
Accurately predicting the degradation trends of proton exchange membrane fuel cells (PEMFCs) can provide a solid basis for optimizing the control of vehicles and stations based on PEMFCs. However, most prediction methods do not consider factors such as measurement errors from experimental…
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Artikel Jurnal
Toward smart railway maintenance: AI-enhanced Non-Destructive Evaluation using Vision Transformers and CNNs for fastener defect detection
Predictive health management and maintenance of transport infrastructure are critical for preventing accidents and service disruptions. Applying Non-Destructive Evaluation (NDE) and imaging techniques is essential for identifying irregularities without causing harm. This research utilizes…
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Artikel Jurnal
Topology-oriented multi-objective optimization for interior permanent magnet synchronous motors using AutoML-based surrogate models
With the rapid expansion of the electric vehicle market, interior permanent magnet synchronous motors (IPMSMs) have become increasingly critical for high-performance drive systems. However, the diversity of rotor topologies and the computational intensity of traditional finite element analysis…
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Artikel Jurnal
Triply Periodic Minimal Surface (TPMS) architectures for advanced battery thermal management systems in EVs: Manufacturing, integration, and future prospects
Efficient thermal management is a critical requirement for high-performance, safe, and long-lasting lithium-ion batteries in electric vehicles (EVs). Triply Periodic Minimal Surface (TPMS) structures have emerged as a transformative approach for battery thermal management systems (BTMS), offering…
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Artikel Jurnal
Improving forecasting accuracy of renewable energy generation via periodicity-aware deep learning framework with Time2Vec
Accurate forecasting of photovoltaic (PV) and wind power generation is vital for reliable renewable energy operations. However, their differing temporal characteristics, especially in periodicity, pose challenges for unified prediction models. This paper proposes a periodicity-aware hybrid deep…
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Artikel Jurnal
Economical vehicle-side strategies for an electric bus charging station in vehicle-to-grid services based on reinforcement learning
The power batteries of idle electric vehicles can be utilized as distributed energy storage units to deliver Vehicle-to-Grid (V2G) services, enabling bidirectional energy flow between the grid and EV batteries. Existing studies on the economic feasibility of V2G focus on conventional passenger…