A5002156207- Advanced Battery Technologies Research
- Advancements in Battery Materials
- Electric Vehicles and Infrastructure
- Smart Grid Energy Management
- Extraction and Separation Processes
- Energy and Environment Impacts
- Transportation and Mobility Innovations
- Microgrid Control and Optimization
- Advanced Battery Materials and Technologies
- Photovoltaic System Optimization Techniques
- Advanced battery technologies research
- Energy, Environment, and Transportation Policies
- Recycling and Waste Management Techniques
- Molecular Communication and Nanonetworks
- Advanced Data Processing Techniques
- Real-time simulation and control systems
- MXene and MAX Phase Materials
- Acupuncture Treatment Research Studies
- Building Energy and Comfort Optimization
- IoT-based Smart Home Systems
- Reliability and Maintenance Optimization
- Facial Nerve Paralysis Treatment and Research
- Conducting polymers and applications
- Medical Imaging and Analysis
- Greenhouse Technology and Climate Control
Tsinghua–Berkeley Shenzhen Institute
2023-2025
Tsinghua University
2023-2025
University of California, Berkeley
2025
Fudan University
2021
Shanghai Institute of Computing Technology
2021
Reuse and recycling of retired electric vehicle (EV) batteries offer a sustainable waste management approach but face decision-making challenges. Based on the process-based life cycle assessment method, we present strategy to optimize pathways battery treatments economically environmentally. The is applied various reuse scenarios with capacity configurations, including energy storage systems, communication base stations, low-speed vehicles. Hydrometallurgical, pyrometallurgical, direct...
The paper proposes a physics-informed model to predict battery lifetime trajectories by computing thermodynamic and kinetic parameters, saving costly data that has not been established for sustainable manufacturing, reuse, recycling.
Unsorted retired batteries with varied cathode materials hinder the adoption of direct recycling due to their cathode-specific nature. The surge in necessitates precise sorting for effective recycling, but challenges arise from varying operational histories, diverse manufacturers, and data privacy concerns collaborators (data owners). Here we show, a unique dataset 130 lithium-ion spanning 5 7 federated machine learning approach can classify these without relying on past data, safeguarding...
We develop an adaptive machine-learning framework that addresses cross-operation-condition battery lifetime prediction, particularly under extreme conditions. This uses correlation alignment to correct feature divergence fast-charging and extremely report a linear between adaptability prediction accuracy. Higher generally leads better accuracy, aiding efficient engineering. Our analysis shows the first 120 cycles provide sufficient information for extending data 320 only marginally improves...
The climate crisis necessitates decarbonization solutions that transform energy systems across all scales. While attention today focuses on utility-scale power systems, mini-or metro-scale grids, and at end-use device efficiency, the individual user scale remains underexplored. Just as with efficiency innovations tailored to micro-environments, body-scale savings offer new opportunities alongside technological behavioral challenges. Here we propose a technique suite of potential focused...
Rapid and accurate state of health (SOH) estimation retired batteries is a crucial pretreatment for reuse recycling. However, data-driven methods require exhaustive data curation under random SOH charge (SOC) retirement conditions. Here, we show that the generative learning-assisted promising in alleviating scarcity heterogeneity challenges, validated through pulse injection dataset 2700 lithium-ion battery samples, covering 3 cathode material types, physical formats, 4 capacity designs,...
V2G (Vehicle to Grid) technology can adjust the grid load through unified control of charging and discharging electric vehicles (EVs), achieve peak shaving valley filling smooth fluctuations. Aiming at random uncertain problem EV users travel behavior decision-making, this paper proposes a multi-objective dispatching strategy based on user behavior. First, model was established questionnaire surveys, effective effect simulated Monte Carlo simulation. Then, combined with regional daily curve...
To achieve the goal of carbon neutrality, demand for energy saving by residential sector has witnessed a soaring increase. As promising paradigm to monitor and manage loads, existing studies on non-intrusive load monitoring (NILM) either lack scalability real-world cases or pay unaffordable attention identification accuracy. This paper proposes high accuracy, ultra-sparse sample, real-time computation based NILM method appliances. The includes three steps: event detection, feature extraction...
Battery screening is the key segment of secondary applications. The benchmark for conventional methods mainly based on series connection and makes parameter difference as index a gold standard. However, because self-balancing current in parallel connection, existence certain degree allowed may not be best option, which leads to lower efficiency due higher uniform parameters. This work firstly identifies boundary provides ideal working point (IWP), related maximum capacity utilization...
Optimal operation of energy storage systems plays an important role in enhancing their lifetime and efficiency. This paper combines the concepts cyber–physical system (CPS) multi-objective optimization into control structure hybrid (HESS). Owing to time-varying characteristics HESS, combining real-time data with physical models via CPS can significantly promote performance HESS. The model designed this improve utilization supercapacitors, reduce consumption, prevent state charge (SOC) HESS...
Power systems optimization is generally subject to the compromise between performance and cost. The 2021 Texas grid outage illustrates worldwide dangers for regional-centralized power grid, with comparable advantages safety flexibility distributed energy system. storage of household batteries helps balance load increase system stability flexibility. However, battery still not widely used today because its high costs. Currently, research on increasing applicability focused largely optimizing...
In view of the load fluctuation caused by large-scale access electric vehicles to power grid, this paper proposes an vehicle cluster dispatching strategy considering demand response, which uses Vehicle Grid (V2G) technology control charging and discharging behavior provide auxiliary services for system. Firstly, V2G model EV is established according travel regular characteristics users. Secondly, combined with regional daily curve time-of-use price, multi-objective optimal stabilize grid...
The reliable operation of photovoltaic (PV) power generation systems is related to the security and stability grid focus current research. At present, reliability evaluation PV mostly calculated by applying standard failure rate each component, ignoring impact thermal environment changes on rate. This paper will use fault tree theory establish assessment method plants, model plants working in variable through hardware-in-the-loop simulation system, analyze influence characteristics...
As a mobile energy storage unit, the large-scale development of electric vehicle (EV) will make application V2G (Vehicle-to-Grid) technology possible: grid peak and valley load shifting can be achieved through charging discharging. However, driving patterns user behavior are highly random uncertain. In order to solve impact on participation in operation, this paper establishes model based questionnaire survey traffic travel data. Then discharging behaviors regulation under different modes is...
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