A5101407209- Advanced Battery Technologies Research
- Advancements in Battery Materials
- Advanced Battery Materials and Technologies
- Electric Vehicles and Infrastructure
- Fuel Cells and Related Materials
- Extraction and Separation Processes
- Electric and Hybrid Vehicle Technologies
- Advanced battery technologies research
- Recycling and Waste Management Techniques
- Electrocatalysts for Energy Conversion
- Advancements in Solid Oxide Fuel Cells
- Hybrid Renewable Energy Systems
- Fault Detection and Control Systems
- Electronic and Structural Properties of Oxides
- Reliability and Maintenance Optimization
- Hydrogen Storage and Materials
- Vehicle emissions and performance
- Thermodynamic and Exergetic Analyses of Power and Cooling Systems
- High-Temperature Coating Behaviors
- Risk and Safety Analysis
- Advanced Thermodynamic Systems and Engines
- Sensor Technology and Measurement Systems
- Microgrid Control and Optimization
- Semiconductor materials and devices
- Nuclear Materials and Properties
Tsinghua University
2016-2025
Leatherhead Food Research
1966
The online estimation of battery state-of-health (SOH) is an ever significant issue for the intelligent energy management autonomous electric vehicles. Machine-learning based approaches are promising SOH estimation. This paper proposes a machine-learning algorithm Li-ion battery. A predictive diagnosis model used in established on support vector machine (SVM). vectors, which reflects intrinsic characteristics battery, determined from charging data fresh cells. Furthermore, coefficients SVMs...
Abstract Lithium-ion batteries connected in series are prone to be overdischarged. Overdischarge results various side effects, such as capacity degradation and internal short circuit (ISCr). However, most of previous research on the overdischarge a cell was terminated when voltage dropped 0 V, leaving further impacts unclear. This paper investigates entire process large-format lithium-ion by discharging −100% state charge (SOC). A significant platform is observed at approximately −12% SOC...
Lithium plating leads to severe capacity fading and possible safety problems in lithium-ion batteries. Thus, non-destructive detection methods for lithium are critical safe reliable operation of In this paper, an electrochemical model incorporated with stripping reactions is established investigate the plating-stripping process at low temperature. The validated different current rates temperatures can successfully predict characteristic voltage plateau during rest period after temperature...
Battery safety, at the foundation of fast charging, is critical to application lithium-ion batteries, especially for high energy density cells applied in electric vehicles. In this paper, an earlier thermal runaway after charging illustrated. Under condition, reaction between plated lithium and electrolyte revealed be mechanism triggering. The proved by accelerated rate calorimetry tests partial cells, which determine triggering reactions anode-electrolyte thermodynamic system. reactants...
The intrinsic poor thermal stability of layered LiNixCoyMn1-x-yO2 (NCM) cathodes and the exothermic side reactions triggered by associated oxygen release are main safety threats for their large-scale implantation. In NCM family, it is widely accepted that Ni troublemaker, while Mn has long been considered as a structure stabilizer, whereas role Co remains elusive. Here, via Co/Mn exchange in Ni-rich LiNi0.83Co0.11Mn0.06O2 cathode, we demonstrate chemical structural deep delithiated...
Accurate evaluation of Li-ion battery (LiB) safety conditions can reduce unexpected cell failures, facilitate deployment, and promote low-carbon economies. Despite the recent progress in artificial intelligence, anomaly detection methods are not customized for or validated realistic settings due to complex failure mechanisms lack real-world testing frameworks with large-scale datasets. Here, we develop a deep-learning framework electric vehicle (EV) LiB detection. It features dynamical...
The lithium ion batteries are having increasing energy densities, meeting the requirement from industry, especially for electric vehicles. However, a cell with higher density is more prone to thermal runaway. We analyze key characteristics during runaway help better define battery Three characteristic temperatures regarded as common features of all kinds batteries. underlying mechanisms three have been investigated by analysis. conclusion analysis set benchmarks evaluating behaviors...