School of Mechanical Engineering, Shanghai Jiao Tong University

A Soft-Switching Bidirectional DC–DC Converter for the Battery Super-Capacitor Hybrid Energy Storage System [J]. IEEE Transactions on Industrial Electronics, 2018, 65 (10):7856-7865.

Fault Diagnosis and Early Warning of Energy Storage Devices in

This paper analyzes the current fault diagnosis and early warning technology for energy storage equipment, points out the limitations of existing methods and the application potential of

In-Situ Early Gas Detection for Lithium-Ion Batteries in Energy Storage

In the experiment, a LiFePO 4 (LFP) cell was heated with a heating rate of 60 W to stimulate a gradual thermal runaway. The battery surface temperature, ambient temperature, and

Target Detection Method for Energy Storage and Power Supply

Abstract: A target detection method for energy storage power supply service cabin based on improved YOLOv5s is proposed to address the issues of low accuracy and low efficiency in target

Battery 2030+ Excellence Seminar The Ageing of Li-ion

His main research interests are Battery degradation and lifetime predication, new electrode/electrolyte materials for Li/Na-ion batteries, in-situ NMR/MRI/NI techniques in electrochemical energy...

Multi-level anomaly detection of lithium battery energy storage system

This paper proposes a three-stage anomaly detection method based on statistics and density concepts to provide real-time potential fault prediction of lithium battery energy storage systems. Considering

Quantitative Analysis of the Coupled Mechanisms of

Here, we used dynamic electrochemical impedance spectroscopy (DEIS), mass spectrometry titration (MST), nuclear magnetic resonance (NMR), and gas chromatography–mass

Off-Gas Detection System Passes Tests

The primary aim of the testing was to assess the effectiveness of an off-gas detection system in providing early warning for the mitigation of TR in Li-ion battery systems.

Design of a visual detection algorithm for battery swelling faults

A realistic deep-learning framework for electric vehicle (EV) LiB anomaly detection that overcomes the limitations of state-of-the-art fault detection models, including deep learning ones and

Gas venting behavior and early detection performance in energy

The present study aims to numerically examine the gas venting behavior and early detection performance in energy storage system (ESS) modules under various thermal runaway