Research on interactive multi‐model fault diagnosis method of Li‐ion battery based on noise suppression

2021 ◽  
Author(s):  
Yongchao Wang ◽  
Dawei Meng ◽  
Ran Li ◽  
Yongqin Zhou ◽  
Xiaoyu Zhang
Keyword(s):  
Fault Diagnosis ◽  
Noise Suppression ◽  
Li Ion Battery ◽  
Diagnosis Method ◽  
Li Ion

Multi-Fault Diagnosis of Li-ion Battery Pack Based on Hybrid System

2021 ◽  
pp. 1-1
Author(s):  
Ziqiang Chen ◽  
Changwen Zheng ◽  
Tiantian Lin ◽  
Qi Yang
Keyword(s):  
Fault Diagnosis ◽  
Hybrid System ◽  
Battery Pack ◽  
Li Ion Battery ◽  
Li Ion

scholarly journals A Review on Fault Mechanism and Diagnosis Approach for Li-Ion Batteries

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Chao Wu ◽  
Chunbo Zhu ◽  
Yunwang Ge ◽  
Yongping Zhao
Keyword(s):  
Fault Diagnosis ◽  
Service Life ◽  
Research And Development ◽  
Storage Device ◽  
Li Ion Batteries ◽  
Li Ion Battery ◽  
Li Ion ◽  
Fault Mechanism ◽  
Energy And Power Density ◽  
Diagnosis Approach

Li-ion battery has attracted more and more attention as it is a promising storage device which has long service life, higher energy, and power density. However, battery ageing always occurs during operation and leads to performance degradation and system fault which not only causes inconvenience, but also risks serious consequences such as thermal runaway or even explosion. This paper reviews recent research and development of ageing mechanisms of Li-ion batteries to understand the origins and symptoms of Li-ion battery faults. Common ageing factors are covered with their effects and consequences. Through ageing tests, relationship between performance and ageing factors, as well as cross-dependence among factors can be quantified. Summary of recent research about fault diagnosis technology for Li-ion batteries is concluded with their cons and pros. The suggestions on novel fault diagnosis approach and remaining challenges are provided at the end of this paper.

scholarly journals Diagnosis Method for Li-Ion Battery Fault Based on an Adaptive Unscented Kalman Filter

Energies ◽  
2017 ◽  
Vol 10 (11) ◽  
pp. 1810 ◽  
Author(s):  
Changwen Zheng ◽  
Yunlong Ge ◽  
Ziqiang Chen ◽  
Deyang Huang ◽  
Jian Liu ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Unscented Kalman Filter ◽  
Li Ion Battery ◽  
Adaptive Unscented Kalman Filter ◽  
Diagnosis Method ◽  
Li Ion

Electrochemical Model Based Fault Diagnosis of Li-Ion Battery Using Fuzzy Logic

2014 ◽  
Author(s):  
Vinay K. S. Muddappa ◽  
Sohel Anwar
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
High Energy ◽  
High Energy Density ◽  
Li Ion Battery ◽  
Model Based ◽  
Internal States ◽  
Diagnosis Method ◽  
Li Ion ◽  
Electrochemical Model

There is a strong urge for advanced diagnosis method, especially in high power battery packs and high energy density cell design applications, such as electric vehicle (EV) and hybrid electric vehicle segment, due to safety concerns. Accurate and robust diagnosis methods are required in order to optimize battery charge utilization and improve EV range. Battery faults cause significant model parameter variation affecting battery internal states and output. This work is focused on developing diagnosis method to reliably detect various faults inside lithiumion cell using electrochemical model based observer and fuzzy logic algorithm, which is implementable in real-time. The internal states and outputs from battery plant model were compared against those from the electrochemical model based observer to generate the residuals. These residuals and states were further used in a fuzzy logic based residual evaluation algorithm in order to detect the battery faults. Simulation results show that the proposed methodology is able to detect various fault types including overcharge, over-discharge and aged battery quickly and reliably, thus providing an effective and accurate way of diagnosing Li-Ion battery faults.

Helicopter main reduction planetary gear fault diagnosis method based on SVDD

2020 ◽  
Vol 64 (1-4) ◽  
pp. 137-145
Author(s):  
Yubin Xia ◽  
Dakai Liang ◽  
Guo Zheng ◽  
Jingling Wang ◽  
Jie Zeng
Keyword(s):  
Fault Diagnosis ◽  
Planetary Gear ◽  
Gaussian Kernel ◽  
Support Vector ◽  
Support Vector Data Description ◽  
Vector Data ◽  
Energy Characteristics ◽  
Gear Fault ◽  
Channel Information ◽  
Diagnosis Method

Aiming at the irregularity of the fault characteristics of the helicopter main reducer planetary gear, a fault diagnosis method based on support vector data description (SVDD) is proposed. The working condition of the helicopter is complex and changeable, and the fault characteristics of the planetary gear also show irregularity with the change of working conditions. It is impossible to diagnose the fault by the regularity of a single fault feature; so a method of SVDD based on Gaussian kernel function is used. By connecting the energy characteristics and fault characteristics of the helicopter main reducer running state signal and performing vector quantization, the planetary gear of the helicopter main reducer is characterized, and simultaneously couple the multi-channel information, which can accurately characterize the operational state of the planetary gear’s state.

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