scholarly journals Assessing the Performance Degradation of Lithium-Ion Batteries Using an Approach Based on Fusion of Multiple Feature Parameters

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Anchen Wang ◽  
Ying Zhang ◽  
Hongfu Zuo
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Degradation Process ◽  
Gaussian Mixture ◽  
Assessment Method ◽  
Performance Degradation ◽  
Discharge Voltage ◽  
Health State ◽  
Multiple Features ◽  
Feature Parameters

A method based on fusion of multiple features is proposed to assess and accurately describe the performance degradation of lithium-ion batteries in this paper. First, the discharge voltage signal of lithium-ion batteries under real-time monitoring is analyzed from the perspective of time domain and complexity to obtain the values of multiple features. Then, the multi-feature parameters undergo a spectral regression process to reduce the number of dimensions and to eliminate redundancy, and on the basis of this regression, a Gaussian mixture model is established to model the health state of batteries. Thus, the degree of lithium-ion battery performance degradation can be quantitatively assessed using the Bayesian inference-based distance metric. A case calculation experiment is carried out to verify the effectiveness of the method proposed in this paper. The experimental results demonstrate that, compared with other assessment methods, the performance degradation assessment method proposed in this paper can be used to monitor the degradation process of lithium-ion batteries more effectively and to improve the accuracy of condition monitoring of batteries, thereby providing powerful support for making maintenance decisions.

Modeling and Estimation for Advanced Battery Management

2019 ◽  
Vol 2 (1) ◽  
pp. 393-426 ◽  
Author(s):  
Xinfan Lin ◽  
Youngki Kim ◽  
Shankar Mohan ◽  
Jason B. Siegel ◽  
Anna G. Stefanopoulou
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
The State ◽  
Consumer Electronics ◽  
Accurate Estimation ◽  
Health State ◽  
Battery Management ◽  
Space Applications ◽  
Internal States ◽  
State Of Power

The commercialization of lithium-ion batteries enabled the widespread use of portable consumer electronics and serious efforts to electrify trans-portation. Managing the potent brew of lithium-ion batteries in the large quantities necessary for vehicle propulsion is still challenging. From space applications a billion miles from Earth to the daily commute of a hybrid electric automobile, these batteries require sophisticated battery management systems based on accurate estimation of battery internal states. This system is the brain of the battery and is responsible for estimating the state of charge, state of health, state of power, and temperature. The state estimation relies on accurate prediction of complex electrochemical, thermal, and mechanical phenomena, which increases the importance of model and parameter accuracy. Moreover, as the batteries age, how should the parameters of the model change to accurately represent the performance, and how can we leverage the limited sensor information from the measured terminal voltage and sparse surface temperatures available in a battery system? With a frugal sensor set, what is the optimal sensor placement? This article reviews estimation techniques and error bounds regarding sensor noise and modeling errors, and concludes with an outlook on the research that will be necessary to enable fast charging, repurposing of batteries for grid energy storage, degradation prediction, and fault detection.

scholarly journals Roller Bearing Performance Degradation Assessment Based on Fusion of Multiple Features of Electrostatic Sensors

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 824 ◽  
Author(s):  
Ying Zhang ◽  
Anchen Wang ◽  
Hongfu Zuo
Keyword(s):  
Monitoring System ◽  
Mixed Model ◽  
Roller Bearing ◽  
Degradation Process ◽  
Performance Degradation ◽  
Vibration Monitoring ◽  
Multiple Features ◽  
Roller Bearings ◽  
The Time Domain ◽  
Spectral Regression

This paper presents a new method to assess the performance degradation of roller bearings based on the fusion of multiple features, with the aim of improving the early degradation detection ability of the electrostatic monitoring system. At first, a set of feature parameters of the electrostatic monitoring system indicating the normal state of the bearings are extracted from the perspective of the time domain, frequency domain and complexity. Then, the parameter set is processed to reduce the dimensions and eliminate the redundancy using spectral regression. With the processed features, a Gaussian mixed model is established to gauge the health of the bearing, providing the distance value obtained using Bayesian inference as a quantitative indicator for assessing the performance degradation. The method is applied to access the life of a bearing in which the mechanic fatigue is artificially accelerated. The test results show that the proposed method can better reflect the degradation process of the bearing compared to other evaluation methods. This enables the electrostatic monitoring technique to detect the degradation of the bearing earlier than the vibration monitoring, providing a powerful tool for the condition monitoring of roller bearings.

scholarly journals Mathematical Models for the Performance Degradation of Lithium-Ion Batteries with Different Status of Charge (SOC) in Long-Term High Temperature Storage

2021 ◽  
Author(s):  
Zheng Wang ◽  
zhen Ma ◽  
Xiongfeng Hu ◽  
Ruirui Zhao ◽  
Junmin Nan
Keyword(s):  
High Temperature ◽  
Mathematical Models ◽  
Lithium Ion Batteries ◽  
Voltage Drop ◽  
Lithium Ion ◽  
Reversible Capacity ◽  
Performance Degradation ◽  
High Temperature Storage ◽  
Temperature Storage

Abstract Mathematical models to evaluate and predict the performance degradation of lithium-ion batteries (LIBs) with different status of charge (SOC) in long-term high-temperature storage which are also applicable for setting rational storage conditions (temperature, SOC, and time) of LIBs were established. Parameters including voltage drop (Delta V), reversible capacity (RC) loss, and internal impedance (IMP) increase of LIBs under different temperature (60, 45, and 25°C) are used to allow the model to clarify its function. According to the results obtained from commercial 18650 cylindrical batteries with LiNi0.33Co0.33Mn0.33O2 cathode, the mathematical relationship between Delta V and storage days (x) is fitted into a simple formula: Delta V =m.In(x)-n, and similarly, RC loss = m'.exp (n'.x) and IMP increase = m''.xn'' can also be acquired. In these formulas, m, n, m', n', m'' and n'' are constants when temperature and SOC are fixed. If only the temperature is fixed, the value of these constants can be derived into a function with SOC (y), respectively, while further plugging the function into the calculation formula of Delta V, RC loss, and IMP increase, respectively, allows the mathematical models to be set up.

General Discharge Voltage Information Enabled Health Evaluation for Lithium-Ion Batteries

2020 ◽  
pp. 1-1
Author(s):  
Zhongwei Deng ◽  
Xiaosong Hu ◽  
Xianke Lin ◽  
Le Xu ◽  
Yunhong Che ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Discharge Voltage ◽  
Health Evaluation

scholarly journals Binder-free SnO2–TiO2 composite anode with high durability for lithium-ion batteries

RSC Advances ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 6589-6595 ◽  
Author(s):  
Hyeonseok Yoo ◽  
Gibaek Lee ◽  
Jinsub Choi
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Performance Degradation ◽  
Composite Anode ◽  
High Durability ◽  
Binder Free

A binder-free SnO2–TiO2 composite, where SnO2 is encapsulated into hollow TiO2, is designed for inhibiting performance degradation for a stable LIB anode.

scholarly journals MoS2 with an intercalation reaction as a long-life anode material for lithium ion batteries

2016 ◽  
Vol 3 (4) ◽  
pp. 532-535 ◽  
Author(s):  
Zhe Hu ◽  
Qiannan Liu ◽  
Weiyi Sun ◽  
Weijie Li ◽  
Zhanliang Tao ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Anode Material ◽  
Layered Structure ◽  
Lithium Ion ◽  
Cycling Performance ◽  
Discharge Voltage ◽  
Intercalation Reaction ◽  
Carbon Modification ◽  
Long Life

MoS2 without carbon modification has achieved a long cycling performance by cutting off the terminal discharge voltage to preserve a layered structure.

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