scholarly journals Impedance-based forecasting of battery performance amid uneven usage

2021 ◽  
Author(s):  
Penelope Jones ◽  
Ulrich Stimming ◽  
Alpha Lee
Keyword(s):  
Machine Learning ◽  
Electrochemical Impedance ◽  
Model Performance ◽  
Lithium Ion ◽  
Constant Current ◽  
Battery Management ◽  
Test Error ◽  
The Future ◽  
Constant Current Charging ◽  
Probabilistic Machine Learning

Accurate forecasting of lithium-ion battery performance is important for easing consumer concerns about the safety and reliability of electric vehicles. Most research on battery health prognostics focuses on the R&D setting where cells are subjected to the same usage patterns, yet in practice there is great variability in use across cells and cycles, making forecasting much more challenging. Here, we address this challenge by combining electrochemical impedance spectroscopy (EIS), a non-invasive measurement of battery state, with probabilistic machine learning. We generated a dataset of 40 commercial lithium-ion coin cells cycled under multistage constant current charging/discharging, with currents randomly changed between cycles to emulate realistic use patterns. We show that future discharge capacities can be predicted with calibrated uncertainties, given the future cycling protocol and a single EIS measurement made just before charging, and without any knowledge of usage history. Our method is data-efficient, requiring just eight cells to achieve a test error of less than 10%, and robust to dataset shifts. Our model can forecast well into the future, attaining a test error of less than 10% when projecting 32 cycles ahead. Further, we find that model performance can be boosted by 25% by augmenting EIS with additional features derived from historical capacity-voltage curves. Our results suggest that battery health is better quantified by a multidimensional vector rather than a scalar State of Health, thus deriving informative electrochemical `biomarkers' in tandem with machine learning is key to predictive battery management and control.

scholarly journals Determination of the Distribution of Relaxation Times by Means of Pulse Evaluation for Offline and Online Diagnosis of Lithium-Ion Batteries

Batteries ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 36
Author(s):  
Erik Goldammer ◽  
Julia Kowal
Keyword(s):  
Lithium Ion Batteries ◽  
Electrochemical Impedance ◽  
Sampling Rate ◽  
Relaxation Times ◽  
Low Frequency ◽  
Lithium Ion ◽  
Battery Management ◽  
Time Constants ◽  
Time Domain Data ◽  
Aging Study

The distribution of relaxation times (DRT) analysis of impedance spectra is a proven method to determine the number of occurring polarization processes in lithium-ion batteries (LIBs), their polarization contributions and characteristic time constants. Direct measurement of a spectrum by means of electrochemical impedance spectroscopy (EIS), however, suffers from a high expenditure of time for low-frequency impedances and a lack of general availability in most online applications. In this study, a method is presented to derive the DRT by evaluating the relaxation voltage after a current pulse. The method was experimentally validated using both EIS and the proposed pulse evaluation to determine the DRT of automotive pouch-cells and an aging study was carried out. The DRT derived from time domain data provided improved resolution of processes with large time constants and therefore enabled changes in low-frequency impedance and the correlated degradation mechanisms to be identified. One of the polarization contributions identified could be determined as an indicator for the potential risk of plating. The novel, general approach for batteries was tested with a sampling rate of 10 Hz and only requires relaxation periods. Therefore, the method is applicable in battery management systems and contributes to improving the reliability and safety of LIBs.

Synthesis and Electrochemical Properties of Spherical LiFePO4/C Composite via Spray Drying

2015 ◽  
Vol 1120-1121 ◽  
pp. 554-558 ◽  
Author(s):  
Juan Mei Wang ◽  
Bing Ren ◽  
Ying Lin Yan ◽  
Qing Zhang ◽  
Yan Wang
Keyword(s):  
Diffusion Coefficient ◽  
Electrochemical Properties ◽  
Spray Drying ◽  
Electrochemical Impedance ◽  
Retention Rate ◽  
Lithium Ion ◽  
Constant Current ◽  
Ion Diffusion ◽  
Electrochemical Tests ◽  
Li Ion

In this work, spherical LiFePO4/C composite had been synthesized by co-precipitation and spray drying method. The structure, morphology and electrochemical properties of the samples were characterized by X-ray diffraction (XRD), scanning electron micrograph (SEM), transmission electron microscope (TEM), constant current charge-discharge tests and electrochemical impedance spectroscopy (EIS) tests. The spherical LiFePO4/C particles consisted of a number of smaller grains. The results showed that the morphology of LiFePO4/C particles seriously affected the Li-ion diffusion coefficient and electrochemical properties of lithium ion batteries. Electrochemical tests revealed the spherical LiFePO4/C composite had excellent Li-ion diffusion coefficient which was calculated to be 1.065×10-11 cm2/s and discharge capacity of 149 (0.1 C), 139 (0.2 C), 133 (0.5 C), 129 (1 C) and 124 mAhg-1(2 C). After 50 cycles, the capacity retention rate was still 93.5%.

scholarly journals A Comparative Study of Charging Voltage Curve Analysis and State of Health Estimation of Lithium-ion Batteries in Electric Vehicle

2019 ◽  
Vol 2 (4) ◽  
pp. 263-275 ◽  
Author(s):  
Xuebing Han ◽  
Xuning Feng ◽  
Minggao Ouyang ◽  
Languang Lu ◽  
Jianqiu Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Electrode Materials ◽  
Lithium Ion ◽  
Curve Analysis ◽  
Constant Current ◽  
Battery Management ◽  
State Of Health ◽  
Voltage Curve ◽  
Battery Capacity ◽  
Li Ion

AbstractLithium-ion (Li-ion) cells degrade after repeated cycling and the cell capacity fades while its resistance increases. Degradation of Li-ion cells is caused by a variety of physical and chemical mechanisms and it is strongly influenced by factors including the electrode materials used, the working conditions and the battery temperature. At present, charging voltage curve analysis methods are widely used in studies of battery characteristics and the constant current charging voltage curves can be used to analyze battery aging mechanisms and estimate a battery’s state of health (SOH) via methods such as incremental capacity (IC) analysis. In this paper, a method to fit and analyze the charging voltage curve based on a neural network is proposed and is compared to the existing point counting method and the polynomial curve fitting method. The neuron parameters of the trained neural network model are used to analyze the battery capacity relative to the phase change reactions that occur inside the batteries. This method is suitable for different types of batteries and could be used in battery management systems for online battery modeling, analysis and diagnosis.

Development of dispersive XAFS system for analysis of time-resolved spatial distribution of electrode reaction

2015 ◽  
Vol 22 (5) ◽  
pp. 1227-1232 ◽  
Author(s):  
Misaki Katayama ◽  
Ryota Miyahara ◽  
Toshiki Watanabe ◽  
Hirona Yamagishi ◽  
Shohei Yamashita ◽  
...  
Keyword(s):  
Lithium Ion ◽  
Vertical Axis ◽  
Electrode Reaction ◽  
Constant Current ◽  
Array Detector ◽  
X Rays ◽  
Time Resolved ◽  
X Ray ◽  
Spatially Resolved ◽  
Constant Current Charging

Apparatus for a technique based on the dispersive optics of X-ray absorption fine structure (XAFS) has been developed at beamline BL-5 of the Synchrotron Radiation Center of Ritsumeikan University. The vertical axis of the cross section of the synchrotron light is used to disperse the X-ray energy using a cylindrical polychromator and the horizontal axis is used for the spatially resolved analysis with a pixel array detector. The vertically dispersive XAFS (VDXAFS) instrument was designed to analyze the dynamic changeover of the inhomogeneous electrode reaction of secondary batteries. The line-shaped X-ray beam is transmitted through the electrode sample, and then the dispersed transmitted X-rays are detected by a two-dimensional detector. An array of XAFS spectra in the linear footprint of the transmitted X-ray on the sample is obtained with the time resolution of the repetition frequency of the detector. Sequential measurements of the space-resolved XAFS data are possible with the VDXAFS instrument. The time and spatial resolutions of the VDXAFS instrument depend on the flux density of the available X-ray beam and the size of the light source, and they were estimated as 1 s and 100 µm, respectively. The electrode reaction of the LiFePO4lithium ion battery was analyzed during the constant current charging process and during the charging process after potential jumping.

Conduction Properties of PTMSPMA-PEO and its Application as Polymer Electrolyte in LiFePO4 Batteries

2015 ◽  
Vol 827 ◽  
pp. 125-130 ◽  
Author(s):  
Sahrul Hidayat ◽  
Orina Amelia ◽  
Iman Rahayu ◽  
Fitrilawati
Keyword(s):  
Polymer Electrolyte ◽  
Room Temperature ◽  
Solution Method ◽  
Ionic Conduction ◽  
Electrochemical Impedance ◽  
Sol Gel ◽  
Lithium Ion ◽  
Constant Current ◽  
Coin Cell ◽  
Conduction Properties

The conduction properties of polymer composite PTMSPMA-PEO as electrolyte in lithium-ion batteries has been investigated. The gel polymer of PTMSPMA was synthesized by sol-gel method using 3-(Trimethoxysilyl)-propyl-methacrylate as monomer. The Composite of PTMSPMA-PEO with various composition (50:50, 60:40, 80:20; wt%) was made by solution method. The polymer electrolyte was composed of LiClO4salt dissolved in propylene carbonate and mixed with PTMSPMA-PEO. The ionic conduction of polymer electrolyte was characterized by electrochemical impedance spectroscopy. The battery performance of polymer electrolyte was estimated with coin cell, where LiFePO4was used as cathode and graphite was use as anode. The high ionic conductivity of 6.67 x10-3S/cm has been observed for the composition of PTMSPMA : PEO 60:40 (wt%) in room temperature. The performance of cell battery was investigated by charge-discharge using constant current 0,1 mA/cm2. The operational voltage of cell battery is around 1 V until 2.2 Volt with Columbic efficiency around 60%.

Substituted phosphonium cation based electrolytes for nonaqueous electrical double-layer capacitors

2010 ◽  
Vol 25 (8) ◽  
pp. 1447-1450 ◽  
Author(s):  
H. Kurig ◽  
A. Jänes ◽  
E. Lust
Keyword(s):  
Double Layer ◽  
Electrical Double Layer ◽  
Electrochemical Impedance ◽  
Cell Voltage ◽  
Constant Current ◽  
Electrochemical Characteristics ◽  
Double Layer Capacitor ◽  
Constant Current Charging ◽  
Double Layer Capacitors ◽  
Carbide Derived Carbon

Tetrakis(diethylamino)phosphonium tetrafluoroborate (TDENPBF4), tetrakis(diethylamino)phosphonium hexafluorophosphate (TDENPPF6), and tetrakis(dimethylamino)phosphonium tetrafluoroborate (TDMNPBF4) in acetonitrile (AN) have been studied as electrical double-layer capacitor electrolytes in a two-electrode test cell using titanium carbide derived carbon, C(TiC), as an electrode material. Electrochemical characteristics for C(TiC)|1 M TDENPBF4 + AN, C(TiC)|1 M TDENPPF6 + AN, and C(TiC)|1 M TDMNPBF4 + AN interfaces have been obtained by cyclic voltammetry, constant current charging/discharging, and electrochemical impedance spectroscopy. High-capacitance (85 °F/g) and gravimetric power (269 kW/kg) have been achieved at cell voltage 3.2 V. Data obtained have been compared with results published previously.

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