Impedance Spectra Of Batteries Research Articles

Design and Validation of Lifetime Prediction Model for Lithium-Thiocarbonyl Chloride Batteries Based on Accelerated Aging Experiments

The purpose of this study is to establish a life prediction model of lithium-thiocarbonyl chloride batteries by semi-empirical method. In the experiment, accelerated life tests on several groups of batteries at different temperatures were conducted. After a period of operation in the range from 25 °C to 74 °C, it was found that the higher the temperature, the less the remaining capacity of the batteries. According to the study of the battery aging mechanism, the characteristic parameter impedance of an aging battery would change exponentially with the increase of storage time and environmental temperature. The established life prediction model showed that the change in battery impedance spectrum had a good law, which made it possible to predict the state of charge (SOC) of the battery according to the local change characteristics of the electrochemical impedance spectroscopy (EIS) spectrum. The experimental data were compared with the fitted prediction curve, and the maximum deviation of the prediction was only 4.1036%, which indicated that the constructed model had high accuracy.

Deep neural network based battery impedance spectrum prediction using only impedance at characteristic frequencies

Electrochemical impedance spectroscopy can be used for characterizing and monitoring the state of batteries. However, the difficulty in the onboard acquisition limits its wide applications. This work proposes a new method to obtain the impedance spectrum by using convolutional neural network, which uses the impedance measured at several characteristic frequencies as input. The characteristic frequencies are determined according to the time constants corresponding to the characteristic peaks and valleys of contact polarization and solid electrolyte interphase growth processes from the distribution of relaxation time. The proposed method is validated based on the dataset which contains the impedance spectra of eight batteries over the whole life cycle. The predictions coincide with the ground truth, with a maximum root mean square error of 0.93 mΩ. The developed method can also be quickly adapted to acquire the impedance spectrum of other batteries with different chemistries and be used for predictions of various battery states based on the transfer learning approach.

Battery impedance spectrum prediction from partial charging voltage curve by machine learning

Electrochemical impedance spectroscopy (EIS) is an effective technique for Lithium-ion battery state of health diagnosis, and the impedance spectrum prediction by battery charging curve is expected to enable battery impedance testing during vehicle operation. However, the mechanistic relationship between charging curves and impedance spectrum remains unclear, which hinders the development as well as optimization of EIS-based prediction techniques. In this paper, we predicted the impedance spectrum by the battery charging voltage curve and optimized the input based on electrochemical mechanistic analysis and machine learning. The internal electrochemical relationships between the charging curve, incremental capacity curve, and the impedance spectrum are explored, which improves the physical interpretability for this prediction and helps define the proper partial voltage range for the input for machine learning models. Different machine learning algorithms have been adopted for the verification of the proposed framework based on the sequence-to-sequence predictions. In addition, the predictions with different partial voltage ranges, at different state of charge, and with different training data ratio are evaluated to prove the proposed method have high generalization and robustness. The experimental results show that the proper partial voltage range has high accuracy and converges to the findings of the electrochemical analysis. The predicted errors for impedance spectrum are less than 1.9 mΩ with the proper partial voltage range selected by the corelative analysis of the electrochemical reactions inside the batteries. Even with the voltage range reduced to 3.65–3.75 V, the predictions are still reliable with most RMSEs less than 4 mΩ.

On the design of multisine signals for maintaining stability condition in impedance spectroscopy measurements of batteries

For measuring the impedance spectra of batteries, several challenges should be overcome to maintain the stability condition, especially at low frequencies in the mHz range. Even if the sine sweep signals realize the highest signal power, they lead to a severe stability problem at low frequencies in the mHz region. In this paper, we propose a novel design method for multisine excitation signals, which reduces measurement time and maintains battery stability. The novel excitation signals are structured in a dummy interval for considering the transient behavior of the battery and three folds of a multisine signal with an optimized crest factor, frequency bins, and measurement time. The system stability is evaluated by a consistency check based on the Linear Kramers–Kronig (LKK) method. The results show that the novel excitation signals outperform the often-used sinusoidal sweep signals by maintaining the stability condition during impedance measurements even at low frequencies in the mHz range. For example, for a signal with six frequencies/decade from 10 mHz to 1 kHz, a root means squares error of the LKK of 31.70 ppm could be realized instead of 201.21 ppm for the sine sweep, and the measurement time could be reduced to 315 s from 1440 s.

Electrochemical impedance spectroscopy characterization of LiFePO4 cathode material with carboxymethylcellulose and poly-3,4-ethylendioxythiophene/polystyrene sulfonate

Novel cathode material compositions based on lithium iron phosphate (LFP) were prepared using conducting polymer dispersion poly-3,4-ethylenedioxythiopene/polystyrene sulfonate (PEDOT:PSS) and water-based carboxymethylcellulose (СМС) as a binder solely and in mixture PEDOT:PSS/СМС. The electrochemical properties of materials in lithium-ion batteries were investigated by galvanostatic charge-discharge curves and by electrochemical impedance spectroscopy and the results were compared with conventional PVDF-bound material. Our best materials consisting of 92wt% of C-LiFePO4, 4wt% of carbon black and 4wt% of conducting polymer binder exhibited excellent rate capability with discharge capacity 148mAhg−1 (at 0.2C, normalized by the electrode mass), 143mAhg−1 at 1C and 128mAhg−1 at 5C as well as good cycling stability at 1C (less than 1% decay after 100 cycles).Impedance spectra of batteries with different compositions were measured and analyzed. Comparison of kinetic parameters obtained for different electrodes revealed main factors responsible for significant improvement of electrochemical performance of LFP-based cathode materials modified with conducting polymer in comparison with conventional electrode. The transition from conventional PVDF-bound LFP-based cathode composition to modified by conducting polymer PEDOT:PSS/CMC was found very effective. The electrode with optimal composition showed substantial decrease of interfacial charge transfer resistance for 30 times, and decrease of Warburg diffusion resistance.The mechanism of positive influence of conducting binder on electrochemical properties of cathode material is discussed.

Online impedance spectroscopy of lead acid batteries for storage management of a standalone power plant

This paper presents a contribution to implementation of hybrid power plants in rural areas without electricity in Senegal. Wind and photovoltaic generators coupling is used to benefit from renewable energy resources in this country. Lead acid storage batteries are coupled with the generators to ensure smoothness of the electricity generation. This work is focused in particular on the development of a low cost online impedance spectroscopy method to address the problem of limited lifetime of batteries and the difficulties of their maintenance in isolated areas. Control of static converter associated with the battery is adapted to integrate the functionality of characterization of batteries by impedance spectroscopy. An experimental platform developed in the laboratory has validated the method for online measurement of battery impedance spectrum and to initiate a phase of data monitoring.

Thermal behaviors of Ni-MH batteries using a novel impedance spectroscopy

In this paper, a novel impedance spectroscopy was used to describe the thermal behaviors of Ni-MH batteries. The impedance functions were derived similarly to electric impedance functions. The square of current was treated as a current equivalent and heat-flow as a voltage equivalent. The impedance spectra of batteries during charge showed that the combination of hydrogen and oxygen increased rapidly when charge rate was higher than 0.5 C. Thermal runaway might happen when battery was charged at temperature above 348 K even at a low charge rate. The cycling test showed that the charge efficiency of battery was the highest after cycling at high-rate for 10–100 cycles and decreased after more cycles. Different batteries showed different thermal behaviors which may be caused by the different structures of batteries.

Electrochemical characteristics of the lithium/carbon monofluoride battery and its component half-cells

The impedance spectrum of the Matsushita lithium/carbon monofluoride battery was studied extensively as a function of load, temperature, state of charge, and time after discharge. Resolution of the battery impedance spectrum into frequency domains characteristic of the electrolyte, the anode, and the cathode permitted the polarization and kinetic parameters of the individual battery electrodes to be measured. Most of the battery voltage loss is attributed to the carbon monofluoride cathode. Comparisons of the interfacial electrochemical properties of lithium half-cells in the battery electrolyte (1.0 mol dm−3 LiBF4/γ-butyrolactone) with those of thein situ battery anode show that the battery anode is coated with a film. Attempts to correlate the high-frequency (> 1 Hz) parameters of the battery impedance with state of charge proved unsuccessful.