scholarly journals Determination of the Differential Capacity of Lithium-Ion Batteries by the Deconvolution of Electrochemical Impedance Spectra

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 915
Author(s):  
Dongxu Guo ◽  
Geng Yang ◽  
Guangjin Zhao ◽  
Mengchao Yi ◽  
Xuning Feng ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Diffusion Processes ◽  
Electrochemical Impedance ◽  
Estimation Method ◽  
Lithium Ion ◽  
Joint Estimation ◽  
Frequency Resolution ◽  
Differential Capacity ◽  
Model Free ◽  
Incremental Capacity

Electrochemical impedance spectroscopy (EIS) is a powerful tool for investigating electrochemical systems, such as lithium-ion batteries or fuel cells, given its high frequency resolution. The distribution of relaxation times (DRT) method offers a model-free approach for a deeper understanding of EIS data. However, in lithium-ion batteries, the differential capacity caused by diffusion processes is non-negligible and cannot be decomposed by the DRT method, which limits the applicability of the DRT method to lithium-ion batteries. In this study, a joint estimation method with Tikhonov regularization is proposed to estimate the differential capacity and the DRT simultaneously. Moreover, the equivalence of the differential capacity and the incremental capacity is proven. Different types of commercial lithium-ion batteries are tested to validate the joint estimation method and to verify the equivalence. The differential capacity is shown to be a promising approach to the evaluation of the state-of-health (SOH) of lithium-ion batteries based on its equivalence with the incremental capacity.

Screening of retired lithium-ion batteries using incremental capacity charging curve based residual capacity estimation method for facilitating sustainable circular lithium-ion battery system

2021 ◽  
pp. 1-16
Author(s):  
Honglei Li ◽  
Liang Cong ◽  
Huazheng Ma ◽  
Weiwei Liu ◽  
Yelin Deng ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Estimation Method ◽  
Lithium Ion ◽  
Capacity Fade ◽  
Characteristic Parameters ◽  
Capacity Estimation ◽  
Capacity Curve ◽  
Residual Capacity ◽  
Remaining Capacity ◽  
Incremental Capacity

Abstract The rapidly growing deployment of lithium-ion batteries in electric vehicles is associated with a great waste of natural resource and environmental pollution caused by manufacturing and disposal. Repurposing the retired lithium-ion batteries can extend their useful life, creating environmental and economic benefits. However, the residual capacity of retired lithium-ion batteries is unknown and can be drastically different owing to various working history and calendar life. The main objective of this paper is to develop a fast and accurate capacity estimation method to classify the retired batteries by the remaining capacity. The hybrid technique of adaptive genetic algorithm and back propagation neural network is developed to estimate battery remaining capacity using the training set comprised of the selected characteristic parameters of incremental capacity curve of battery charging. Also, the paper investigated the correlation between characteristic parameters with capacity fade. The results show that capacity estimation errors of the proposed neural network are within 3%. Peak intensity of the incremental capacity curve has strong correlation with capacity fade. The findings also show that the translation of peak of the incremental capacity curve is strongly related with internal resistance.

scholarly journals Joint estimation of SOC and SOH for lithium-ion batteries based on EKF multiple time scales

2020 ◽  
Vol 1 (1) ◽  
pp. 107-120
Author(s):  
Peiqing Li ◽  
Huile Wang ◽  
Zixiao Xing ◽  
Kanglong Ye ◽  
Qipeng Li
Keyword(s):  
Lithium Ion Batteries ◽  
Estimation Method ◽  
Lithium Ion ◽  
Joint Estimation ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Content Type ◽  
Scale Theory ◽  
Multi Scale ◽  
Battery Capacity

PurposeThe operation state of lithium-ion battery for vehicle is unknown and the remaining life is uncertain. In order to improve the performance of battery state prediction, in this paper, a joint estimation method of state of charge (SOC) and state of health (SOH) for lithium-ion batteries based on multi-scale theory is designed.Design/methodology/approachIn this paper, a joint estimation method of SOC and SOH for lithium-ion batteries based on multi-scale theory is designed. The venin equivalent circuit model and fast static calibration method are used to fit the relationship between open-circuit voltage and SOC, and the resistance and capacitance parameters in the model are identified based on exponential fitting method. A battery capacity model for SOH estimation is established. A multi-time scale EKF filtering algorithm is used to estimate the SOC and SOH of lithium-ion batteries.FindingsThe SOC and SOH changes in dynamic operation of lithium-ion batteries are accurately predicted so that batteries can be recycled more effectively in the whole vehicle process.Originality/valueA joint estimation method of SOC and SOH for lithium-ion batteries based on multi-scale theory is accurately predicted and can be recycled more effectively in the whole vehicle process.

scholarly journals A Fast Online State of Health Estimation Method for Lithium-Ion Batteries Based on Incremental Capacity Analysis

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3333 ◽  
Author(s):  
Shaofei Qu ◽  
Yongzhe Kang ◽  
Pingwei Gu ◽  
Chenghui Zhang ◽  
Bin Duan
Keyword(s):  
Lithium Ion Batteries ◽  
Estimation Error ◽  
Estimation Method ◽  
Lithium Ion ◽  
Computation Time ◽  
Absolute Error ◽  
Capacity Analysis ◽  
State Of Health ◽  
Important Challenge ◽  
Incremental Capacity

Efficient and accurate state of health (SoH) estimation is an important challenge for safe and efficient management of batteries. This paper proposes a fast and efficient online estimation method for lithium-ion batteries based on incremental capacity analysis (ICA), which can estimate SoH through the relationship between SoH and capacity differentiation over voltage (dQ/dV) at different states of charge (SoC). This method estimates SoH using arbitrary dQ/dV over a large range of charging processes, rather than just one or a limited number of incremental capacity peaks, and reduces the SoH estimation time greatly. Specifically, this method establishes a black box model based on fitting curves first, which has a smaller amount of calculation. Then, this paper analyzes the influence of different SoC ranges to obtain reasonable fitting curves. Additionally, the selection of a reasonable dV is taken into account to balance the efficiency and accuracy of the SoH estimation. Finally, experimental results validate the feasibility and accuracy of the method. The SoH estimation error is within 5% and the mean absolute error is 1.08%. The estimation time of this method is less than six minutes. Compared to traditional methods, this method is easier to obtain effective calculation samples and saves computation time.

scholarly journals Nonlinear electrochemical impedance spectroscopy of lithium-ion batteries: Experimental approach, analysis, and initial findings

2018 ◽  
Author(s):  
Matthew D. Murbach ◽  
Victor Hu ◽  
Daniel T. Schwartz
Keyword(s):  
Charge Transfer ◽  
Electrochemical Impedance Spectroscopy ◽  
Impedance Spectroscopy ◽  
Lithium Ion Batteries ◽  
Diffusion Processes ◽  
Electrochemical Impedance ◽  
Second Harmonic ◽  
Lithium Ion ◽  
Mathematical Framework ◽  
High Symmetry

Nonlinear electrochemical impedance spectroscopy (NLEIS) is a moderate-amplitude extension to linear EIS that provides a sensitive and complementary whole-battery diagnostic for charge transfer kinetics, mass transport, and thermodynamics. We present the first full-frequency, second harmonic NLEIS spectra for lithium-ion batteries using commercially available, 1.5 Ah LiNMC|C cells. The mathematical framework for NLEIS shows, and experiments confirm, that moderate-amplitude input modulations can generate a second harmonic output that does not intrinsically corrupt the linear EIS response. Experimental measurements at varied states-of-charge (SoC) and states-of-health (SoH) are used to illustrate and compare NLEIS and EIS data. At low frequencies, the second harmonic NLEIS spectrum is shown to produce a much more distinct response to SoC dependent thermodynamic and diffusion processes than linear EIS. By combining NLEIS and EIS, we are able to characterize degradation in early cell cycling (where cells lost less than 1% of initial capacity). We also show that NLEIS complements the characterization of charge transfer kinetics of linear EIS through the second harmonic sensitivity to symmetry. For example, NLEIS shows that fresh cells have high symmetry charge transfer (α_a = α_c = 0.5) on both electrodes, whereas early in the cycling there is a shift toward kinetics that favor oxidation on the positive electrode (α_(a,pos) greater than 0.5, α_(c,pos) less than 0.5). Combined analysis of EIS and NLEIS spectra shows promise for improved parameter estimation and model validation. All experimental data and analysis code for this manuscript can be found on ECSarXiv.

Online capacity estimation for lithium-ion batteries through joint estimation method

2019 ◽  
Vol 255 ◽  
pp. 113817 ◽  
Author(s):  
Quanqing Yu ◽  
Rui Xiong ◽  
Ruixin Yang ◽  
Michael G. Pecht
Keyword(s):  
Lithium Ion Batteries ◽  
Estimation Method ◽  
Lithium Ion ◽  
Joint Estimation ◽  
Capacity Estimation

A framework for battery internal temperature and state-of-charge estimation based on fractional-order thermoelectric model

2022 ◽  
pp. 014233122110672
Author(s):  
Yujie Wang ◽  
Caijie Zhou ◽  
Guanghui Zhao ◽  
Zonghai Chen
Keyword(s):  
Lithium Ion Batteries ◽  
Fractional Order ◽  
Electrochemical Impedance ◽  
Prediction Method ◽  
Lithium Ion ◽  
State Of Charge ◽  
Joint Estimation ◽  
Internal Temperature ◽  
Model Based ◽  
Thermoelectric Model

In recent years, the rapid development of electric vehicles has raised a wave of innovation in lithium-ion batteries. The safety operation of lithium-ion batteries is one of the major bottlenecks restraining the development of the energy storage market. The temperature especially the internal temperature can significantly affect the performance and safety of the battery; therefore, this paper presented a novel framework for joint estimation of the internal temperature and state-of-charge of the battery based on a fractional-order thermoelectric model. Due to the nonlinearity, coupling, and time-varying parameters of lithium-ion batteries, a fractional-order thermoelectric model which is suitable for a wide temperature range is first established to simulate the battery’s thermodynamic and electrical properties. The parameters of the model are identified by the electrochemical impedance spectroscopy experiments and particle swarm optimization method at six different temperatures, and then the relationship between parameters and temperature is obtained. Finally, the framework for joint estimation of both the cell internal temperature and the state-of-charge is presented based on the model-based state observer. The experimental results under different operation conditions indicated that, compared with the traditional off-line prediction method, the model-based online estimation method not only shows stronger robustness under different initial conditions but also has better accuracy. Specifically, the absolute mean error of the estimation of state-of-charge and internal temperature based on the proposed method is about 0.5% and 0.3°C respectively, which is about half of that based on the off-line prediction method.

scholarly journals Characterization of the Compressive Load on a Lithium-Ion Battery for Electric Vehicle Application

Machines ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 71
Author(s):  
Seyed Saeed Madani ◽  
Erik Schaltz ◽  
Søren Knudsen Kær
Keyword(s):  
Electrochemical Impedance Spectroscopy ◽  
Impedance Spectroscopy ◽  
Lithium Ion Batteries ◽  
Lithium Ion Battery ◽  
Electric Vehicles ◽  
Large Scale ◽  
Electrochemical Impedance ◽  
Applied Pressure ◽  
Lithium Ion ◽  
Battery Cells

Lithium-ion batteries are being implemented in different large-scale applications, including aerospace and electric vehicles. For these utilizations, it is essential to improve battery cells with a great life cycle because a battery substitute is costly. For their implementation in real applications, lithium-ion battery cells undergo extension during the course of discharging and charging. To avoid disconnection among battery pack ingredients and deformity during cycling, compacting force is exerted to battery packs in electric vehicles. This research used a mechanical design feature that can address these issues. This investigation exhibits a comprehensive description of the experimental setup that can be used for battery testing under pressure to consider lithium-ion batteries’ safety, which could be employed in electrified transportation. Besides, this investigation strives to demonstrate how exterior force affects a lithium-ion battery cell’s performance and behavior corresponding to static exterior force by monitoring the applied pressure at the dissimilar state of charge. Electrochemical impedance spectroscopy was used as the primary technique for this research. It was concluded that the profiles of the achieved spectrums from the experiments seem entirely dissimilar in comparison with the cases without external pressure. By employing electrochemical impedance spectroscopy, it was noticed that the pure ohmic resistance, which is related to ion transport resistance of the separator, could substantially result in the corresponding resistance increase.

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