scholarly journals Combining the Distribution of Relaxation Times from EIS and Time-Domain Data for Parameterizing Equivalent Circuit Models of Lithium-Ion Batteries

Batteries ◽  
2021 ◽  
Vol 7 (3) ◽  
pp. 52
Author(s):  
Leo Wildfeuer ◽  
Philipp Gieler ◽  
Alexander Karger
Keyword(s):  
Lithium Ion Batteries ◽  
Frequency Domain ◽  
Time Domain ◽  
Partial Information ◽  
Measurement Data ◽  
Lithium Ion ◽  
Constant Current ◽  
Full Potential ◽  
Fitting Algorithm ◽  
Parameterized Model

ECM are a widely used modeling approach for lithium-ion batteries in engineering applications. The RC elements, which display the dynamic loss processes of the cell, are usually parameterized by fitting the ECM to experimental data in either the time-domain or the frequency-domain. However, both types of data have limitations with regard to the observable time constants of electrochemical processes. This work proposes a method to combine time-domain and frequency-domain measurement data for parameterization of RC elements by exploiting the full potential of the DRT. Instead of using only partial information from the DRT to supplement a conventional fitting algorithm, we determine the parameters of an arbitrary number of RC elements directly from the DRT. The difficulties of automated deconvolution of the DRT, including regularization and the choice of an optimal regularization factor, is tackled by using the L-curve criterion for optimized calculation of the DRT via Tikhonov regularization. Three different approaches to merge time- and frequency-domain data are presented, including a novel approach where the DRT is simultaneously calculated from EIS and pulse relaxation measurements. The parameterized model for a commercial 18650 NCA cell was validated during a validation cycle consisting of constant current and real-world automotive cycling and yields a relative improvement of over 40 % compared to a conventional EIS-fitting algorithm.

Measurement and Prediction of Decomposed Energy Efficiencies of Lithium Ion Batteries With Two Charge Models

2021 ◽  
Vol 18 (3) ◽  
Author(s):  
Yuhao Huang ◽  
Yan Su ◽  
Akhil Garg
Keyword(s):  
Lithium Ion Batteries ◽  
Open Circuit Voltage ◽  
Prediction Method ◽  
Lithium Ion ◽  
Open Circuit ◽  
Constant Current ◽  
New Process ◽  
Artificial Neural Network Ann ◽  
Cv Model ◽  
Charge Discharge

Abstract A new process decomposed calculation method is developed to compare the cycle based charge, discharge, net, and overall energy efficiencies of lithium-ion batteries. Multi-cycle measurements for both constant current (CC) and constant current to constant voltage (CC-CV) charge models have been performed. Unlike most conventional efficiency calculation methods with one mean open-circuit voltage (OCV) curve, two OCV curves are calculated separately for the charge and discharge processes. These two OCV curves help to clarify the intra-cycle charge, discharge, net, and overall energy efficiencies. The relationships of efficiencies versus state of charge, state of quantity, and scaled stresses are demonstrated. Efficiency degradation patterns versus cycle numbers and scaled stresses are also illustrated with the artificial neural network (ANN) prediction method. The decaying ratios of the overall efficiencies are about 2% and 0.3% in the first 30 cycles, for CC and CC-CV, respectively. Hence, efficiencies of the CC-CV model are more stable compared with the CC model, which are shown by both experimental and ANN prediction results.

Time-domain simulations of transient response in LiFePO4 cathode lithium ion batteries

2014 ◽  
Vol 14 (5) ◽  
pp. 702-707 ◽  
Author(s):  
Xiaoping Xu ◽  
Miao Shui ◽  
Weidong Zheng ◽  
Jie Shu ◽  
Lei Hui ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Transient Response ◽  
Time Domain ◽  
Lithium Ion ◽  
Lifepo4 Cathode

scholarly journals Non-Inverting Cascaded Bidirectional Buck-Boost DC-DC Converter with Average Current Mode Control for Lithium-Ion Battery Charger

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Heri Suryoatmojo ◽  
Indra Anugrah Pratama ◽  
Soedibyo .
Keyword(s):  
Energy Storage ◽  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Current Mode ◽  
Boost Converter ◽  
Constant Current ◽  
Voltage Gain ◽  
Battery Charger ◽  
Energy Storage Devices ◽  
Li Ion

In order to develop renewable energy, it also needs to enhance the developing of supporting elements. For example, lithium-ion batteries as a component of energy storage. Lithium-ion batteries (Li-ion) have been chosen as energy storage devices for portable equipment, unmanned Aerial Vehicle (UAV) and grid storage systems. But there is a problem such as the process of charging the battery for UAV. Conventional converters used in those chargers have disadvantages such as limited power, lower voltage gain and also high current stress. Therefore, such converters are not efficient to be used for charging the battery. This paper proposes a cascaded bidirectional buck-boost converter for charging the battery. This converter can be operated bidirectional and have better rated power and higher voltage gain. Also, this topology has the same polarity with the input. From the test results, the converter can work in either forward or backward power flow. This converter is working in both buck or boost mode and has an efficiency of 83% in buck mode and 81% for boost mode. The charging process is about 83 minutes until SOC approximately 90 – 95.Keywords: battery charger, cascaded bidirectional buck – boost converter, constant current, li-ion introduction.

scholarly journals Heat Loss Measurement of Lithium Titanate Oxide Batteries under Fast Charging Conditions by Employing Isothermal Calorimeter

Batteries ◽  
2018 ◽  
Vol 4 (4) ◽  
pp. 59 ◽  
Author(s):  
Seyed Madani ◽  
Erik Schaltz ◽  
Søren Knudsen Kær
Keyword(s):  
Lithium Ion Batteries ◽  
Heat Loss ◽  
Lithium Ion ◽  
Lithium Titanate ◽  
Constant Current ◽  
Maximum Temperature ◽  
Battery Cell ◽  
Lithium Titanate Oxide ◽  
Temperature Efficiency ◽  
Constant Current Charge

To understand better the thermal behaviour of lithium-ion batteries under different working conditions, various experiments were applied to a 13 Ah Altairnano lithium titanate oxide battery cell by means of isothermal battery calorimeter. Several parameters were measured such as the battery surface temperature, voltage, current, power, heat flux, maximum temperature and power area. In addition, the efficiency was calculated. Isothermal battery calorimeter was selected as the most appropriate method for heat loss measurements. Temperatures on the surface of the battery were measured by employing four contact thermocouples (type K). In order to determine the heat loss of the battery, constant current charge and discharge pulses at sixteen different C-rates were applied to the battery. It was seen that the charge and discharge C-rates has a considerable influence on the thermal behaviours of lithium-ion batteries. In this research paper, the C-rate was linked to the peak temperature, efficiency and heat loss and it was concluded that they are linear dependent on the C-rate. In addition, the outcomes of this investigation can be used for battery thermal modelling and design of thermal management systems.

Innovating Safe Lithium-Ion Batteries Through Basic to Applied Research

2017 ◽  
Vol 15 (1) ◽  
Author(s):  
Corey T. Love ◽  
Christopher Buesser ◽  
Michelle D. Johannes ◽  
Karen E. Swider-Lyons
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion Battery ◽  
Performance Metrics ◽  
Lithium Ion ◽  
Research Area ◽  
Naval Research ◽  
Multiple Time ◽  
Full Potential ◽  
Battery Safety ◽  
Safety Research

This paper for inclusion in the special issue provides a brief synopsis of lithium-ion battery safety research efforts at the Naval Research Laboratory (NRL) and presents the viewpoint that lithium-ion battery safety is a growing research area for both academic and applied researchers. We quantify how the number of lithium-ion battery research efforts worldwide has plateaued while publications associated with the safety aspect of lithium-ion batteries are on a rapid incline. The safety challenge creates a unique research opportunity to not only understand basic phenomena but also enhance existing fielded system through advanced controls and prognostics. As the number of lithium-ion battery safety research contributions climbs, significant advancements will come in the area of modeling across multiple time and length scales. Additionally, the utility of in situ and in operando techniques, several performed by the NRL and our collaborators, will feed the data necessary to validate these models. Lithium-ion battery innovations are no longer tied to performance metrics alone, but are increasingly dependent on safety research to unlock their full potential. There is much work to be done.

Large-scale Gauss-Newton inversion of transient controlled-source electromagnetic measurement data using the model reduction framework

Geophysics ◽  
2013 ◽  
Vol 78 (4) ◽  
pp. E161-E171 ◽  
Author(s):  
M. Zaslavsky ◽  
V. Druskin ◽  
A. Abubakar ◽  
T. Habashy ◽  
V. Simoncini
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Large Scale ◽  
Jacobian Matrix ◽  
Computational Cost ◽  
Measurement Data ◽  
Multiple Sources ◽  
Time Data ◽  
Controlled Source ◽  
The Time Domain

Transient data controlled-source electromagnetic measurements are usually interpreted via extracting few frequencies and solving the corresponding inverse frequency-domain problem. Coarse frequency sampling may result in loss of information and affect the quality of interpretation; however, refined sampling increases computational cost. Fitting data directly in the time domain has similar drawbacks, i.e., its large computational cost, in particular, when the Gauss-Newton (GN) algorithm is used for the misfit minimization. That cost is mainly comprised of the multiple solutions of the forward problem and linear algebraic operations using the Jacobian matrix for calculating the GN step. For large-scale 2.5D and 3D problems with multiple sources and receivers, the corresponding cost grows enormously for inversion algorithms using conventional finite-difference time-domain (FDTD) algorithms. A fast 3D forward solver based on the rational Krylov subspace (RKS) reduction algorithm using an optimal subspace selection was proposed earlier to partially mitigate this problem. We applied the same approach to reduce the size of the time-domain Jacobian matrix. The reduced-order model (ROM) is obtained by projecting a discretized large-scale Maxwell system onto an RKS with optimized poles. The RKS expansion replaces the time discretization for forward and inverse problems; however, for the same or better accuracy, its subspace dimension is much smaller than the number of time steps of the conventional FDTD. The crucial new development of this work is the space-time data compression of the ROM forward operator and decomposition of the ROM’s time-domain Jacobian matrix via chain rule, as a product of time- and space-dependent terms, thus effectively decoupling the discretizations in the time and parameter spaces. The developed technique can be equivalently applied to finely sampled frequency-domain data. We tested our approach using synthetic 2.5D examples of hydrocarbon reservoirs in the marine environment.

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