Real-time overcharge warning and early thermal runaway prediction of Li-ion battery by online impedance measurement

2021 ◽  
pp. 1-1
Author(s):  
Nawei Lyu ◽  
Yang Jin ◽  
Rui Xiong ◽  
Shan Miao ◽  
Jinfeng Gao
Keyword(s):  
Real Time ◽  
Impedance Measurement ◽  
Thermal Runaway ◽  
Li Ion Battery ◽  
Li Ion

scholarly journals Fast Impedance Measurement of Li-Ion Battery Using Discrete Random Binary Excitation and Wavelet Transform

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 46152-46165
Author(s):  
Gjorgji Nusev ◽  
Dani Juricic ◽  
Miran Gaberscek ◽  
Joze Moskon ◽  
Pavle Boskoski
Keyword(s):  
Wavelet Transform ◽  
Impedance Measurement ◽  
Li Ion Battery ◽  
Li Ion

Real-Time Estimation of Lithium-Ion Concentration in Both Electrodes of a Lithium-Ion Battery Cell Utilizing Electrochemical–Thermal Coupling

2017 ◽  
Vol 139 (3) ◽  
Author(s):  
Satadru Dey ◽  
Beshah Ayalew
Keyword(s):  
Real Time ◽  
Unscented Kalman Filter ◽  
Lithium Ion ◽  
Time Estimation ◽  
Li Ion Battery ◽  
Battery Cell ◽  
Thermal Dynamics ◽  
Estimation Scheme ◽  
Real Time Estimation ◽  
Li Ion

This paper proposes and demonstrates an estimation scheme for Li-ion concentrations in both electrodes of a Li-ion battery cell. The well-known observability deficiencies in the two-electrode electrochemical models of Li-ion battery cells are first overcome by extending them with a thermal evolution model. Essentially, coupling of electrochemical–thermal dynamics emerging from the fact that the lithium concentrations contribute to the entropic heat generation is utilized to overcome the observability issue. Then, an estimation scheme comprised of a cascade of a sliding-mode observer and an unscented Kalman filter (UKF) is constructed that exploits the resulting structure of the coupled model. The approach gives new real-time estimation capabilities for two often-sought pieces of information about a battery cell: (1) estimation of cell-capacity and (2) tracking the capacity loss due to degradation mechanisms such as lithium plating. These capabilities are possible since the two-electrode model needs not be reduced further to a single-electrode model by adding Li conservation assumptions, which do not hold with long-term operation. Simulation studies are included for the validation of the proposed scheme. Effect of measurement noise and parametric uncertainties is also included in the simulation results to evaluate the performance of the proposed scheme.

scholarly journals Real Time Observation of Nanomaterials in Energy Harvesting and Li-ion Battery Systems

2011 ◽  
Vol 17 (S2) ◽  
pp. 1570-1571
Author(s):  
R Shahbazian-Yassar ◽  
H Ghassemi ◽  
A Asthana ◽  
M Au ◽  
Y Yap
Keyword(s):  
Energy Harvesting ◽  
Real Time ◽  
Li Ion Battery ◽  
Battery Systems ◽  
Li Ion ◽  
Time Observation ◽  
Real Time Observation

Extended abstract of a paper presented at Microscopy and Microanalysis 2011 in Nashville, Tennessee, USA, August 7–August 11, 2011.

Predicting Thermal Runaway in Li-Ion Battery Employing Machine Learning Framework

2020 ◽  
Vol MA2020-01 (2) ◽  
pp. 429-429 ◽  
Author(s):  
Marco Ragone ◽  
Vitaliy Yurkiv ◽  
Ajaykrishna Ramasubramanian ◽  
Reza Shahbazian-Yassar ◽  
Farzad Mashayek
Keyword(s):  
Machine Learning ◽  
Thermal Runaway ◽  
Li Ion Battery ◽  
Learning Framework ◽  
Li Ion

scholarly journals Broadband Impedance Measurement of Lithium-Ion Battery in the Presence of Nonlinear Distortions

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2493
Author(s):  
Jussi Sihvo ◽  
Tomi Roinila ◽  
Daniel-Ioan Stroe
Keyword(s):  
Electrochemical Impedance ◽  
Equivalent Circuit Model ◽  
Impedance Measurement ◽  
Lithium Ion ◽  
Li Ion Battery ◽  
Third Order ◽  
Impedance Measurements ◽  
Nonlinear Distortions ◽  
Measured Impedance ◽  
Li Ion

The impedance of a Lithium-ion (Li-ion) battery has been shown to be a valuable tool in evaluating the battery characteristics such as the state-of-charge (SOC) and state-of-health (SOH). Recent studies have shown impedance-measurement methods based on broadband pseudo-random sequences (PRS) and Fourier techniques. The methods can be efficiently applied in real-time applications where the conventional electrochemical-impedance spectroscopy (EIS) is not well suited to measure the impedance. The techniques based on the PRS are, however, strongly affected by the battery nonlinearities. This paper presents the use of a direct-synthesis ternary (DST) signal to minimize the effect caused by the nonlinearities. In such a signal, the second- and third-order harmonics are suppressed from the signal energy spectrum. As a result, the effect of the second- and third-order nonlinearities are suppressed from the impedance measurements. The impedance measurements are carried out for a nickel manganese cobalt Li-ion battery cell. The performance of the method is compared to the conventional EIS, as well as to other PRS signals which are more prone to battery nonlinearities. The Kronig–Kramers (K–K) transformation test is used to validate the uniqueness of the measured impedance spectra. It is shown that the measurement method based on the DST produces highly accurate impedance measurements under nonlinear distortions of the battery. The method shows a good K–K test behavior indicating that the measured impedance complies well to a linearized equivalent circuit model that can be used for the SOC and SOH estimation of the battery. Due to the good performance, low measurement time, and simplicity of the DST, the method is well suited for practical battery applications.

Real Time Prediction of Li-Ion Battery Pack Temperatures in EV Vehicles

2020 ◽  
Author(s):  
Azita Soleymani ◽  
William Maltz
Keyword(s):  
Real Time ◽  
Heat Generation ◽  
Equivalent Circuit Model ◽  
Battery Pack ◽  
Generation Rate ◽  
Li Ion Battery ◽  
Heat Generation Rate ◽  
Digital Twin ◽  
Twin Model ◽  
Li Ion

Abstract A semi-analytical digital twin model of a 90 kW.h li-ion battery pack was developed to capture thermal behavior of the pack in a real-time environment. The solution uses reduced-order models that minimize compute cost/time yet are accurate in predicting real-world operation. The real-time heat generation rate in the battery pack is calculated using 2RC equivalent circuit model. A series of HPPC tests were conducted to calibrate the equivalent circuit model in order to accurately calculate heat generation rate as a function of SOC, temperature, current, charge/discharge mode and pulse duration. In the paper, live-sensor data was integrated into the digital twin system level model of the battery pack to create a real-time environment. The generated tool was utilized to monitor the real-time temperature of the battery pack remotely and have a predictive maintenance solution. The model results for heat generation rate, terminal voltage, and temperature were found to be consistent with the test data across a wide range of conditions. The generated model was used to accelerate battery pack design and development by enabling the evaluation of design feasibility and to conduct in-depth root causes analyses for various inputs and operating conditions, including initial SOC, temperature, coolant flow rate, different charge and discharge profiles. The resulting digital twin model provides additional data that cannot be measured offering the EV industry an opportunity to improve its safety record.

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