Magnetography: A novel Characterization Tool for Li-Ion-Batteries

2013 ◽  
Vol 1544 ◽  
Author(s):  
Timm Bergholz ◽  
Theodor Nuñez ◽  
Jürgen Wackerl ◽  
Carsten Korte ◽  
Detlef Stolten
Keyword(s):  
Magnetic Field ◽  
Normal Operation ◽  
Additional Parameter ◽  
Battery Management ◽  
Li Ion Batteries ◽  
Non Invasive ◽  
Spatially Resolved ◽  
Standardized Measurement ◽  
Li Ion ◽  
The Magnetic Field

ABSTRACTThe application of magnetography as a novel method to determine the state of charge (SoC) of commercial Li-ion Batteries is reported. The method is non-invasive and nondestructive and suitable to be applied during normal operation. It is based on spatially resolved measurement of the magnetic field B, induced by the changing current flow during cycling. A standardized measurement setup and procedure for conventional AMR-sensors has been developed, offering high reproducibility (∼0.1%) and the chance to characterize the different spatial components of the magnetic field (Bx, By, Bz). The percentage deviation of the B-distributions for different SoCs for a given current load reveals significant differences. A change of B of up to 20% between SoCs of 90% and 10% is found. The influence of current density at different SoC reveals a constant magnetic susceptibility χ at low SoC and a field dependent χ at high SoC. Both effects are attributed to the change of the magnetic properties upon varying the amount of intercalated lithium in the transition metal (LixNi1/3Co1/3Mn1/3O2) based intercalation cathode. The method can be used to provide an additional parameter for SoCestimation to battery management systems.

scholarly journals A Novel Impedance Micro-Sensor for Metal Debris Monitoring of Hydraulic Oil

Micromachines ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 150
Author(s):  
Hongpeng Zhang ◽  
Haotian Shi ◽  
Wei Li ◽  
Laihao Ma ◽  
Xupeng Zhao ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Wear Debris ◽  
Detection Method ◽  
Silicon Steel ◽  
Detection Sensitivity ◽  
Normal Operation ◽  
Metal Debris ◽  
Hydraulic Oil ◽  
Steel Strips ◽  
The Magnetic Field

Hydraulic oil is the key medium for the normal operation of hydraulic machinery, which carries various wear debris. The information reflected by the wear debris can be used to predict the early failure of equipment and achieve predictive maintenance. In order to realize the real-time condition monitoring of hydraulic oil, an impedance debris sensor that can detect inductance and resistance parameters is designed and studied in this paper. The material and size of wear debris can be discriminated based on inductance-resistance detection method. Silicon steel strips and two rectangular channels are designed in the sensor. The silicon steel strips are used to enhance the magnetic field strength, and the double rectangular detection channels can make full use of the magnetic field distribution region, thereby improving the detection sensitivity and throughput of the sensor. The comparison experiment shows that the coils in series are more suitable for the monitoring of wear debris. By comparing and analyzing the direction and the presence or absence of the signal pulses, the debris sensor can detect and distinguish 46 µm iron particles and 110 µm copper particles. This impedance detection method provides a new technical support for the high-precision distinguishing measurement of metal debris. The sensor can not only be used for oil detection in the laboratory, but also can be made into portable oil detection device for machinery health monitoring.

scholarly journals Designing of Lithium - Ion Battery Pack Rechargeable on a Hybrid System with Battery Management System (BMS) for DC Loads of Low Power Applications – A Prototype Model

2021 ◽  
Vol 2089 (1) ◽  
pp. 012017
Author(s):  
Ramu Bhukya ◽  
Praveen Kumar Nalli ◽  
Kalyan Sagar Kadali ◽  
Mahendra Chand Bade
Keyword(s):  
Lithium Ion Battery ◽  
Management System ◽  
Short Circuit ◽  
Lithium Ion ◽  
Battery Pack ◽  
Prototype Model ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Batteries ◽  
Li Ion

Abstract Now a days, Li-ion batteries are quite possibly the most exceptional battery-powered batteries; these are drawing in much consideration from recent many years. M Whittingham first proposed lithium-ion battery technology in the 1970s, using titanium sulphide for the cathode and lithium metal for the anode. Li-ion batteries are the force to be reckoned with for the advanced electronic upset in this cutting-edge versatile society, solely utilized in cell phones and PC computers. A battery is a Pack of cells organized in an arrangement/equal association so the voltage can be raised to the craving levels. Lithium-ion batteries, which are completely utilised in portable gadgets & electric vehicles, are the driving force behind the digital technological revolution in today’s mobile societies. In order to protect and maintain voltage and current of the battery with in safe limit Battery Management System (BMS) should be used. BMS provides thermal management to the battery, safeguarding it against over and under temperature and also during short circuit conditions. The battery pack is designed with series and parallel connected cells of 3.7v to produce 12v. The charging and releasing levels of the battery pack is indicated by interfacing the Arduino microcontroller. The entire equipment is placed in a fiber glass case (looks like aquarium) in order to protect the battery from external hazards to design an efficient Lithium-ion battery by using Battery Management System (BMS). We give the supply to the battery from solar panel and in the absence of this, from a regular AC supply.

scholarly journals Less Is Enough: Assessment of the Random Sampling Method for the Analysis of Magnetoencephalography (MEG) Data

2019 ◽  
Vol 24 (4) ◽  
pp. 98
Author(s):  
Cristina Campi ◽  
Annalisa Pascarella ◽  
Francesca Pitolli
Keyword(s):  
Magnetic Field ◽  
Random Sampling ◽  
Sampling Method ◽  
Brain Activity ◽  
Memory Storage ◽  
Non Invasive ◽  
Regularization Techniques ◽  
Ill Posed ◽  
The Brain ◽  
The Magnetic Field

Magnetoencephalography (MEG) aims at reconstructing the unknown neuroelectric activity in the brain from non-invasive measurements of the magnetic field induced by neural sources. The solution of this ill-posed, ill-conditioned inverse problem is usually dealt with using regularization techniques that are often time-consuming, and computationally and memory storage demanding. In this paper we analyze how a slimmer procedure, random sampling, affects the estimation of the brain activity generated by both synthetic and real sources.

Thermomagnetic convection in a layer of ferrofluid placed in a uniform oblique external magnetic field

2015 ◽  
Vol 764 ◽  
pp. 316-348 ◽  
Author(s):  
Habibur Rahman ◽  
Sergey A. Suslov
Keyword(s):  
Magnetic Field ◽  
External Magnetic Field ◽  
Additional Parameter ◽  
Thermomagnetic Convection ◽  
Uniform External Magnetic Field ◽  
Inclination Angles ◽  
Convection Patterns ◽  
The Stability ◽  
The Magnetic Field ◽  
Field Inclination

AbstractLinear stability of magnetoconvection of a ferromagnetic fluid contained between two infinite differentially heated non-magnetic plates in the presence of an oblique uniform external magnetic field is studied in zero gravity conditions. The thermomagnetic convection that arises is caused by the spatial variation of magnetisation occurring due to its dependence on the temperature. The critical values of the governing parameters at which the transition between motionless and convective states is observed are determined for various field inclination angles and for fluid magnetic parameters that are consistently chosen from a realistic experimental range. It is shown that, similar to natural paramagnetic fluids, the most prominent convection patterns align with the in-layer component of the applied magnetic field but in contrast to such paramagnetic fluids the instability patterns detected in ferrofluids can be oscillatory. It is also found that, contrary to paramagnetic fluids, the stability characteristics of magnetoconvection in ferrofluids depend on the magnitude of the applied field which becomes an additional parameter of the problem. This is shown to be due to the nonlinearity of the magnetic field distribution within the ferrofluid.

Magnetic Sensors for Space Applications

2018 ◽  
pp. 248-283 ◽  
Author(s):  
Neoclis Hadjigergiou ◽  
Marios Sophocleous ◽  
Evangelos Hristoforou ◽  
Paul Peter Sotiriadis
Keyword(s):  
Magnetic Field ◽  
Quantum Interference ◽  
Measurement Techniques ◽  
General Information ◽  
Magnetic Sensors ◽  
Normal Operation ◽  
Space Applications ◽  
Flux Gate ◽  
Magneto Resistance ◽  
The Magnetic Field

This chapter is composed of three parts. The first is an introductory part, providing general information about magnetism and related phenomena. Magnetic materials are also discussed and presented. Afterwards, the magnetic field and various measurement techniques are discussed. In the second part, different magnetic sensors used in a laboratory or space are presented. Magnetic sensors that are discussed include anisotropic magneto-resistance (AMR), giant magneto-resistance (GMR), giant magneto-impedance (GMI), flux-gate and superconducting quantum interference device (SQUID). Although some of them may be outdated and well known, they are widespread and they still pose an excellent choice for certain applications. Magnetic cleanliness is an important factor both in calibration and in normal operation of a system; in the third part, current techniques to isolate a system from the external magnetic field providing cleanliness are discussed.

scholarly journals Comparative Study of Equivalent Circuit Models Performance in Four Common Lithium-Ion Batteries: LFP, NMC, LMO, NCA

Batteries ◽  
2021 ◽  
Vol 7 (3) ◽  
pp. 51
Author(s):  
Manh-Kien Tran ◽  
Andre DaCosta ◽  
Anosh Mevawalla ◽  
Satyam Panchal ◽  
Michael Fowler
Keyword(s):  
Equivalent Circuit ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Batteries ◽  
Li Ion Battery ◽  
Battery Modeling ◽  
Li Ion ◽  
And Control

Lithium-ion (Li-ion) batteries are an important component of energy storage systems used in various applications such as electric vehicles and portable electronics. There are many chemistries of Li-ion battery, but LFP, NMC, LMO, and NCA are four commonly used types. In order for the battery applications to operate safely and effectively, battery modeling is very important. The equivalent circuit model (ECM) is a battery model often used in the battery management system (BMS) to monitor and control Li-ion batteries. In this study, experiments were performed to investigate the performance of three different ECMs (1RC, 2RC, and 1RC with hysteresis) on four Li-ion battery chemistries (LFP, NMC, LMO, and NCA). The results indicated that all three models are usable for the four types of Li-ion chemistries, with low errors. It was also found that the ECMs tend to perform better in dynamic current profiles compared to non-dynamic ones. Overall, the best-performed model for LFP and NCA was the 1RC with hysteresis ECM, while the most suited model for NMC and LMO was the 1RC ECM. The results from this study showed that different ECMs would be suited for different Li-ion battery chemistries, which should be an important factor to be considered in real-world battery and BMS applications.

Implementation of the Li-Ion Battery Management System Based on DS2438

2015 ◽  
Vol 733 ◽  
pp. 714-717 ◽  
Author(s):  
Ping Yang ◽  
Hou Yu Yu ◽  
Yong Gang Yan
Keyword(s):  
Management System ◽  
State Of Charge ◽  
Battery Management System ◽  
Battery Management ◽  
Li Ion Batteries ◽  
Li Ion Battery ◽  
Electric Cars ◽  
Power Battery ◽  
Electric Vehicle Battery ◽  
Li Ion

In order to ensure good performance and extend the lifetime of li-ion batteries in electric cars, effective real-time monitoring and management must be valued. This paper designs an electric vehicle battery management system based on a smart battery monitoring chip, DS2438. It integrates the measurement of battery's temperature, voltage, current, and power as a whole, which not only simplifies the circuit, but also saves system cost. The battery’s SOC (State Of Charge) can be easily estimated and displayed in this design. It improves the reliability of power battery pack and prolonged its life, which can be used as reference to battery management system design and application.

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