Performance Analysis of Li-ion Battery Under Various Thermal and Load Conditions

2018 ◽  
Vol 16 (2) ◽  
Author(s):  
Krishnashis Chatterjee ◽  
Pradip Majumdar ◽  
David Schroeder ◽  
S. Rao Kilaparti
Keyword(s):  
Energy Storage ◽  
Internal Heat ◽  
Lithium Ion ◽  
Operating Conditions ◽  
Li Ion Battery ◽  
Discharge Rates ◽  
Wide Range ◽  
Li Ion ◽  
Load Conditions ◽  
Charge Discharge

In the recent years, with the rapid advancements made in the technologies of electric and hybrid electric vehicles, selecting suitable batteries has become a major factor. Among the batteries currently used for these types of vehicles, the lithium-ion battery leads the race. Apart from that, the energy gained from regenerative braking in locomotives and vehicles can be stored in batteries for later use for propulsion thus improving the fuel consumption and efficiency. But batteries can be subjected to a wide range of temperatures depending upon the operating conditions. Thus, a thorough knowledge of the battery performance over a wide range of temperatures and different load conditions is necessary for their successful employment in future technologies. In this context, this study aims to experimentally analyze the performance of Li-ion batteries by monitoring the charge–discharge rates, efficiencies, and energy storage capabilities under different environmental and load conditions. Sensors and thermal imaging camera were used to track the environment and battery temperatures, whereas the charge–discharge characteristics were analyzed using CADEX analyzer. The results show that the battery performance is inversely proportional to charge–discharge rates. This is because, at higher charge–discharge rates, the polarization losses increase thus increasing internal heat generation and battery temperature. Also, based on the efficiency and energy storage ability, the optimum performing conditions of the Li-ion battery are 30–40 °C (temperature) and 0.5 C (C-rate).

scholarly journals Direct X-Ray Imaging as a Tool for Understanding Multiphysics Phenomena in Energy Storage

2016 ◽  
Vol 13 (3) ◽  
Author(s):  
George J. Nelson ◽  
Zachary K. van Zandt ◽  
Piyush D. Jibhakate
Keyword(s):  
Energy Storage ◽  
Lithium Ion ◽  
Ex Situ ◽  
Storage Device ◽  
Li Ion Batteries ◽  
X Ray ◽  
X Ray Imaging ◽  
Wide Range ◽  
Li Ion ◽  
Insight Into

The lithium-ion battery (LIB) has emerged as a key energy storage device for a wide range of applications, from consumer electronics to transportation. While LIBs have made key advancements in these areas, limitations remain for Li-ion batteries with respect to affordability, performance, and reliability. These challenges have encouraged the exploration for more advanced materials and novel chemistries to mitigate these limitations. The continued development of Li-ion and other advanced batteries is an inherently multiscale problem that couples electrochemistry, transport phenomena, mechanics, microstructural morphology, and device architecture. Observing the internal structure of batteries, both ex situ and during operation, provides a critical capability for further advancement of energy storage technology. X-ray imaging has been implemented to provide further insight into the mechanisms governing Li-ion batteries through several 2D and 3D techniques. Ex situ imaging has yielded microstructural data from both anode and cathode materials, providing insight into mesoscale structure and composition. Furthermore, since X-ray imaging is a nondestructive process studies have been conducted in situ and in operando to observe the mechanisms of operation as they occur. Data obtained with these methods has also been integrated into multiphysics models to predict and analyze electrode behavior. The following paper provides a brief review of X-ray imaging work related to Li-ion batteries and the opportunities these methods provide for the direct observation and analysis of the multiphysics behavior of battery materials.

scholarly journals Calibration Optimization Methodology for Lithium-Ion Battery Pack Model for Electric Vehicles in Mining Applications

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3532 ◽  
Author(s):  
Majid Astaneh ◽  
Jelena Andric ◽  
Lennart Löfdahl ◽  
Dario Maggiolo ◽  
Peter Stopp ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Large Scale ◽  
Lithium Ion ◽  
Operating Conditions ◽  
Battery Pack ◽  
Li Ion Battery ◽  
Battery Packs ◽  
Li Ion ◽  
Optimization Methodology ◽  
Battery Cells

Large-scale introduction of electric vehicles (EVs) to the market sets outstanding requirements for battery performance to extend vehicle driving range, prolong battery service life, and reduce battery costs. There is a growing need to accurately and robustly model the performance of both individual cells and their aggregated behavior when integrated into battery packs. This paper presents a novel methodology for Lithium-ion (Li-ion) battery pack simulations under actual operating conditions of an electric mining vehicle. The validated electrochemical-thermal models of Li-ion battery cells are scaled up into battery modules to emulate cell-to-cell variations within the battery pack while considering the random variability of battery cells, as well as electrical topology and thermal management of the pack. The performance of the battery pack model is evaluated using transient experimental data for the pack operating conditions within the mining environment. The simulation results show that the relative root mean square error for the voltage prediction is 0.7–1.7% and for the battery pack temperature 2–12%. The proposed methodology is general and it can be applied to other battery chemistries and electric vehicle types to perform multi-objective optimization to predict the performance of large battery packs.

The Effect of Temperature on Lithium-Ion Battery Energy Efficiency With Graphite/LiFePO4 Electrodes at Different Nominal Capacities

2018 ◽  
Author(s):  
Ashkan Nazari ◽  
Roja Esmaeeli ◽  
Seyed Reza Hashemi ◽  
Haniph Aliniagerdroudbari ◽  
Siamak Farhad
Keyword(s):  
Energy Efficiency ◽  
Heat Generation ◽  
Lithium Ion ◽  
Effect Of Temperature ◽  
Discharge Rates ◽  
Wide Range ◽  
Different Temperatures ◽  
Lifepo4 Cathode ◽  
Battery Energy ◽  
Charge Discharge

In this work, the energy efficiency of the lithium-ion batteries (LIB) with graphite anode and LiFePO4 cathode (G/LFP) at different nominal capacities and charge/discharge rates is studied through multiphysics modeling and computer simulation. After characterizing all the heat generation sources in the cell, the total heat generation in LIBs is calculated and the charge/discharge efficiency plots at different temperatures are obtained. Since G/LFP LIBs have a wide range of applications in passenger and commercial electric vehicles (EVs), the result of this study assist engineer toward more efficient battery pack design.

Design of a Hybrid Accumulator Architecture for Harvesting and Storing of Power in WSN using an Adaptive Power Organizing Algorithm

2019 ◽  
Vol 28 (08) ◽  
pp. 1950130
Author(s):  
R. Senthilkumar ◽  
G. M. Tamilselvan
Keyword(s):  
Energy Harvesting ◽  
Lithium Ion ◽  
Electrical Energy ◽  
Maximum Energy ◽  
Li Ion Battery ◽  
Solar Panels ◽  
Wide Range ◽  
Li Ion ◽  
Adaptive Power ◽  
Ultra Capacitor

Converting the harnessed energy from the environment or other energy sources to electrical energy is referred to as energy harvesting. The need of energy harvesting in wireless sensor networks is an essential issue to be handled to allow adequacy of the innovation in a wide range of utilizations. The maximum energy should be harvested from the solar panels and it should be stored and managed effectively to power the nodes in the wireless network. For this purpose, a solution proposed in this paper utilizes a hybrid accumulator architecture that combines the advantages of an effectively controlled “battery and ultra-capacitor (UC)” where the power stream from a lithium ion (Li-ion) battery is combined with a UC for power upgrade and conveyance to the stack proficiently and using a new adaptive power organizing algorithm, management of power in the battery and capacitor can be performed. The proposed design is implemented in Simulink and the results show the effect of the hybrid design.

MnO2 Nanoparticles Anchored Multi Walled Carbon Nanotubes as Potential Anode Materials for Lithium Ion Batteries

2021 ◽  
Vol 21 (10) ◽  
pp. 5296-5301
Author(s):  
Ahmad Umar ◽  
Faheem Ahmed ◽  
Ahmed A. Ibrahim ◽  
Hassan Algadi ◽  
Hasan B. Albargi ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Anode Materials ◽  
Coulombic Efficiency ◽  
Lithium Ion ◽  
Reversible Capacity ◽  
Li Ion Battery ◽  
Multi Walled Carbon Nanotubes ◽  
Li Ion ◽  
Walled Carbon Nanotubes ◽  
Charge Discharge

Herein, we report a facile hydrothermal synthesis of MnO2 nanoparticles anchored multi walled carbon nanotubes (MnO2@MWCNTs) as potential anode materials for lithium-ion (Li-ion) batteries. The prepared MnO2@MWCNTs were characterized by several techniques which confirmed the formation of MnO2 nanoparticles anchored MWCNTs. The X-ray diffraction and Raman-scattering analyses of the prepared material further revealed the effective synthesis of MnO2@MWCNTs. The fabricated Li-ion battery based on MnO2@MWCNTs exhibited a reversible capacity of ~823 mAhg−1 at a current density of 100 mAg−1 for the first cycle, and delivered a capacity of ~421 mAhg−1 for the 60 cycles. The coulombic efficiency was found to be ~100% which showed excellent reversible charge–discharge behavior. The outstanding performance of the MnO2@MWCNTs anode for the Li-ion battery can be attributed to the distinctive morphology of the MnO2 nanoparticles anchored MWCNTs that facilitated the fast transport of lithium ions and electrons and accommodated a broad volume change during the cycles of charge/discharge.

scholarly journals Lifetime Degradation Cost Analysis for Li-Ion Batteries in Capacity Markets using Accurate Physics-Based Models

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2816 ◽  
Author(s):  
Ahmed Gailani ◽  
Maher Al-Greer ◽  
Michael Short ◽  
Tracey Crosbie ◽  
Nashwan Dawood
Keyword(s):  
Energy Storage ◽  
Active Material ◽  
Lithium Ion ◽  
Operating Conditions ◽  
Storage Device ◽  
Li Ion Batteries ◽  
Degradation Model ◽  
Capacity Markets ◽  
Degradation Models ◽  
Li Ion

Capacity markets (CM) are energy markets created to ensure energy supply security. Energy storage devices provide services in the CMs. Li-ion batteries are a popular type of energy storage device used in CMs. The battery lifetime is a key factor in determining the economic viability of Li-ion batteries, and current approaches for estimating this are limited. This paper explores the potential of a lithium-ion battery to provide CM services with four de-rating factors (0.5 h, 1 h, 2 h, and 4 h). During the CM contract, the battery experiences both calendar and cycle degradation, which reduces the overall profit. Physics-based battery and degradation models are used to quantify the degradation costs for batteries in the CM to enhance the previous research results. The degradation model quantifies capacity losses related to the solid–electrolyte interphase (SEI) layer, active material loss, and SEI crack growth. The results show that the physics-based degradation model can accurately predict degradation costs under different operating conditions, and thus can substantiate the business case for the batteries in the CM. The simulated CM profits can be increased by 60% and 75% at 5 °C and 25 °C, respectively, compared to empirical and semiempirical degradation models. A sensitivity analysis for a range of parameters is performed to show the effects on the batteries’ overall profit margins.

scholarly journals An Adaptive and Wide-Range Output DC-DC Converter for Loading Circuit of Li-Ion Battery Charger

2018 ◽  
Vol 34 (1) ◽  
Author(s):  
Nguyen Van Hao ◽  
Nguyen Duc Minh ◽  
Pham Nguyen Thanh Loan
Keyword(s):  
Power Efficiency ◽  
Output Voltage ◽  
Average Power ◽  
Lithium Ion ◽  
Li Ion Battery ◽  
Battery Charger ◽  
Load Current ◽  
Voltage Range ◽  
Wide Range ◽  
Li Ion

In this paper, an adaptive and wide-range output DC-DC converter designed for lithium-ion (Li-Ion) battery charger circuit is proposed. The converter operates in continuous conduction mode (CCM) to provide an output voltage in response to battery voltage and a wide-range output current to ensure that circuit requirements are met. This circuit is designed on Cadence using 0.35-um BCD technology. Simulation results show that the circuit fully operates in CCM mode with a load current from 50 mA to 1000 mA and output voltage ripple factor is less than 1 %. Furthermore, the current supplied to the load circuit responses to three types of Li-Ion rechargeable currents. The output voltage of the converter varies from 2.8 to 4.5 V corresponding to the voltage range of the battery being charged from 2.5 to 4.2 V. The average power efficiency of the converter in large load current mode (1000 mA) reaches 94 %.

scholarly journals Stochastic Expansion Planning of Various Energy Storage Technologies in Active Power Distribution Networks

2021 ◽  
Vol 13 (10) ◽  
pp. 5752
Author(s):  
Reza Sabzehgar ◽  
Diba Zia Amirhosseini ◽  
Saeed D. Manshadi ◽  
Poria Fajri
Keyword(s):  
Energy Storage ◽  
Power Distribution ◽  
Power Flow ◽  
Lithium Ion ◽  
Distribution Networks ◽  
Renewable Energy Resources ◽  
Flow Equations ◽  
Second Order Cone ◽  
Li Ion ◽  
The Cost

This work aims to minimize the cost of installing renewable energy resources (photovoltaic systems) as well as energy storage systems (batteries), in addition to the cost of operation over a period of 20 years, which will include the cost of operating the power grid and the charging and discharging of the batteries. To this end, we propose a long-term planning optimization and expansion framework for a smart distribution network. A second order cone programming (SOCP) algorithm is utilized in this work to model the power flow equations. The minimization is computed in accordance to the years (y), seasons (s), days of the week (d), time of the day (t), and different scenarios based on the usage of energy and its production (c). An IEEE 33-bus balanced distribution test bench is utilized to evaluate the performance, effectiveness, and reliability of the proposed optimization and forecasting model. The numerical studies are conducted on two of the highest performing batteries in the current market, i.e., Lithium-ion (Li-ion) and redox flow batteries (RFBs). In addition, the pros and cons of distributed Li-ion batteries are compared with centralized RFBs. The results are presented to showcase the economic profits of utilizing these battery technologies.

Enhancing Co/Co2VO4 Li-ion Battery Anode Performances via 2D-2D Heterostructure Engineering

Nanoscale ◽  
2021 ◽  
Author(s):  
Kun Wang ◽  
Yongyuan Hu ◽  
Jian Pei ◽  
Fengyang Jing ◽  
Zhongzheng Qin ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Anode Material ◽  
Output Voltage ◽  
High Capacity ◽  
Lithium Ion ◽  
Li Ion Battery ◽  
Li Ion ◽  
Battery Anode

High capacity Co2VO4 becomes a potential anode material for lithium ion batteries (LIBs) benefiting from its lower output voltage during cycling than other cobalt vanadates. However, the application of this...

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