Comparison of one and two time constant models for lithium ion battery

The fast and accurate modeling topologies are very much essential for power train electrification. The importance of thermal effect is very important in any electrochemical systems and must be considered in battery models because temperature factor has highest importance in transport phenomena and chemical kinetics. The dynamic performance of the lithium ion battery is discussed here and a suitable electrical equivalent circuit is developed to study its response for sudden changes in the output. An effective lithium cell simulation model with thermal dependence is presented in this paper. One series resistor, one voltage source and a single RC block form the proposed equivalent circuit model. The 1 RC and 2 RC Lithium ion battery models are commonly used in the literature are studied and compared. The simulation of Lithium-ion battery 1RC and 2 RC Models are performed by using Matlab/Simulink Software. The simulation results in his paper shows that Lithium-ion battery 1 RC model has more maximum output error of 0.42% than 2 RC Lithium-ion battery model in constant current condition and the maximum output error of 1 RC Lithium-ion battery model is 0.18% more than 2 RC Lithium-ion battery model in UDDS Cycle condition. The simulation results also show that in both simple and complex discharging modes, the error in output is much improved in 2 RC lithium ion battery model when compared to 1 RC Lithium-ion battery model. Thus the paper shows for general applications like in portable electronic design like laptops, Lithium-ion battery 1 RC model is the preferred choice and for automotive and space design applications, Lithium-ion 2 RC model is the preferred choice. In this paper, these simulation results for 1 RC and 2 RC Lithium-ion battery models will be very much useful in the application of practical Lithium-ion battery management systems for electric vehicle applications

Modeling Nanomaterials in Lithium Ion Battery with Experimental Validation

poster abstractA lithium-ion battery (Li-ion battery or LIB) is a rechargeable battery type in which lithium ions move from the negative electrode to the positive electrode during discharge and back when charging. Lithium systems are of considerable interest due to their high energy density and low toxicity compared to other rechargeable lithium battery chemistries. Conventional Lithium-ion battery materials typically start as 10-50 micron sized particles. In many of these new chemistries, having the materials in nanoparticle form or as a nanostructured particle or film is critical to achieving the desired performance. The goal of this study is to understand the mechanisms that govern the size-dependence of electrochemical properties and mechanical properties of nanomaterials in Lithium ion batteries using first principles method. We have been developing computational models of LiCoO2 crystals. The specific objectives of the MURI project are to: (1) conduct first principles study of the electrochemical properties and mechanical properties of nanosize LiCoO2; (2) investigate Li ion diffusion phenomena in the nanomaterial; and (3) experimentally validate the computational results

Mathematical Modelling of Lithium-ion Concentration in Rechargeable Lithium Batteries

The demand for lithium ion batteries has increased due to the increasing need by consumers for rechargeable batteries. In the effort to produce high performance batteries, mathematical model becomes a vital instrument in helping batteries developers to understand the behaviour of the battery systems during charge and discharge process. This understanding is useful in the optimization of the battery design and parameters. This paper presents a mathematical model used to simulate the intercalation process of lithium ions in the electrode of a lithium-ion battery. This model is used to study the intercalation process through the lithium-ion concentration profiles during charge/discharge of a rechargeable lithium-ion battery. This approach resulted in solving the diffusion equation in the solution phase and the solid phase of the battery. Results from both phases are plotted and compared. (Abstract by authors

Two-dimensional Thermal Modeling of Lithium-ion Battery Cell Based on Electrothermal Impedance Spectroscopy

Thermal modeling of lithium-ion batteries is gaining its importance together with increasing power density and compact design of the modern battery systems in order to assure battery safety and long lifetime. Thermal models of lithium-ion batteries are usually either expensive to develop and accurate or equivalent thermal circuit based with moderate accuracy and without spatial temperature distribution. This work presents initial results that can be used as a fundament for the cost-efficient development of the two-dimensional thermal model of lithium-ion battery based on multipoint electrothermal impedance spectroscopy. </jats:p

Effective fire extinguishing systems for lithium-ion battery

Lithium-ion batteries are a popular choice of power source for a variety of energy and power demanding applications for both stationary applications and electromobility. Among electrochemical storage systems, Lithium-ion batteries were found to be promising candidate, due to their high power and high energy density. In order to assemble high power batteries for plug-in hybrid electric vehicles and pure electric vehicles, several hundreds of large-format Lithium-ion cells will be required, and even more cells for power/energy demanding stationary applications. However, safety remains a significant concern, as battery failure leads to ejection of hazardous materials and rapid heat release. The failure of a single cell can generate a large amount of heat which can then initiate, in the worst case, the thermal runaway of neighbouring cells, leading to failure throughout the battery pack. The heat accumulation can also run into the venting of a cell, with the emission of flammable organic solvent inside the battery pack. Battery failure can be initiated via a number of different abuse scenarios, such as overheating, overcharging, puncture/crushing, water immersion, or external short circuit. Development of effective mitigation strategies necessitates a study on battery failure events and a better understanding of important characteristics relating to safety, such as heat release, hazardous materials ejection, and thermal propagation. On the other hand, when a fire event is initiated, proper intervention strategies have to be defined in order to avoid it becoming catastrophic. In this paper are reported the results of thermal abuse tests on single Lithium-ion cells and a battery pack. The tests were performed with the technical equipment and resources of National Fire Corps. Screening tests for battery fire extinguishing agents were also performed. The effectiveness of an agent was evaluated through experiments on the cooling effect of fire extinguishing agents. Among the various agents, water and foam were found to be the most effective

In Situ Monitoring of Temperature inside Lithium-Ion Batteries by Flexible Micro Temperature Sensors

Lithium-ion secondary batteries are commonly used in electric vehicles, smart phones, personal digital assistants (PDA), notebooks and electric cars. These lithium-ion secondary batteries must charge and discharge rapidly, causing the interior temperature to rise quickly, raising a safety issue. Over-charging results in an unstable voltage and current, causing potential safety problems, such as thermal runaways and explosions. Thus, a micro flexible temperature sensor for the in in-situ monitoring of temperature inside a lithium-ion secondary battery must be developed. In this work, flexible micro temperature sensors were integrated into a lithium-ion secondary battery using the micro-electro-mechanical systems (MEMS) process for monitoring temperature in situ

A Design for a Lithium-Ion Battery Pack Monitoring System Based on NB-IoT-ZigBee

With environmental issues arising from the excessive use of fossil fuels, clean energy has gained widespread attention, particularly the application of lithium-ion batteries. Lithium-ion batteries are integrated into various industrial products, which necessitates higher safety requirements. Narrowband Internet of Things (NB-IoT) is an LPWA (Low Power Wide Area Network) technology that provides IoT devices with low-power, low-cost, long-endurance, and wide-coverage wireless connectivity. This study addresses the shortcomings of existing lithium-ion battery pack detection systems and proposes a lithium-ion battery monitoring system based on NB-IoT-ZigBee technology. The system operates in a master-slave mode, with the subordinate module collecting and fusing multi-source sensor data, while the master control module uploads the data to local monitoring centers and cloud platforms via TCP and NB-IoT. Experimental validation demonstrates that the design functions effectively, accomplishing the monitoring and protection of lithium-ion battery packs in energy storage power stations

Thermal Characteristics and Safety Aspects of Lithium-Ion Batteries: An In-Depth Review

This paper provides an overview of the significance of precise thermal analysis in the context of lithium-ion battery systems. It underscores the requirement for additional research to create efficient methodologies for modeling and controlling thermal properties, with the ultimate goal of enhancing both the safety and performance of Li-ion batteries. The interaction between temperature regulation and lithium-ion batteries is pivotal due to the intrinsic heat generation within these energy storage systems. A profound understanding of the thermal behaviors exhibited by lithium-ion batteries, along with the implementation of advanced temperature control strategies for battery packs, remains a critical pursuit. Utilizing tailored models to dissect the thermal dynamics of lithium-ion batteries significantly enhances our comprehension of their thermal management across a wide range of operational scenarios. This comprehensive review systematically explores diverse research endeavors that employ simulations and models to unravel intricate thermal characteristics, behavioral nuances, and potential runaway incidents associated with lithium-ion batteries. The primary objective of this review is to underscore the effectiveness of employed characterization methodologies and emphasize the pivotal roles that key parameters—specifically, current rate and temperature—play in shaping thermal dynamics. Notably, the enhancement of thermal design systems is often more feasible than direct alterations to the lithium-ion battery designs themselves. As a result, this thermal review primarily focuses on the realm of thermal systems. The synthesized insights offer a panoramic overview of research findings, with a deeper understanding requiring consultation of specific published studies and their corresponding modeling endeavors

Economic optimization of component sizing for residential battery storage systems

Battery energy storage systems (BESS) coupled with rooftop-mounted residential photovoltaic (PV) generation, designated as PV-BESS, draw increasing attention and market penetration as more and more such systems become available. The manifold BESS deployed to date rely on a variety of different battery technologies, show a great variation of battery size, and power electronics dimensioning. However, given today's high investment costs of BESS, a well-matched design and adequate sizing of the storage systems are prerequisites to allow profitability for the end-user. The economic viability of a PV-BESS depends also on the battery operation, storage technology, and aging of the system. In this paper, a general method for comprehensive PV-BESS techno-economic analysis and optimization is presented and applied to the state-of-art PV-BESS to determine its optimal parameters. Using a linear optimization method, a cost-optimal sizing of the battery and power electronics is derived based on solar energy availability and local demand. At the same time, the power flow optimization reveals the best storage operation patterns considering a trade-off between energy purchase, feed-in remuneration, and battery aging. Using up to date technology-specific aging information and the investment cost of battery and inverter systems, three mature battery chemistries are compared; a lead-acid (PbA) system and two lithium-ion systems, one with lithium-iron-phosphate (LFP) and another with lithium-nickel-manganese-cobalt (NMC) cathode. The results show that different storage technology and component sizing provide the best economic performances, depending on the scenario of load demand and PV generation.Web of Science107art. no. 83

Prognostics of Lithium-Ion Batteries Based on Wavelet Denoising and DE-RVM

Lithium-ion batteries are widely used in many electronic systems. Therefore, it is significantly important to estimate the lithium-ion battery’s remaining useful life (RUL), yet very difficult. One important reason is that the measured battery capacity data are often subject to the different levels of noise pollution. In this paper, a novel battery capacity prognostics approach is presented to estimate the RUL of lithium-ion batteries. Wavelet denoising is performed with different thresholds in order to weaken the strong noise and remove the weak noise. Relevance vector machine (RVM) improved by differential evolution (DE) algorithm is utilized to estimate the battery RUL based on the denoised data. An experiment including battery 5 capacity prognostics case and battery 18 capacity prognostics case is conducted and validated that the proposed approach can predict the trend of battery capacity trajectory closely and estimate the battery RUL accurately