A Study on Modeling of Effective Series Resistance for Lithium-ion Batteries under Life Cycle Consideration

Somakettarin, Natthawuth; Pichetjamroen, Achara

doi:10.1088/1755-1315/322/1/012008

Cited by 7 publications

(5 citation statements)

References 13 publications

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“…By introducing two heating mechanisms into a thermal model and utilizing artificial neural networks to capture the relationship between temperature and state of charge for effective prediction, this algorithm has low time complexity and strong adaptability. Somakettarin et al proposed an effective series resistance model to study the relationship with battery life [37], resulting in small estimation errors. It can serve as a novel indicator for evaluating the health status of lithium-ion batteries.…”

Section: Discussionmentioning

confidence: 99%

Enhanced Whale Optimization Algorithm with Wavelet Decomposition for Lithium Battery Health Estimation in Deep Extreme Learning Machines

Wang,

Luo,

Zhu

et al. 2023

Applied Sciences

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Lithium battery health state estimation can help optimize battery usage and management strategies. In response to the challenges faced by traditional battery management systems in accurately estimating the State of Health of lithium-ion batteries and addressing issues such as capacity recovery and noise interference, this paper proposes a method based on wavelet decomposition and an improved whale optimization algorithm optimized deep extreme learning machine for estimating the SOH of lithium-ion batteries. Firstly, the lithium-ion battery capacity degradation sequence is extracted, and the wavelet decomposition method is used to decompose the battery capacity into global and local degradation trends. Next, the non-linear convergence factor and the whale optimization algorithm with adaptive weights are employed to optimize the deep extreme learning machine for predicting each trend component. Finally, the prediction results are effectively integrated to obtain the lithium-ion battery SOH. This experimental method is validated using NASA and CALCE datasets, and the results indicate that the root mean square error and mean absolute percentage error are both below 0.95%, with relative accuracy and absolute correlation coefficients exceeding 98%. This demonstrates the method’s excellent accuracy and robustness.

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Section: Discussionmentioning

confidence: 99%

Enhanced Whale Optimization Algorithm with Wavelet Decomposition for Lithium Battery Health Estimation in Deep Extreme Learning Machines

Wang,

Luo,

Zhu

et al. 2023

Applied Sciences

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“…In addition, tests of Sony LIBs were carried out, stored at temperatures of 20 and 60 C, which showed that in the case of potentiostatic maintenance of 4.2 V, capacity losses during the year amounted to 23%, of which 18% were irreversible losses. Storage under normal temperature conditions and constant charge maintenance increase the rate of LIB degradation, while at elevated temperatures this factor is not so critical [107]. In addition, exceeding the threshold value of the charging voltage or a long-term charge of LIB at a voltage of 4.2 V has an extremely negative effect on the performance of the battery.…”

Section: Degradation Processes In a Lithium-ion Batterymentioning

confidence: 99%

Degradation of Lithium-Ion Batteries in an Electric Transport Complex

et al. 2021

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The article provides an overview and comparative analysis of various types of batteries, including the most modern type—lithium-ion batteries. Currently, lithium-ion batteries (LIB) are widely used in electrical complexes and systems, including as a traction battery for electric vehicles. Increasing the service life of the storage devices used today is an important scientific and technical problem due to their rapid wear and tear and high cost. This article discusses the main approaches and methods for researching the LIB resource. First of all, a detailed analysis of the causes of degradation was carried out and the processes occurring in lithium-ion batteries during charging, discharging, resting and difficult operating conditions were established. Then, the main factors influencing the service life are determined: charging and discharging currents, self-discharge current, temperature, number of cycles, discharge depth, operating range of charge level, etc. when simulating a real motion process. The work considers the battery management systems (BMS) that take into account and compensate for the influence of the factors considered. In the conclusion, the positive and negative characteristics of the presented methods of scientific research of the residual life of LIB are given and recommendations are given for the choice of practical solutions to engineers and designers of batteries. The work also analyzed various operating cycles of electric transport, including heavy forced modes, extreme operating modes (when the amount of discharge and discharge of batteries is greater than the nominal value) and their effect on the degradation of lithium-ion batteries.

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“…But in 2020, the mileage of electric cars increased to 300-500 km after the release of Tesla cars. In this regard, there is still a tendency to increase the maximum range of electric cars, and accordingly, the change in battery capacity and daily mileage [19].…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modelling of Traction Equipment Parameters of Electric Cargo Trucks

Malozyomov,

Martyushev,

Sorokova

et al. 2024

Mathematics

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Electric vehicles are one of the most innovative and promising areas of the automotive industry. The efficiency of traction equipment is an important factor in the operation of an electric vehicle. In electric vehicles, the energy stored in the battery is converted into mechanical energy to drive the vehicle. The higher the efficiency of the battery, the less energy is lost in the conversion process, which improves the overall energy efficiency of the electric vehicle. Determining the performance characteristics of the traction battery of an electric vehicle plays an important role in the selection of the vehicle and its future operation. Using mathematical modelling, it is shown that battery capacity, charging rate, durability and efficiency are essential to ensure the comfortable and efficient operation of an electric vehicle throughout its lifetime. A mathematical model of an electric truck including a traction battery has been developed. It is shown that, with the help of the developed mathematical model, it is possible to calculate the load parameters of the battery in standardised driving cycles. The data verification is carried out by comparing the data obtained during standardised driving with the results of mathematical modelling.

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A Study on Modeling of Effective Series Resistance for Lithium-ion Batteries under Life Cycle Consideration

Cited by 7 publications

References 13 publications

Enhanced Whale Optimization Algorithm with Wavelet Decomposition for Lithium Battery Health Estimation in Deep Extreme Learning Machines

Enhanced Whale Optimization Algorithm with Wavelet Decomposition for Lithium Battery Health Estimation in Deep Extreme Learning Machines

Degradation of Lithium-Ion Batteries in an Electric Transport Complex

Mathematical Modelling of Traction Equipment Parameters of Electric Cargo Trucks

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