scholarly journals Sensitivity of Impedance Parameters of Li-ion Batteries Under Different State of Health

Author(s):  
Hao Yuan ◽  
Haifeng Dai ◽  
Xuezhe Wei ◽  
Yihui Dai
Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4415
Author(s):  
Brian Ospina Agudelo ◽  
Walter Zamboni ◽  
Eric Monmasson

This paper is a comparative study of the multiple RC, Oustaloup and Grünwald–Letnikov approaches for time domain implementations of fractional-order battery models. The comparisons are made in terms of accuracy, computational burden and suitability for the identification of impedance parameters from time-domain measurements. The study was performed in a simulation framework and focused on a set of ZARC elements, representing the middle frequency range of Li-ion batteries’ impedance. It was found that the multiple RC approach offers the best accuracy–complexity compromise, making it the most interesting approach for real-time battery simulation applications. As for applications requiring the identification of impedance parameters, the Oustaloup approach offers the best compromise between the goodness of the obtained frequency response and the accuracy–complexity requirements.


Author(s):  
Zhimin Xi ◽  
Rong Jing ◽  
Cheol Lee

This paper investigates recent research on battery diagnostics and prognostics especially for Lithium-ion (Li-ion) batteries. Battery diagnostics focuses on battery models and diagnosis algorithms for battery state of charge (SOC) and state of health (SOH) estimation. Battery prognostics elaborates data-driven prognosis algorithms for predicting the remaining useful life (RUL) of battery SOC and SOH. Readers will learn not only basics but also very recent research developments on battery diagnostics and prognostics.


Author(s):  
Xiaowei Zhao ◽  
Guoyu Zhang ◽  
Lin Yang

A task that has to be solved for the application of batteries in vehicles with an electric drive train is the determination of the actual state-of-health (SOH) and state-of-charge (SOC) of the battery cells. In this paper, an on board strategy for estimating SOC and SOH of Li-ion batteries is proposed. The equivalent circuit model is used for both SOC and SOH estimations. In SOH algorithm, the estimated value of battery capacity not only reflects the aging degree of battery pack, but also provides information for SOC estimation. Meanwhile, the extended Kaiman filtering is used in SOC estimation. Because the performance of the equivalent circuit model will be better at small currents than at high currents, extended Kaiman filtering is substituted by Ampere-Hour counting when the absolute value of current is greater than a calibration value. The Digatron battery tester was used to evaluate the proposed estimation method, and results show that the estimation method has high accuracy and efficiency at ordinary temperatures.


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