Internal short circuit detection for battery pack using equivalent parameter and consistency method

Ouyang, Minggao; Zhang, Mingxuan; Feng, Xuning; Lu, Languang; Li, Jianqiu; He, Xiangming; Zheng, Yuejiu

doi:10.1016/j.jpowsour.2015.06.087

Cited by 232 publications

(113 citation statements)

References 20 publications

Supporting

Mentioning

112

Contrasting

Order By: Relevance

“…A normal Li-ion battery can be represented by an equivalent circuit model (Figure 2a) [15,17,19] that consists of OCV , internal resistance , load current and terminal voltage . The Li-ion …”

Section: Equivalent Circuit Modelsmentioning

confidence: 99%

“…A normal Li-ion battery can be represented by an equivalent circuit model (Figure 2a) [15,17,19] that consists of OCV V oc , internal resistance R, load current I and terminal voltage V t . The Li-ion battery with ISCr can be represented by a similar equivalent circuit model (Figure 2b) [15,17,20] where I 1 f is the current that flows within the battery, and I 2 f is the current that flows through the R ISC f .…”

Section: Equivalent Circuit Modelsmentioning

confidence: 99%

“…For these reasons, studies to detect the ISCr have been presented [14][15][16][17]. The ISCr can be detected by determining certain thresholds such as reduction of terminal voltage and increase of batteries temperature [14], but to obtain the thresholds, this method requires prior ISCr tests with batteries.…”

Section: Introductionmentioning

confidence: 99%

“…The ISCr can be detected by determining certain thresholds such as reduction of terminal voltage and increase of batteries temperature [14], but to obtain the thresholds, this method requires prior ISCr tests with batteries. Therefore, model-based algorithms have been presented to detect the ISCr by identifying variations of parameters in the model [15,16]. Using equivalent circuit models of a normal battery and a battery with ISCr as thresholds, characteristic parameters are obtained to detect ISCr in a battery pack [15], but this method can be used only when the battery with ISCr is connected to several normal batteries normal batteries in series, and the terminal voltages of both the battery with ISCr and the normal batteries are provided.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, model-based algorithms have been presented to detect the ISCr by identifying variations of parameters in the model [15,16]. Using equivalent circuit models of a normal battery and a battery with ISCr as thresholds, characteristic parameters are obtained to detect ISCr in a battery pack [15], but this method can be used only when the battery with ISCr is connected to several normal batteries normal batteries in series, and the terminal voltages of both the battery with ISCr and the normal batteries are provided. The ISCr can be detected by using variation of estimated parameters in the equivalent circuit model and the energy balance equation [16], but this method must be verified with other load current profiles to check whether the estimated parameters show similar variation.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Detection of Internal Short Circuit in Lithium Ion Battery Using Model-Based Switching Model Method

et al. 2017

View full text Add to dashboard Cite

Abstract:Early detection of an internal short circuit (ISCr) in a Li-ion battery can prevent it from undergoing thermal runaway, and thereby ensure battery safety. In this paper, a model-based switching model method (SMM) is proposed to detect the ISCr in the Li-ion battery. The SMM updates the model of the Li-ion battery with ISCr to improve the accuracy of ISCr resistance R ISC f estimates. The open circuit voltage (OCV) and the state of charge (SOC) are estimated by applying the equivalent circuit model, and by using the recursive least squares algorithm and the relation between OCV and SOC. As a fault index, the R ISC f is estimated from the estimated OCVs and SOCs to detect the ISCr, and used to update the model; this process yields accurate estimates of OCV and R ISC f . Then the next R ISC f is estimated and used to update the model iteratively. Simulation data from a MATLAB/Simulink model and experimental data verify that this algorithm shows high accuracy of R ISC f estimates to detect the ISCr, thereby helping the battery management system to fulfill early detection of the ISCr.

show abstract

Section: Equivalent Circuit Modelsmentioning

confidence: 99%

Section: Equivalent Circuit Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Detection of Internal Short Circuit in Lithium Ion Battery Using Model-Based Switching Model Method

et al. 2017

View full text Add to dashboard Cite

show abstract

Battery Management Systems in Electric Vehicles

2018

Advanced Battery Management Technologies for Electric Vehicles

View full text Add to dashboard Cite

The Significance of Enhancing the Reliability of Lithium‐Ion Batteries in Reducing Electric Vehicle Field Safety Accidents

Zhang,

Zhu,

Wang

et al. 2024

Batteries & Supercaps

View full text Add to dashboard Cite

In recent years, the frequency of incidents related to the safety of electric vehicles (EVs) due to lithium‐ion batteries has seen a troubling uptick, leading to a heightened focus on the safety of lithium‐ion batteries (LIBs) as a critical area of research. After thorough analysis, this study contends that the root cause of the majority of safety incidents involving LIBs in the field is predominantly linked to reliability issues within the battery products themselves. This argument offers a more targeted perspective than a broad discussion on the safety concerns of LIBs. Reliability, in this context, is defined as the likelihood that a product will execute its intended function without error over a defined period and under specific conditions. The paper delineates the reasons why current safety testing standards are unable to entirely prevent LIB safety incidents, scrutinizes the multifaceted causes and testing methodologies associated with LIB unpredictive thermal runaways from reliability perspective, and aims to reduce the probability of battery field failure and electric vehicle fire incidents, with an emphasis on mtigating unpredictive fire accidents. This study advocates for a more aggressive research effort into the reliability of LIBs, parallel to the vigorous advancement of safety technologies for these batteries.

show abstract

Internal short circuit detection for battery pack using equivalent parameter and consistency method

Cited by 232 publications

References 20 publications

Detection of Internal Short Circuit in Lithium Ion Battery Using Model-Based Switching Model Method

Detection of Internal Short Circuit in Lithium Ion Battery Using Model-Based Switching Model Method

Battery Management Systems in Electric Vehicles

The Significance of Enhancing the Reliability of Lithium‐Ion Batteries in Reducing Electric Vehicle Field Safety Accidents

Contact Info

Product

Resources

About