Development of a voltage relaxation model for rapid open-circuit voltage prediction in lithium-ion batteries

The open-circuit voltage (OCV) of a battery, as a crucial characteristic parameter, is widely used in many aspects of battery technology, such as electrode material mechanism analysis, battery performance/state estimation and working process management. However, the applications of OCV are severely...

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Published inJournal of power sources Vol. 253; pp. 412 - 418
Main Authors Pei, Lei, Wang, Tiansi, Lu, Rengui, Zhu, Chunbo
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.05.2014
Elsevier
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Abstract The open-circuit voltage (OCV) of a battery, as a crucial characteristic parameter, is widely used in many aspects of battery technology, such as electrode material mechanism analysis, battery performance/state estimation and working process management. However, the applications of OCV are severely limited due to the need for a long rest time for full relaxation. In this paper, a rapid OCV prediction method is proposed to predict the final static OCV in a few minutes using linear regression techniques, based on a new mathematical model developed from an improvement on a second-order resistance–capacitance (RC) model. As the improvement, an important discovery is demonstrated by experimental investigation and data analysis: the relaxation time (i.e., time constant) of the diffusion circuit of the second-order RC model is not a fixed constant, unlike an intrinsic value for a given material, but an apparent linear function of the open-circuit time. This improvement enables the new model to track the actual relaxation process very well. The accuracy and the rapidity of the new model and proposed method are validated with working-condition experimental data on battery cells with different cathodes, and the results of OCV prediction are very accurate (errors below 1 mV in 20 min). •Discover that diffusion time constant is a linear function of open-circuit time.•Established a new voltage relaxation model with good curve-fitting performance.•Presented a rapid, adaptive and online OCV prediction method.•Shorten the waiting time from traditional 20 h to 20 min with the new method.
AbstractList The open-circuit voltage (OCV) of a battery, as a crucial characteristic parameter, is widely used in many aspects of battery technology, such as electrode material mechanism analysis, battery performance/state estimation and working process management. However, the applications of OCV are severely limited due to the need for a long rest time for full relaxation. In this paper, a rapid OCV prediction method is proposed to predict the final static OCV in a few minutes using linear regression techniques, based on a new mathematical model developed from an improvement on a second-order resistance–capacitance (RC) model. As the improvement, an important discovery is demonstrated by experimental investigation and data analysis: the relaxation time (i.e., time constant) of the diffusion circuit of the second-order RC model is not a fixed constant, unlike an intrinsic value for a given material, but an apparent linear function of the open-circuit time. This improvement enables the new model to track the actual relaxation process very well. The accuracy and the rapidity of the new model and proposed method are validated with working-condition experimental data on battery cells with different cathodes, and the results of OCV prediction are very accurate (errors below 1 mV in 20 min). •Discover that diffusion time constant is a linear function of open-circuit time.•Established a new voltage relaxation model with good curve-fitting performance.•Presented a rapid, adaptive and online OCV prediction method.•Shorten the waiting time from traditional 20 h to 20 min with the new method.
The open-circuit voltage (OCV) of a battery, as a crucial characteristic parameter, is widely used in many aspects of battery technology, such as electrode material mechanism analysis, battery performance/state estimation and working process management. However, the applications of OCV are severely limited due to the need for a long rest time for full relaxation. In this paper, a rapid OCV prediction method is proposed to predict the final static OCV in a few minutes using linear regression techniques, based on a new mathematical model developed from an improvement on a second-order resistance-capacitance (RC) model. As the improvement, an important discovery is demonstrated by experimental investigation and data analysis: the relaxation time (i.e., time constant) of the diffusion circuit of the second-order RC model is not a fixed constant, unlike an intrinsic value for a given material, but an apparent linear function of the open-circuit time. This improvement enables the new model to track the actual relaxation process very well. The accuracy and the rapidity of the new model and proposed method are validated with working-condition experimental data on battery cells with different cathodes, and the results of OCV prediction are very accurate (errors below 1 mV in 20 min).
The open-circuit voltage (OCV) of a battery, as a crucial characteristic parameter, is widely used in many aspects of battery technology, such as electrode material mechanism analysis, battery performance/state estimation and working process management. However, the applications of OCV are severely limited due to the need for a long rest time for full relaxation. In this paper, a rapid OCV prediction method is proposed to predict the final static OCV in a few minutes using linear regression techniques, based on a new mathematical model developed from an improvement on a second-order resistance-capacitance (RC) model. As the improvement, an important discovery is demonstrated by experimental investigation and data analysis: the relaxation time (i.e., time constant) of the diffusion circuit of the second-order RC model is not a fixed constant, unlike an intrinsic value for a given material, but an apparent linear function of the open-circuit time. This improvement enables the new model to track the actual relaxation process very well. The accuracy and the rapidity of the new model and proposed method are validated with working-condition experimental data on battery cells with different cathodes, and the results of OCV prediction are very accurate (errors below 1 mV in 20 mm).
Author Lu, Rengui
Wang, Tiansi
Pei, Lei
Zhu, Chunbo
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Keywords Lithium-ion battery
Open-circuit voltage
Relaxation model
Time constant
Rapid prediction
Lithium ion batteries
Relaxation
Prediction
Voltage
Secondary cell
Models
Open circuit voltage
Language English
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Snippet The open-circuit voltage (OCV) of a battery, as a crucial characteristic parameter, is widely used in many aspects of battery technology, such as electrode...
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SubjectTerms Applied sciences
Direct energy conversion and energy accumulation
Electric batteries
Electric potential
Electrical engineering. Electrical power engineering
Electrical power engineering
Electrochemical conversion: primary and secondary batteries, fuel cells
Exact sciences and technology
Glass transition temperature
Lithium batteries
Lithium-ion batteries
Lithium-ion battery
Mathematical analysis
Mathematical models
Open-circuit voltage
Rapid prediction
Relaxation model
Relaxation time
Time constant
Voltage
Title Development of a voltage relaxation model for rapid open-circuit voltage prediction in lithium-ion batteries
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Volume 253
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