A 2D-Filter for Battery Incremental Capacity Curve Extraction

Xiaopeng TANG; Jingyi LU; Ke YAO; Zhou LV; Furong GAO

doi:10.46855/energy-proceedings-3461

A 2D-Filter for Battery Incremental Capacity Curve Extraction

Xiaopeng TANG, Jingyi LU^*, Ke YAO, Zhou LV, Furong GAO^*

^*Corresponding author for this work

Research output: Journal Publications › Journal Article (refereed) › peer-review

Abstract

A 2D filter is proposed for battery incremental capacity curve filtering in a cyclic aging test. The filter works in two directions, namely, from time to time and from batch (cycle) to batch. In details, a simple low-pass filter is applied in the batch direction, and a bias-corrected Gaussian filter is applied in the time direction. Experimental results show that the root-meansquare-error of the proposed method is 20% lower than the neural-network-based benchmarking algorithm. Over-fitting and under-fitting could also be resolved.

Original language	English
Number of pages	4
Journal	Energy Proceedings
Volume	4
DOIs	https://doi.org/10.46855/energy-proceedings-3461
Publication status	Published - 2019
Externally published	Yes
Event	International Conference on Applied Energy 2019 - Västerås, Sweden Duration: 12 Aug 2019 → 15 Aug 2019

Bibliographical note

Publisher Copyright:
© 2019, ISRES Publishing. All rights reserved.

Keywords

2D filter
incremental capacity analysis (ICA)
Gaussian filter

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10.46855/energy-proceedings-3461

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title = "A 2D-Filter for Battery Incremental Capacity Curve Extraction",

abstract = "A 2D filter is proposed for battery incremental capacity curve filtering in a cyclic aging test. The filter works in two directions, namely, from time to time and from batch (cycle) to batch. In details, a simple low-pass filter is applied in the batch direction, and a bias-corrected Gaussian filter is applied in the time direction. Experimental results show that the root-meansquare-error of the proposed method is 20% lower than the neural-network-based benchmarking algorithm. Over-fitting and under-fitting could also be resolved.",

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author = "Xiaopeng TANG and Jingyi LU and Ke YAO and Zhou LV and Furong GAO",

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language = "English",

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journal = "Energy Proceedings",

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AU - TANG, Xiaopeng

AU - LU, Jingyi

AU - YAO, Ke

AU - LV, Zhou

AU - GAO, Furong

PY - 2019

Y1 - 2019

N2 - A 2D filter is proposed for battery incremental capacity curve filtering in a cyclic aging test. The filter works in two directions, namely, from time to time and from batch (cycle) to batch. In details, a simple low-pass filter is applied in the batch direction, and a bias-corrected Gaussian filter is applied in the time direction. Experimental results show that the root-meansquare-error of the proposed method is 20% lower than the neural-network-based benchmarking algorithm. Over-fitting and under-fitting could also be resolved.

AB - A 2D filter is proposed for battery incremental capacity curve filtering in a cyclic aging test. The filter works in two directions, namely, from time to time and from batch (cycle) to batch. In details, a simple low-pass filter is applied in the batch direction, and a bias-corrected Gaussian filter is applied in the time direction. Experimental results show that the root-meansquare-error of the proposed method is 20% lower than the neural-network-based benchmarking algorithm. Over-fitting and under-fitting could also be resolved.

KW - 2D filter

KW - incremental capacity analysis (ICA)

KW - Gaussian filter

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U2 - 10.46855/energy-proceedings-3461

DO - 10.46855/energy-proceedings-3461

M3 - Journal Article (refereed)

SN - 2004-2965

VL - 4

JO - Energy Proceedings

JF - Energy Proceedings

T2 - International Conference on Applied Energy 2019

Y2 - 12 August 2019 through 15 August 2019

ER -

A 2D-Filter for Battery Incremental Capacity Curve Extraction

Abstract

Bibliographical note

Keywords

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