Performance comparison of nonlinear state estimators for state-of-charge estimation of supercapacitor

Manika Saha; Pankaj Saha; Munmun Khanra

doi:10.1109/CMI50323.2021.9362850

Performance comparison of nonlinear state estimators for state-of-charge estimation of supercapacitor

Manika Saha
, Pankaj Saha
, Munmun Khanra

Not published at VTT

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

6 Citations (Scopus)

Abstract

Accurate state-of-Charge (SOC) estimation of supercapacitor is very crucial for real-time energy management and control of the energy storage device. This paper deals with performance comparison and analysis of the two most commonly used SOC estimators, namely Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) for remaining charge monitoring of supercapacitors. For that purpose, a completely observable equivalent circuit model of supercapacitor has been adopted in order to design the estimation algorithms. In order to perform the comparative analysis, a commercially available Maxwell supercapacitor has been chosen to conduct experimental studies. Finally, The performance of the estimators has been illustrated via both the single-run and the Monte Carlo runs.

Original language	English
Title of host publication	2021 IEEE 2nd International Conference on Control, Measurement and Instrumentation, CMI 2021
Subtitle of host publication	Proceedings
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	105-109
Number of pages	5
ISBN (Electronic)	978-1-72819-342-7
DOIs	https://doi.org/10.1109/CMI50323.2021.9362850
Publication status	Published - 8 Jan 2021
MoE publication type	A4 Article in a conference publication
Event	2nd IEEE International Conference on Control, Measurement and Instrumentation, CMI 2021 - Virtual, Kolkata, India Duration: 8 Jan 2021 → 10 Jan 2021

Conference

Conference	2nd IEEE International Conference on Control, Measurement and Instrumentation, CMI 2021
Country/Territory	India
City	Virtual, Kolkata
Period	8/01/21 → 10/01/21

Funding

This work is supported by DST (SEED division), India under SYST; Ref. SP/YO/054/2016.

Keywords

Extended Kalman filter
Nonlinear filtering
State-of-charge estimation
Supercapacitor
Unscented Kalman filter

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10.1109/CMI50323.2021.9362850

Cite this

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title = "Performance comparison of nonlinear state estimators for state-of-charge estimation of supercapacitor",

abstract = "Accurate state-of-Charge (SOC) estimation of supercapacitor is very crucial for real-time energy management and control of the energy storage device. This paper deals with performance comparison and analysis of the two most commonly used SOC estimators, namely Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) for remaining charge monitoring of supercapacitors. For that purpose, a completely observable equivalent circuit model of supercapacitor has been adopted in order to design the estimation algorithms. In order to perform the comparative analysis, a commercially available Maxwell supercapacitor has been chosen to conduct experimental studies. Finally, The performance of the estimators has been illustrated via both the single-run and the Monte Carlo runs.",

keywords = "Extended Kalman filter, Nonlinear filtering, State-of-charge estimation, Supercapacitor, Unscented Kalman filter",

author = "Manika Saha and Pankaj Saha and Munmun Khanra",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2nd IEEE International Conference on Control, Measurement and Instrumentation, CMI 2021 ; Conference date: 08-01-2021 Through 10-01-2021",

year = "2021",

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doi = "10.1109/CMI50323.2021.9362850",

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booktitle = "2021 IEEE 2nd International Conference on Control, Measurement and Instrumentation, CMI 2021",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

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Saha, M, Saha, P & Khanra, M 2021, Performance comparison of nonlinear state estimators for state-of-charge estimation of supercapacitor. in 2021 IEEE 2nd International Conference on Control, Measurement and Instrumentation, CMI 2021: Proceedings. IEEE Institute of Electrical and Electronic Engineers, pp. 105-109, 2nd IEEE International Conference on Control, Measurement and Instrumentation, CMI 2021, Virtual, Kolkata, India, 8/01/21. https://doi.org/10.1109/CMI50323.2021.9362850

Performance comparison of nonlinear state estimators for state-of-charge estimation of supercapacitor. / Saha, Manika; Saha, Pankaj; Khanra, Munmun.
2021 IEEE 2nd International Conference on Control, Measurement and Instrumentation, CMI 2021: Proceedings. IEEE Institute of Electrical and Electronic Engineers, 2021. p. 105-109.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Performance comparison of nonlinear state estimators for state-of-charge estimation of supercapacitor

AU - Saha, Manika

AU - Saha, Pankaj

AU - Khanra, Munmun

PY - 2021/1/8

Y1 - 2021/1/8

N2 - Accurate state-of-Charge (SOC) estimation of supercapacitor is very crucial for real-time energy management and control of the energy storage device. This paper deals with performance comparison and analysis of the two most commonly used SOC estimators, namely Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) for remaining charge monitoring of supercapacitors. For that purpose, a completely observable equivalent circuit model of supercapacitor has been adopted in order to design the estimation algorithms. In order to perform the comparative analysis, a commercially available Maxwell supercapacitor has been chosen to conduct experimental studies. Finally, The performance of the estimators has been illustrated via both the single-run and the Monte Carlo runs.

AB - Accurate state-of-Charge (SOC) estimation of supercapacitor is very crucial for real-time energy management and control of the energy storage device. This paper deals with performance comparison and analysis of the two most commonly used SOC estimators, namely Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) for remaining charge monitoring of supercapacitors. For that purpose, a completely observable equivalent circuit model of supercapacitor has been adopted in order to design the estimation algorithms. In order to perform the comparative analysis, a commercially available Maxwell supercapacitor has been chosen to conduct experimental studies. Finally, The performance of the estimators has been illustrated via both the single-run and the Monte Carlo runs.

KW - Extended Kalman filter

KW - Nonlinear filtering

KW - State-of-charge estimation

KW - Supercapacitor

KW - Unscented Kalman filter

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DO - 10.1109/CMI50323.2021.9362850

M3 - Conference article in proceedings

AN - SCOPUS:85102622949

SP - 105

EP - 109

BT - 2021 IEEE 2nd International Conference on Control, Measurement and Instrumentation, CMI 2021

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - 2nd IEEE International Conference on Control, Measurement and Instrumentation, CMI 2021

Y2 - 8 January 2021 through 10 January 2021

ER -

Performance comparison of nonlinear state estimators for state-of-charge estimation of supercapacitor

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Keywords

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