Battery State of Charge Estimation Based on a Pure Hardware Implementable Method

Xiaopeng TANG; Furong GAO; Ke YAO; Yujie WANG

doi:10.12783/dteees/iceee2018/27801

Battery State of Charge Estimation Based on a Pure Hardware Implementable Method

Xiaopeng TANG, Furong GAO, Ke YAO, Yujie WANG

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

Abstract

In this paper, a light-weighted state of charge (SoC) estimation method is proposed. A novel proportional-integral-delta structure is proposed to improve the noise-rejection performance. Experimental results show that the proposed algorithm can achieve a 4% accuracy with the presence of 50mV voltage measurement noise, while its computational time is 90% less than that of the extended Kalman filter.
Compared with the existing SoC algorithms, a distinguishing feature of the algorithm is that it is implementable using pure analog devices. This feature makes it possible to build a redundant hardware-based SoC estimator to enhance the overall reliability of the battery management system.

Original language	English
Title of host publication	Proceeding of the 2nd Joint International Conference on Energy, Ecology and Environment (ICEEE 2018) and Electrical Intelligent Vehicles (ICEIV 2018)
Publisher	Destech Publications, Inc
Number of pages	5
ISBN (Print)	9781605955902
DOIs	https://doi.org/10.12783/dteees/iceee2018/27801
Publication status	Published - 2018
Externally published	Yes
Event	The 2nd Joint International Conference on Energy, Ecology and Environment and Electrical Intelligent Vehicles - Melbourne, Australia Duration: 21 Nov 2018 → 25 Nov 2018

Publication series

Name	DEStech Transactions on Environment, Energy and Earth Sciences
ISSN (Print)	2475-8833

Conference

Conference	The 2nd Joint International Conference on Energy, Ecology and Environment and Electrical Intelligent Vehicles
Abbreviated title	ICEEE 2018/ICEIV 2018
Country/Territory	Australia
City	Melbourne
Period	21/11/18 → 25/11/18

Bibliographical note

This work was supported partly by the National Natural Science Fund of China (Grant No. 61803359), partly by National Natural Science Foundation of China project (61433005), partly by Guangdong scientific and technological project (2017B010120002) partly by CPSF-CAS Joint Foundation for Excellent Postdoctoral Fellow (Grant No. 2017LH007), and partly by China Postdoctoral Science Foundation Funded Project (Grant No. 2017M622019).

Keywords

State of charge
Electric vehicles
Light-weighted observer
Redundant design

Access to Document

10.12783/dteees/iceee2018/27801

Cite this

TANG, X., GAO, F., YAO, K., & WANG, Y. (2018). Battery State of Charge Estimation Based on a Pure Hardware Implementable Method. In Proceeding of the 2nd Joint International Conference on Energy, Ecology and Environment (ICEEE 2018) and Electrical Intelligent Vehicles (ICEIV 2018) (DEStech Transactions on Environment, Energy and Earth Sciences). Destech Publications, Inc. https://doi.org/10.12783/dteees/iceee2018/27801

TANG, Xiaopeng ; GAO, Furong ; YAO, Ke et al. / Battery State of Charge Estimation Based on a Pure Hardware Implementable Method. Proceeding of the 2nd Joint International Conference on Energy, Ecology and Environment (ICEEE 2018) and Electrical Intelligent Vehicles (ICEIV 2018). Destech Publications, Inc, 2018. (DEStech Transactions on Environment, Energy and Earth Sciences).

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title = "Battery State of Charge Estimation Based on a Pure Hardware Implementable Method",

abstract = "In this paper, a light-weighted state of charge (SoC) estimation method is proposed. A novel proportional-integral-delta structure is proposed to improve the noise-rejection performance. Experimental results show that the proposed algorithm can achieve a 4% accuracy with the presence of 50mV voltage measurement noise, while its computational time is 90% less than that of the extended Kalman filter.Compared with the existing SoC algorithms, a distinguishing feature of the algorithm is that it is implementable using pure analog devices. This feature makes it possible to build a redundant hardware-based SoC estimator to enhance the overall reliability of the battery management system.",

keywords = "State of charge, Electric vehicles, Light-weighted observer, Redundant design",

author = "Xiaopeng TANG and Furong GAO and Ke YAO and Yujie WANG",

note = "This work was supported partly by the National Natural Science Fund of China (Grant No. 61803359), partly by National Natural Science Foundation of China project (61433005), partly by Guangdong scientific and technological project (2017B010120002) partly by CPSF-CAS Joint Foundation for Excellent Postdoctoral Fellow (Grant No. 2017LH007), and partly by China Postdoctoral Science Foundation Funded Project (Grant No. 2017M622019).; The 2nd Joint International Conference on Energy, Ecology and Environment and Electrical Intelligent Vehicles, ICEEE 2018/ICEIV 2018 ; Conference date: 21-11-2018 Through 25-11-2018",

year = "2018",

doi = "10.12783/dteees/iceee2018/27801",

language = "English",

isbn = "9781605955902",

series = "DEStech Transactions on Environment, Energy and Earth Sciences",

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booktitle = "Proceeding of the 2nd Joint International Conference on Energy, Ecology and Environment (ICEEE 2018) and Electrical Intelligent Vehicles (ICEIV 2018)",

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TANG, X, GAO, F, YAO, K & WANG, Y 2018, Battery State of Charge Estimation Based on a Pure Hardware Implementable Method. in Proceeding of the 2nd Joint International Conference on Energy, Ecology and Environment (ICEEE 2018) and Electrical Intelligent Vehicles (ICEIV 2018). DEStech Transactions on Environment, Energy and Earth Sciences, Destech Publications, Inc, The 2nd Joint International Conference on Energy, Ecology and Environment and Electrical Intelligent Vehicles, Melbourne, Victoria, Australia, 21/11/18. https://doi.org/10.12783/dteees/iceee2018/27801

Battery State of Charge Estimation Based on a Pure Hardware Implementable Method. / TANG, Xiaopeng; GAO, Furong; YAO, Ke et al.
Proceeding of the 2nd Joint International Conference on Energy, Ecology and Environment (ICEEE 2018) and Electrical Intelligent Vehicles (ICEIV 2018). Destech Publications, Inc, 2018. (DEStech Transactions on Environment, Energy and Earth Sciences).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

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T1 - Battery State of Charge Estimation Based on a Pure Hardware Implementable Method

AU - TANG, Xiaopeng

AU - GAO, Furong

AU - YAO, Ke

AU - WANG, Yujie

N1 - This work was supported partly by the National Natural Science Fund of China (Grant No. 61803359), partly by National Natural Science Foundation of China project (61433005), partly by Guangdong scientific and technological project (2017B010120002) partly by CPSF-CAS Joint Foundation for Excellent Postdoctoral Fellow (Grant No. 2017LH007), and partly by China Postdoctoral Science Foundation Funded Project (Grant No. 2017M622019).

PY - 2018

Y1 - 2018

N2 - In this paper, a light-weighted state of charge (SoC) estimation method is proposed. A novel proportional-integral-delta structure is proposed to improve the noise-rejection performance. Experimental results show that the proposed algorithm can achieve a 4% accuracy with the presence of 50mV voltage measurement noise, while its computational time is 90% less than that of the extended Kalman filter.Compared with the existing SoC algorithms, a distinguishing feature of the algorithm is that it is implementable using pure analog devices. This feature makes it possible to build a redundant hardware-based SoC estimator to enhance the overall reliability of the battery management system.

AB - In this paper, a light-weighted state of charge (SoC) estimation method is proposed. A novel proportional-integral-delta structure is proposed to improve the noise-rejection performance. Experimental results show that the proposed algorithm can achieve a 4% accuracy with the presence of 50mV voltage measurement noise, while its computational time is 90% less than that of the extended Kalman filter.Compared with the existing SoC algorithms, a distinguishing feature of the algorithm is that it is implementable using pure analog devices. This feature makes it possible to build a redundant hardware-based SoC estimator to enhance the overall reliability of the battery management system.

KW - State of charge

KW - Electric vehicles

KW - Light-weighted observer

KW - Redundant design

U2 - 10.12783/dteees/iceee2018/27801

DO - 10.12783/dteees/iceee2018/27801

M3 - Conference paper (refereed)

SN - 9781605955902

T3 - DEStech Transactions on Environment, Energy and Earth Sciences

BT - Proceeding of the 2nd Joint International Conference on Energy, Ecology and Environment (ICEEE 2018) and Electrical Intelligent Vehicles (ICEIV 2018)

PB - Destech Publications, Inc

T2 - The 2nd Joint International Conference on Energy, Ecology and Environment and Electrical Intelligent Vehicles

Y2 - 21 November 2018 through 25 November 2018

ER -

TANG X, GAO F, YAO K, WANG Y. Battery State of Charge Estimation Based on a Pure Hardware Implementable Method. In Proceeding of the 2nd Joint International Conference on Energy, Ecology and Environment (ICEEE 2018) and Electrical Intelligent Vehicles (ICEIV 2018). Destech Publications, Inc. 2018. (DEStech Transactions on Environment, Energy and Earth Sciences). doi: 10.12783/dteees/iceee2018/27801

Battery State of Charge Estimation Based on a Pure Hardware Implementable Method

Abstract

Publication series

Conference

Bibliographical note

Keywords

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Cite this