State of Charge Estimation for Off-Grid System Under Two Charge Controller Using Combination Methods

Waleed Karrar; Zhen Zhang

doi:doi:10.11648/j.ijse.20180201.11

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State of Charge Estimation for Off-Grid System Under Two Charge Controller Using Combination Methods

Waleed Karrar, Zhen Zhang

Published in International Journal of Systems Engineering (Volume 2, Issue 1)

Received: 28 June 2018 Accepted: 9 July 2018 Published: 26 July 2018

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Abstract

The state of charge (SOC) estimation plays important role in the battery energy storage system (BESS). Nowadays many semiconductor companies are paying more and more attention and investment to support many researchers to implement the state of charge for the batteries storage. the key to optimize the batteries storage is determine SOC value based on accuracy methods. a number of brief methods for SOC determination have been studied and compared with traditional methods the adaptive methods shown precise result because didn’t consider the dynamic effect of the batteries. In this paper, we use combination methods to estimate the SOC for lead-acid battery storage under two charge techniques namely Maximum Power Point Tracking – Plus Width Module (MPPT- PWM) when considering the effect of voltage drops on the estimation of SOC. The model uses the coulomb counting as an algorithm to determine the SOC and set it as a target in the backpropagation function in artificial neural network in MATLAB program (R2016a 64-bit (win64)). The simulation results show that the model is very precise to estimate the SOC in realistic operation.

Published in	International Journal of Systems Engineering (Volume 2, Issue 1)
DOI	10.11648/j.ijse.20180201.11
Page(s)	1-8
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

State of Charge (SOC), Lead-Acid Battery, Coulomb Counting (AH), Backpropagation (PB)

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APA Style

Waleed Karrar, Zhen Zhang. (2018). State of Charge Estimation for Off-Grid System Under Two Charge Controller Using Combination Methods. International Journal of Systems Engineering, 2(1), 1-8. https://doi.org/10.11648/j.ijse.20180201.11

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ACS Style

Waleed Karrar; Zhen Zhang. State of Charge Estimation for Off-Grid System Under Two Charge Controller Using Combination Methods. Int. J. Syst. Eng. 2018, 2(1), 1-8. doi: 10.11648/j.ijse.20180201.11

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AMA Style

Waleed Karrar, Zhen Zhang. State of Charge Estimation for Off-Grid System Under Two Charge Controller Using Combination Methods. Int J Syst Eng. 2018;2(1):1-8. doi: 10.11648/j.ijse.20180201.11

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@article{10.11648/j.ijse.20180201.11,
  author = {Waleed Karrar and Zhen Zhang},
  title = {State of Charge Estimation for Off-Grid System Under Two Charge Controller Using Combination Methods},
  journal = {International Journal of Systems Engineering},
  volume = {2},
  number = {1},
  pages = {1-8},
  doi = {10.11648/j.ijse.20180201.11},
  url = {https://doi.org/10.11648/j.ijse.20180201.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijse.20180201.11},
  abstract = {The state of charge (SOC) estimation plays important role in the battery energy storage system (BESS). Nowadays many semiconductor companies are paying more and more attention and investment to support many researchers to implement the state of charge for the batteries storage. the key to optimize the batteries storage is determine SOC value based on accuracy methods. a number of brief methods for SOC determination have been studied and compared with traditional methods the adaptive methods shown precise result because didn’t consider the dynamic effect of the batteries. In this paper, we use combination methods to estimate the SOC for lead-acid battery storage under two charge techniques namely Maximum Power Point Tracking – Plus Width Module (MPPT- PWM) when considering the effect of voltage drops on the estimation of SOC. The model uses the coulomb counting as an algorithm to determine the SOC and set it as a target in the backpropagation function in artificial neural network in MATLAB program (R2016a 64-bit (win64)). The simulation results show that the model is very precise to estimate the SOC in realistic operation.},
 year = {2018}
}

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TY  - JOUR
T1  - State of Charge Estimation for Off-Grid System Under Two Charge Controller Using Combination Methods
AU  - Waleed Karrar
AU  - Zhen Zhang
Y1  - 2018/07/26
PY  - 2018
N1  - https://doi.org/10.11648/j.ijse.20180201.11
DO  - 10.11648/j.ijse.20180201.11
T2  - International Journal of Systems Engineering
JF  - International Journal of Systems Engineering
JO  - International Journal of Systems Engineering
SP  - 1
EP  - 8
PB  - Science Publishing Group
SN  - 2640-4230
UR  - https://doi.org/10.11648/j.ijse.20180201.11
AB  - The state of charge (SOC) estimation plays important role in the battery energy storage system (BESS). Nowadays many semiconductor companies are paying more and more attention and investment to support many researchers to implement the state of charge for the batteries storage. the key to optimize the batteries storage is determine SOC value based on accuracy methods. a number of brief methods for SOC determination have been studied and compared with traditional methods the adaptive methods shown precise result because didn’t consider the dynamic effect of the batteries. In this paper, we use combination methods to estimate the SOC for lead-acid battery storage under two charge techniques namely Maximum Power Point Tracking – Plus Width Module (MPPT- PWM) when considering the effect of voltage drops on the estimation of SOC. The model uses the coulomb counting as an algorithm to determine the SOC and set it as a target in the backpropagation function in artificial neural network in MATLAB program (R2016a 64-bit (win64)). The simulation results show that the model is very precise to estimate the SOC in realistic operation.
VL  - 2
IS  - 1
ER  -

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Author Information

Waleed Karrar

College of Mechanical and Electrical Engineering, Hohai University, Changzhou, China
Zhen Zhang

College of Mechanical and Electrical Engineering, Hohai University, Changzhou, China

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APA Style

Waleed Karrar, Zhen Zhang. (2018). State of Charge Estimation for Off-Grid System Under Two Charge Controller Using Combination Methods. International Journal of Systems Engineering, 2(1), 1-8. https://doi.org/10.11648/j.ijse.20180201.11

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ACS Style

Waleed Karrar; Zhen Zhang. State of Charge Estimation for Off-Grid System Under Two Charge Controller Using Combination Methods. Int. J. Syst. Eng. 2018, 2(1), 1-8. doi: 10.11648/j.ijse.20180201.11

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AMA Style

Waleed Karrar, Zhen Zhang. State of Charge Estimation for Off-Grid System Under Two Charge Controller Using Combination Methods. Int J Syst Eng. 2018;2(1):1-8. doi: 10.11648/j.ijse.20180201.11

Copy | Download

@article{10.11648/j.ijse.20180201.11,
  author = {Waleed Karrar and Zhen Zhang},
  title = {State of Charge Estimation for Off-Grid System Under Two Charge Controller Using Combination Methods},
  journal = {International Journal of Systems Engineering},
  volume = {2},
  number = {1},
  pages = {1-8},
  doi = {10.11648/j.ijse.20180201.11},
  url = {https://doi.org/10.11648/j.ijse.20180201.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijse.20180201.11},
  abstract = {The state of charge (SOC) estimation plays important role in the battery energy storage system (BESS). Nowadays many semiconductor companies are paying more and more attention and investment to support many researchers to implement the state of charge for the batteries storage. the key to optimize the batteries storage is determine SOC value based on accuracy methods. a number of brief methods for SOC determination have been studied and compared with traditional methods the adaptive methods shown precise result because didn’t consider the dynamic effect of the batteries. In this paper, we use combination methods to estimate the SOC for lead-acid battery storage under two charge techniques namely Maximum Power Point Tracking – Plus Width Module (MPPT- PWM) when considering the effect of voltage drops on the estimation of SOC. The model uses the coulomb counting as an algorithm to determine the SOC and set it as a target in the backpropagation function in artificial neural network in MATLAB program (R2016a 64-bit (win64)). The simulation results show that the model is very precise to estimate the SOC in realistic operation.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - State of Charge Estimation for Off-Grid System Under Two Charge Controller Using Combination Methods
AU  - Waleed Karrar
AU  - Zhen Zhang
Y1  - 2018/07/26
PY  - 2018
N1  - https://doi.org/10.11648/j.ijse.20180201.11
DO  - 10.11648/j.ijse.20180201.11
T2  - International Journal of Systems Engineering
JF  - International Journal of Systems Engineering
JO  - International Journal of Systems Engineering
SP  - 1
EP  - 8
PB  - Science Publishing Group
SN  - 2640-4230
UR  - https://doi.org/10.11648/j.ijse.20180201.11
AB  - The state of charge (SOC) estimation plays important role in the battery energy storage system (BESS). Nowadays many semiconductor companies are paying more and more attention and investment to support many researchers to implement the state of charge for the batteries storage. the key to optimize the batteries storage is determine SOC value based on accuracy methods. a number of brief methods for SOC determination have been studied and compared with traditional methods the adaptive methods shown precise result because didn’t consider the dynamic effect of the batteries. In this paper, we use combination methods to estimate the SOC for lead-acid battery storage under two charge techniques namely Maximum Power Point Tracking – Plus Width Module (MPPT- PWM) when considering the effect of voltage drops on the estimation of SOC. The model uses the coulomb counting as an algorithm to determine the SOC and set it as a target in the backpropagation function in artificial neural network in MATLAB program (R2016a 64-bit (win64)). The simulation results show that the model is very precise to estimate the SOC in realistic operation.
VL  - 2
IS  - 1
ER  -

Copy | Download