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Uninterruptible power supply state of charge estimation based on BP neural network

Published: 09 April 2021 Publication History

Abstract

Objetive: Display console is the software and hardware platform of warship and submarine control system. It's very important to strengthen the performance and improve the life of the Uninterruptible power supply (UPS) in display console . The residual capacity of UPS is a nonlinear function of voltage, discharge current, temperature and other variables. At present, there are some problems such as large measurement error and poor state prediction, what influence the battery power management system's management effectiveness. Therefore, this paper studies the estimation method of battery residual capacity based on BP Algorithm according to the principle of neural network, so as to improve the estimation accuracy of UPS residual capacity. Method: Firstly, we establish the BP neural network model consists of three layers, secondly gather UPS experimental data set, then build, train and test BP network model with LM algorithm by Matlab program language, finally gather the state of charge(SOC) training results. Result: Experimental results indicate that the method in this paper can estimate UPS SOC accurately and efficiently. Conclusion: It can satisfy the system requirements of uninterruptible power supply SOC estimation.

References

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Huixin Tian, Beiping Ouyang. Estimation of EV battery SOC based on KF dynamic neural network with GA [J].2018CCDC,2018
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Ting He, Donghai Li, Zhenlong Wu. A Modified Luenberger Observer for SOC Estimation of Lithium-Ion Battery [J].CCC2017,2017
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Li Shifeng, Qiu Zhanzhi, Fan Liping. Modeling and Simulation of Networked Control Systems Based on Improved BP Network [J]. Journal of System Simulation,2018, 30(6): 2279-2287
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Qiyan Yan, Yanning Wang. Predicting for Power Battery SOC Based on Neural Network [J]. CCC2017,2017, 838-841
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Huang Xu. Online Short-circuit Current Forecast Based on Improved BP Neural Network[J]. Hunan University, 2017, 3
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Li Shifeng; Qiu Zhanzhi; Fan Liping;Zhao Lina. Modeling and Simulation of Networked Control Systems Based on Improved BP Network[J].Journal of System Simulation,2018

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ICIT '20: Proceedings of the 2020 8th International Conference on Information Technology: IoT and Smart City
December 2020
266 pages
ISBN:9781450388559
DOI:10.1145/3446999
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 April 2021

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Author Tags

  1. BP neural network
  2. MATLAB
  3. state of charge
  4. uninterruptible power supply

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  • Research-article
  • Research
  • Refereed limited

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ICIT 2020
ICIT 2020: IoT and Smart City
December 25 - 27, 2020
Xi'an, China

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