Paper
16 October 2024 Study on SOC estimation method for mine backup power supply
Haidong Xu, Wei Qin, Yanzhao Wang, Qiang Zhou, Lijun Su, Bo Qin
Author Affiliations +
Proceedings Volume 13291, Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024); 132911F (2024) https://doi.org/10.1117/12.3034207
Event: Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024), 2024, Changchun, China
Abstract
This paper focuses on nickel metal hydride batteries that are monomers. By increasing the adaptive rate of BP neural networks, the batteries can increase discharge, with temperature, current, and end voltage acting as the network's input characteristics. Nickel metal hydride batteries are the primary backup battery used in mining power supplies. Their high stability and energy density make them ideal for improving battery SOC (charge) estimation accuracy and prolonging service life at the same time. In accordance with the difference between the training sample's actual and expected output, adjust the momentum term; in accordance with the backpropagation error's direction change, raise the adaptive learning rate. In contrast to the traditional BP neural network approach, there was a 78% increase in convergence speed and a steady estimation error within 10%.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Haidong Xu, Wei Qin, Yanzhao Wang, Qiang Zhou, Lijun Su, and Bo Qin "Study on SOC estimation method for mine backup power supply", Proc. SPIE 13291, Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024), 132911F (16 October 2024); https://doi.org/10.1117/12.3034207
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KEYWORDS
Batteries

Neural networks

Neurons

Metals

Mining

Nickel

Power supplies

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