arrow
Return

An On-Line Battery Parameter Detection Algorithm for Sinusoidal Ripple Charge (SRC) Method

delete2020-02-01
delete2
PRE
AI
H
Hossein Hajisadeghian *
A
Ali Akbar Moti Birjandi
M
Mehdi Asadi
H
Hossein Vazini
DOI:10.1109/pedstc49159.2020.9088417delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Sinusoidal Ripple Current (SRC) charge method is a new technique which has been more developed among fast charge algorithms due to higher charge speed, lower temperature rise and adverse effects on battery lifetime. Studies have been focused on presenting an appropriate algorithm to find optimal charge frequency, which minimizes battery impedance. Some of proposed methods suffer from accuracy and other methods increase complexity in practice. In this paper, a new simple on-line method based on battery parameters detection has been developed to overcome complexity of previous works. Although this method is simple, it has enough accuracy to extract battery parameters and find the optimal charge frequency. In order to show the performance of proposed algorithm, a laboratory battery charger consists of a Phase Shifted Full Bridge (PSFB) DC/DC converter has been employed to test proposed algorithm. In addition, results of the proposed algorithm have been compared with conventional CC/CV algorithm and fixed optimal frequency charge algorithm. Experimental results show, proposed algorithm to find optimal frequency reduces charge time about 9.25% in comparison with conventional CC/CV algorithm and 0.25% compared to fixed optimal frequency charge algorithm.
Keywords:
Battery Parameters Detection
Fast Battery Charger
Sinusoidal Ripple Charge Algorithm
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

P
Power Electronics, Drive Systems, and Technologies Conference
IF:
0
Papers:
34
Citations:
0

Organization

S
shahid rajaee teacher training university (srttu)
Scholars:
1.0K
Papers: 1.0K
Citations: 0