DocumentCode
3546067
Title
Research upon the submarine high-capacity lead-acid battery discharge characteristic model
Author
Yang, Kun ; Ouyang, Guangyao ; Zhang, Jingqiu
Author_Institution
Power Eng. Dept., Naval Univ. of Eng., Wuhan, China
fYear
2009
fDate
16-19 Aug. 2009
Abstract
Long-playing, the simulation of the high-capacity lead-acid battery is very difficult. Basing on the particular research upon the characteristic of the submarine battery discharge process, at the same time in view of the electrochemistry mechanism complexity of the lead-acid battery, a new algorithm which is the integration of the improved BP neural network algorithm by adding the item of the momentum and the golden cut algorithm is brought forward in the paper to solve the problem of the submarine battery discharge process modeling, in succession the model is consummated by additional research on the battery state of charge parameter. Simulation results show that the model can be commendably used in engineering practice, thus the building method of the battery discharge model also provides us a new effective approach for the simulation of the highly complex electrochemistry process, and it also establishes a foundation for the integration simulation of the whole submarine power system.
Keywords
backpropagation; battery powered vehicles; electrochemistry; lead acid batteries; neural nets; power engineering computing; underwater vehicles; BP neural network algorithm; charge parameter; electrochemistry mechanism; electrochemistry process; golden cut algorithm; submarine high-capacity lead-acid battery discharge; submarine power system; Battery charge measurement; Fault location; Instruments; Neural networks; Power engineering and energy; Power measurement; Power system modeling; Power system simulation; Underwater vehicles; Voltage; eural network; golden cut algorithm; simulation;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-3863-1
Electronic_ISBN
978-1-4244-3864-8
Type
conf
DOI
10.1109/ICEMI.2009.5274709
Filename
5274709
Link To Document