Journal
MODERN PHYSICS LETTERS B
Volume 32, Issue 34-36, Pages -Publisher
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0217984918400626
Keywords
Lithium-ion battery; neural network; fuzzy control; call-back voltage; SOC
Funding
- National Key Research and Development Program of China [2017YFF0210002]
- Changzhou Science Technology project [CJ20179038]
- university brand specialty construction supporting project of Jiangsu Province [PPZY2015B129]
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The lithium ion battery is considered as the experimental object, and its discharge characteristics are studied. A model of the battery in different charge-states is established by a tool of neural network while battery's rebound voltage, temperature and load are set as input parameters. The validity of the model is tested based on the experimental data. The accuracy, adaptability and stability of the SOC in this model is validated in a variety of the working conditions, and the accuracy of the model is demonstrated to be higher than 5%.
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