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Prediction of discharge capacity of lithium battery based on cloud neural network

  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The prediction of discharge capacity of lithium batteries was one of the main tasks of battery management system. The discharge capacity of lithium batteries was related with many parameters, including discharge current, voltage, temperature, and the past charge and discharge history. The prediction methods of existing lithium battery discharge capacity mostly have no learning capabilities and nonlinear prediction ability, in order to predict the discharge capacity of lithium battery more accurately, an algorithm Based on cloud neural network (CNN) was presented. On the basis of the analysis of the actual data of NASA, determine the related influence factors of discharge capacity, set up a corresponding CNN prediction model using cloud model, and use the cloud model for adaptive adjustment of the learning speed. Comparing with the traditional NN method, the simulation result demonstrates that the CNN prediction model has smaller prediction error.

Original languageEnglish
Title of host publicationProceedings - 2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013
Pages335-339
Number of pages5
DOIs
StatePublished - 2013
Event2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013 - Hangzhou, Zhejiang, China
Duration: 26 Aug 201327 Aug 2013

Publication series

NameProceedings - 2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013
Volume1

Conference

Conference2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2013
Country/TerritoryChina
CityHangzhou, Zhejiang
Period26/08/1327/08/13

Keywords

  • Cloud model
  • Discharge capacity prediction
  • Lithium battery
  • Neural network

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