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³¤°²´óѧѧ±¨£¨×ÔÈ»¿Æѧ°æ£©[ISSN:1006-6977/CN:61-1281/TN]

Issue:

2009Äê05ÆÚ

Page:

112-115

Research Field:

Publishing date:

2009-10-20

Info

Title:

New battery modeling analysis for electric vehicle

Author(s):

ZHANG Jieª²xin¹;  CHENG Bo¹;  ZHOU Yanª²lu¹;  WANG Junª²ping²

1. School of Engineering Machinery, Chang¬ðan University, Xi¬ðan 710064, Shaanxi, China; 2. School of Mechanical Engineering, Xi¬ðan Jiaotong University, Xi¬ðan 710049, Shaanxi, China

Keywords:

automobile engineering;  electric vehicle;  battery modeling;  immune clustering;  RBF network

PACS:

U469.72

DOI:

-

Abstract:

In order to solve the problems of traditional neural network battery modeling method, the computational intelligence algorithm is used to train RBF networks and to realize the nickelª²hydrogen batteries modeling, the immune clustering algorithm is adopted to extract the radial basis function. Combined with adaptive parallel immune evolutionary strategy(PIES), a more effective strategy of constructing RBF network is formed. This method is verified by the battery discharge experiment. The results show that the method proposed in this paper can reduce training time and the number of hidden nodes, and it can more effectively determine the center width of hide layer. The modeling is more accurate than the traditional methods, the most voltage error of this modeling is less than 0.3 V. 7 figs, 9 refs.

References:

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Memo

Memo:

-

Common functions

Last Update: 2009-10-20