Abstract
In this paper, a study of Li-ion battery charge forecasting using Grey theory is presented. A test-bench system for the battery charge forecasting is designed and built. Using this test-bench system, the charge condition for charging Li-ion battery can be easily set and the data of the charged Li-ion battery can be obtained, simultaneously. Experimental results show that the GM(1,1) model can actually predict the Li-ion battery voltage curve when its sampling period is smaller than the safe sampling period. How the safe sampling period determined is presented, and a mathematical formula is for determining the safe sampling period successfully obtained in this paper. Finally, a test example is implemented to assess this proposed Li-ion battery charging forecast method. The experimental results are very attractive as theory predicts.
| Original language | English |
|---|---|
| Pages (from-to) | 744-749 |
| Number of pages | 6 |
| Journal | INTELEC, International Telecommunications Energy Conference (Proceedings) |
| Publication status | Published - 2003 Dec 1 |
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All Science Journal Classification (ASJC) codes
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering
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A study of Li-ion Battery Charge Forecasting Using Grey Theory. / Chen, L. R.; Lin, C. H.; Hsu, R. C.; Ku, B. G.; Liu, C. S.
In: INTELEC, International Telecommunications Energy Conference (Proceedings), 01.12.2003, p. 744-749.Research output: Contribution to journal › Article
TY - JOUR
T1 - A study of Li-ion Battery Charge Forecasting Using Grey Theory
AU - Chen, L. R.
AU - Lin, C. H.
AU - Hsu, R. C.
AU - Ku, B. G.
AU - Liu, C. S.
PY - 2003/12/1
Y1 - 2003/12/1
N2 - In this paper, a study of Li-ion battery charge forecasting using Grey theory is presented. A test-bench system for the battery charge forecasting is designed and built. Using this test-bench system, the charge condition for charging Li-ion battery can be easily set and the data of the charged Li-ion battery can be obtained, simultaneously. Experimental results show that the GM(1,1) model can actually predict the Li-ion battery voltage curve when its sampling period is smaller than the safe sampling period. How the safe sampling period determined is presented, and a mathematical formula is for determining the safe sampling period successfully obtained in this paper. Finally, a test example is implemented to assess this proposed Li-ion battery charging forecast method. The experimental results are very attractive as theory predicts.
AB - In this paper, a study of Li-ion battery charge forecasting using Grey theory is presented. A test-bench system for the battery charge forecasting is designed and built. Using this test-bench system, the charge condition for charging Li-ion battery can be easily set and the data of the charged Li-ion battery can be obtained, simultaneously. Experimental results show that the GM(1,1) model can actually predict the Li-ion battery voltage curve when its sampling period is smaller than the safe sampling period. How the safe sampling period determined is presented, and a mathematical formula is for determining the safe sampling period successfully obtained in this paper. Finally, a test example is implemented to assess this proposed Li-ion battery charging forecast method. The experimental results are very attractive as theory predicts.
UR - http://www.scopus.com/inward/record.url?scp=1542330089&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=1542330089&partnerID=8YFLogxK
M3 - Article
SP - 744
EP - 749
JO - INTELEC, International Telecommunications Energy Conference (Proceedings)
JF - INTELEC, International Telecommunications Energy Conference (Proceedings)
SN - 0275-0473
ER -