ACM Home Page
Please provide us with feedback. Feedback
Accurate battery lifetime estimation using high-frequency power profile emulation
Full text PdfPdf (300 KB)
Source International Symposium on Low Power Electronics and Design archive
Proceedings of the 2005 international symposium on Low power electronics and design table of contents
San Diego, CA, USA
POSTER SESSION: Power supply design table of contents
Pages: 307 - 310  
Year of Publication: 2005
ISBN:1-59593-137-6
Authors
Farhan Simjee  University of California-Irvine, Irvine, CA
Pai H. Chou  University of California-Irvine, Irvine, CA
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 11,   Downloads (12 Months): 72,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1077603.1077676
What is a DOI?

Warning: The download time has expired please click on the item to try again.


ABSTRACT

For accurate estimation of battery lifetime, researchers have developed analytical and empirical models and applied them to representative load profiles. However, accurate battery models are not available for most batteries on the market. Although high-accuracy simulation models exist for certain battery chemistries, they are computationally intensive and still require calibration through trial and error. To address this problem, this paper presents a low-cost load emulation platform for automated, accurate battery estimation. By draining a battery with high-frequency emulation of a system power profile, all of the battery characteristics are accounted for, including the discharge rate and recovery effects. A designer can then accurately observe how the system effects battery life, quantify lifetime performance for multiple batteries, and ultimately optimize the system's power scheduling around a particular battery


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

1
 
2
J.S. Newman. FORTRAN programs for simulation of electrochemical systems. http://www.cchem.berkeley.edu/~jsngrp/.
 
3
 
4
K. Lahiri, A. Raghunathan, and S. Dey. Efficient power profiling for battery-driven embedded system design. IEEE Trans. on Computer-aided Design of Integrated Circuits and Systems, 23(6):919--932, June 2004.
5
 
6
Agilent Technologies. Agilent DC Electronics Loads Models N3300A-N3307A.
 
7
J.A. McNeill, M. Layler, G. Levesque, J. Ruiter, and J. Noon. A 50 A, 1-us-rise-time, programmable electronic load instrument for measurement of microprocessor power supply transient performance. In Proceedings of Instrumentation and Measurement Technology Conf., pages 410--414, May 2000.

Collaborative Colleagues:
Farhan Simjee: colleagues
Pai H. Chou: colleagues