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Adaptive State-of-Charge Indication System for Li-ion Battery-Powered Devices
1
Holst Centre / IMEC-NL, High Tech Campus 48, 5656AE, Eindhoven, the Netherlands
2
NXP Research, High Tech Campus 5, 5656AE, Eindhoven, the Netherlands
3
Eindhoven University of Technology, P.O. Box 513, 5600MB, Eindhoven, the Netherlands
4
Philips Research Laboratories, High Tech Campus 4, 5656AE, Eindhoven, the Netherlands
5
University of Twente, P.O. Box 217, 7500AE, Enschede, the Netherlands
*
Author to whom correspondence should be addressed.
World Electr. Veh. J. 2007, 1(1), 38-45; https://doi.org/10.3390/wevj1010038
Published: 28 March 2008
PDF [541 KB, uploaded 10 May 2018]
Abstract
An algorithm that combines adaptive system with Electro-Motive-Force (EMF) measurements during equilibrium and current measurement and integration during (dis)charge states has been implemented in a real-time SoC evaluation system. During the discharge state also the effect of the overpotential is considered. The overpotential model includes a variety of parameters that are changing during cycling of the battery. Adaptive methods for the battery maximum capacity and for the overpotential model parameters are presented in this paper. The final aim is to predict the SoC and the remaining run-time of a Li-ion battery within 1% inaccuracy under all realistic user conditions.
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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MDPI and ACS Style
Pop, V.; Bergveld, H.; Danilov, D.; Notten, P.; Regtien, P. Adaptive State-of-Charge Indication System for Li-ion Battery-Powered Devices. World Electr. Veh. J. 2007, 1, 38-45.
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