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Universal State-of-Charge indication for battery-powered applications

Part of the Philips Research Book Series book series (PRBS, volume 9)

The battery EMF and overpotential were combined with the voltagerelaxation predictive method and the maximum capacity adaptive method in a new SoC evaluation system in chapter 7. Accurate results have been obtained with the SoC evaluation system using fresh batteries under an extended range of conditions. However, the SoC=f(EMF), overpotential and SoCl models include a variety of parameters that change during cycling of the battery. For a more accurate determination of the SoC when a battery ages, innovative adaptive systems were developed in chapter 6.

Implementation aspects and results obtained with the overpotential adaptive system will be presented in section 8.2. The focus in section 8.3 will be on a new adaptive system that combines the SoC=f(EMF) adaptive model under equilibrium conditions with an SoCl adaptive model under load conditions. Implementation aspects of the adaptive system in the SoC evaluation system will also be presented. Section 8.4 will present measurement results obtained with the adaptive SoC evaluation system. An uncertainty analysis will be discussed in section 8.5. The dream of the last 70 years of research in the field of SoC has been to design a universal SoC system that will adapt to any type of battery on line, without user intervention. Results obtained with the adaptive SoC evaluation system for another type of battery will be presented in section 8.6. These results prove that the developed SoC evaluation system is capable of adapting to batteries with different chemistries and of offering accurate, universal SoC indication. Designers will also be interested in the implementation requirements of the mathematical functions in a practical application. A possible implementation of the SoC evaluation system on a mobile phone platform will be presented in section 8.7. The usability of the SoC algorithm in a newly developed ultra-fast recharging algorithm will also be presented in this section. Finally, section 8.8 will present concluding remarks.

Keywords

Adaptive System Battery Voltage Evaluation Board Controller Board Battery Type 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer Science + Business Media B.V 2008

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