This book describes the field of State-of-Charge (SoC) indication for rechargeable batteries. An overview of the state-of-the-art of SoC indication methods including available market solutions from leading semiconductor companies is provided. All disciplines are covered, from electrical, chemical, mathematical and measurement engineering to understanding battery behavior. This book will therefore is for persons in engineering and involved in battery management.

Battery Management Systems: Accurate State-of-Charge Indication for Battery-Powered Applications describes the field of State-of-Charge (SoC) indication for rechargeable batteries. With the emergence of battery-powered devices accurately estimating the battery SoC, and even more important the remaining time of use, becomes more and more important.

An overview of the state-of-the-art of SoC indication methods including available market solutions from leading semiconductor companies, e.g. Texas Instruments, Microchip, Maxim, is given in the first part of this book. Furthermore, a universal SoC indication system that enables 1% or better accuracy under all realistic user conditions is developed. A possible integration with a newly developed ultra-fast recharging algorithm is also described.

The contents of this book builds further on the contents of the first volume in the Philips Research Book Series, Battery Management Systems - Design by Modelling. Since the subject of battery SoC indication requires a number of disciplines, this book covers all important disciplines starting from (electro)chemistry to understand battery behaviour, via mathematics to enable modelling of the observed battery behaviour and measurement science to enable accurate measurement of battery variables and assessment of the overall accuracy, to electrical engineering to enable an efficient implementation of the developed SoC indication system. It will therefore serve as an important source of information for any person working in engineering and involved in battery management.

Leseprobe
" Chapter 3

A State-of-Charge indication algorithm (p. 47-48)

As discussed in chapter 2, many advances have been made in State-of- Charge (SoC) indication in recent years, both through continued improvement of the SoC algorithms and through the development of more accurate hardware systems. Nevertheless, there is still no ""ideal"" SoC system that gives accurate indications under all realistic user conditions. The ""ideal"" SoC system is obviously one that is not expensive, can handle all battery chemistries, can operate over a wide range of load currents and can deal with the aging effect. Leading semiconductor companies (e.g. Philips [1]-[3], NXP Research, Texas Instruments [4]-[6], Microchip [7], [8] Maxim [9], [10], etc.) are paying more and more attention to accurate State-of-Charge indication in attempts to find that ideal system.

A SoC algorithm that combines some form of adaptivity with direct measurement and book-keeping systems was developed and implemented by Bergveld et al. in 2000 [1]-[3]. By implementing the mathematical models described in [1], this algorithm was found to be the most sophisticated and accurate [11], [12]. This chapter will give a complete description of this algorithm, which serves as the starting point of this book. This chapter is organised as follows.

An introduction to the algorithm is given in section 3.1. Section 3.2 describes the models and states of the SoC indication system. The main aspects of the algorithm are given in section 3.3. The focus in section 3.4 is on accuracy problems. Section 3.5 presents concluding remarks.

3.1 An introduction to the algorithm

The SoC indication algorithm presented by Bergveld et al. in [1]-[3] aims to eliminate the main drawbacks and combine the advantages of the direct measurement and book-keeping methods described in Chapter 2. The basis of the SoC algorithm is Electro-Motive Force (EMF) measurement during equilibrium and current measurement and integration during charge and discharge. During discharge, in addition to simple Coulomb counting, the effect of the overpotential is also considered [1]. A method has also been developed for updating the value of the maximum capacity for coping with capacity loss due to the aging effect. The algorithm will be described below for a Panasonic CGR17500 Li-ion battery, but the basis of the algorithm holds for other types of Li batteries, too. The rated capacity of this battery is 720 mAh.

3.2 Battery measurements and modelling for the State-of-Charge indication algorithm

The battery model applied in the developed SoC indication algorithm describes the battery EMF and overpotential behaviour, neither of which can be measured directly. The EMF and overpotential curves have been measured with an accurate battery tester and implemented in the Battery Management System (BMS) using mathematical-function approximations [1], [13]. Both the measurement and the implementation method contribute to the final accuracy of the SoC indication.
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Inhalt
State-of-the-Art of battery State-of-Charge determination.- A State-of-Charge indication algorithm.- Methods for measuring and modelling a battery's Electro-Motive Force.- Methods for measuring and modelling a battery's overpotential.- Battery aging process.- Measurement results obtained with new SoC algorithms using fresh batteries.- Universal State-of-Charge indication for battery-powered applications.- General conclusions.