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Battery Management Systems Accurate State-of-Charge Indication for Battery-Powered Applications

:	Valer Pop, Henk Jan Bergveld, Dmitry Danilov, Paul P. L. Regtien, Peter H. L. Notten
:	Battery Management Systems Accurate State-of-Charge Indication for Battery-Powered Applications
:	Springer-Verlag
:	9781402069451
:	1
:	CHF 155.60
:

:	Physikalische Chemie
:	English

:	238
:	Wasserzeichen/DRM
:	PC/MAC/eReader/Tablet
:	PDF

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.

"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.
"

	Table of contents	7
	List of abbreviations	10
	List of symbols	12
	Chapter 1 Introduction	20
	1.1 Battery Management Systems	20
	1.2 State-of-Charge definition	22
	1.3 Goal and motivation of the research described in this book	23
	1.4 Scope of this book	25
	1.5 References	26
	Chapter 2 State-of-the-Art of battery State-of-Charge determination	29
	2.1 Introduction	29
	2.2 Battery technology and applications	29
	2.3 History of State-of-Charge indication	34
	2.4 A general State-of-Charge system	41
	2.5 Possible State-of-Charge indication methods	42
	2.6 Commercial State-of-Charge indication systems	56
	2.7 Conclusions	59
	2.8 References	60
	Chapter 3 A State-of-Charge indication algorithm	64
	3.1 An introduction to the algorithm	64
	3.2 Battery measurements and modelling for the State-of-Charge indication algorithm	64
	3.3 States of the State-of-Charge algorithm	69
	3.4 Main issues of the algorithm	71
	3.5 General remarks on the accuracy of SoC indication systems	76
	3.6 Conclusions	76
	3.7 References	77
	Chapter 4 Methods for measuring and modelling a battery’s Electro-Motive Force	79
	4.1 EMF measurement	79
	4.2 Voltage prediction	85
	4.3 Hysteresis	99
	4.4 Electro-Motive Force modelling	102
	4.5 Conclusions	109
	4.6 References	109
	Chapter 5 Methods for measuring and modelling a battery’s overpotential	111
	5.1 Overpotential measurements	111
	5.2 Overpotential modelling and simulation	119
	5.3 Conclusions	124
	5.4 References	125
	Chapter 6 Battery aging process	126
	6.1 General aspects of battery aging	126
	6.2 EMF measurements as a function of battery aging	129
	6.3 Overpotential dependence on battery aging	147
	6.4 Adaptive systems	152
	6.5 Conclusions	156
	6.6 References	157
	Chapter 7 Measurement results obtained with new SoC algorithms using fresh batteries	159
	7.1 Introduction	159
	7.2 Implementation aspects of the algorithm	160
	7.3 Results obtained with the algorithm using fresh batteries	165
	7.4 Uncertainty analysis	169
	7.5 Improvements in the new SoC algorithm	178
	7.6 Comparison with Texas Instruments’ bq26500 SoC indication IC	188
	7.7 Conclusions	192
	7.8 References	193
	Chapter 8 Universal State-of-Charge indication for battery-powered applications	195
	8.1 Introduction	195
	8.2 Implementation aspects of the overpotential adaptive system	196
	8.3 SoC=f(EMF) and adaptive system	197
	8.4 Results obtained with the adaptive SoC system using aged adaptive system	199
	8.5 Uncertainty analysis	202
	8.6 Results obtained with other Li-based battery	203
	8.7 Practical implementation aspects of the SoC algorithm	214
	8.8 Conclusions	232
	8.9 References	233
	Chapter 9 General conclusions	235
	References	237