IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 48, NO. 3, JUNE 2001
585
Fuzzy-Controlled Li–Ion Battery Charge System with
Active State-of-Charge Controller
Guan-Chyun Hsieh, Senior Member, IEEE, Liang-Rui Chen, and Kuo-Shun Huang
Abstract—A fuzzy-controlled active state-of-charge controller
(FC-ASCC) for improving the charging behavior of a lithium–ion
(Li–ion) battery is proposed. The proposed FC-ASCC is designed
to replace the general constant-voltage charging mode by two
kinds of modes: sense and charge. A fuzzy-controlled algorithm
is built with the predicted charger performance to program the
charging trajectory faster and to remain the charge operation in a
proposed safe-charge area (SCA). A modeling work is conducted
for analyzing and describing the Li–ion battery in charging
process. A three-dimensional Y-mesh diagram for describing the
charging trajectories of the proposed FC charger is simulated. A
prototype of a Li–ion battery charger with FC-ASCC is simulated
and realized to assess the predicted charging performance.
Experiment shows that the charging speed of the proposed FC
charger compared with the general one increases about 23% and
the charger can safely work in the SCA.
Index Terms—Charge mode, fuzzy-controlled
state-of-charge controller, safe-charge area, sense mode.
active
I. INTRODUCTION
T
HE rapid progress in developing computer and communication systems promotes the design trend of portable
electronic apparatuses which are light, thin, short, and small.
The secondary batteries then become the significant power
source for the portable electronic apparatuses. Nowadays,
widely used secondary batteries such as NiCd and NiMH are
not satisfying people’s requirements due to lack of high-energy
capacity and bulky size. Furthermore, another consideration
is possibly the environmental pollution, such as from the
cadmium in a NiCd battery. However, many advantages, such
as no memory effect, high operation voltage, and high energy
density in weight (Wh/kg) and volume (Wh/L) forward the
lithium–ion (Li–ion) battery in becoming the acceptable battery
for portable electronic systems [1]–[8]. For charging processes,
constant-current (CC) and constant-voltage (CV) techniques
are still widely used for Li–ion batteries [2], [7], [9]. However,
it always takes about 25% 40% of the complete charging
period to fulfill about 75% 80% of the totally required charge
Manuscript received March 23, 2000; revised February 14, 2001. Abstract
published on the Internet February 15, 2001.
G.-C. Hsieh is with the Department of Electronic Engineering, National
Taiwan University of Science and Technology, Taipei 106, Taiwan R.O.C.
(e-mail: gchsieh@et.ntust.edu.tw).
L.-R. Chen is with the Department of Electronic Engineering, National
Taiwan University of Science and Technology, Taipei 106, Taiwan R.O.C., and
also with the Department of Electronic Engineering, Chien Kuo Institute of
Technology, Changhua 500, Taiwan, R.O.C.
K.-S. Huang was with the Department of Electronic Engineering, National
Taiwan University of Science and Technology, Taipei 106, Taiwan R.O.C. He
is now with Sunplus Technology Company, Ltd., Hsinchu 300, Taiwan, R.O.C.
Publisher Item Identifier S 0278-0046(01)03813-8.
capacity during the CC mode, and the time required for the remaining 20% 25% capacity to be charged in CV mode should
be 3 the charging length in CC mode [2]. Due to complex
electrochemical characteristics in a Li–ion battery, a precise
model is difficult and complex to build [10]. In addition, human
expertise in the charging process for a Li–ion battery is also
not accurately realized by a usual control rule. Thus, a fuzzy
control sense is adopted for solving the nature language of the
Li–ion battery charger in man–machine interface [11], [12].
The estimation of the remnant charge in the secondary battery
has been conducted by the open-circuit voltage monitoring and
Coulomb counting methods, but it is not accurate [13]. James
proposed a microprocessor-based estimator for detecting the
state-of-charge in the battery by combining the two methods
mentioned [14]. Stolitzka indicated that Jame’s method could
provide 1% accuracy for the charge detection but kept the high
cost for realization [13], [14]. In this paper, a fuzzy-controlled
active state-of-charge controller (FC-ASCC) is presented to
replace the usual CV mode. The proposed FC-ASCC can
instantly monitor the charging state of the Li–ion battery
for adaptively programming its charging performance. A
fuzzy-controlled current source (FCCS) in FC-ASCC can
adaptively provide a suitable charging current for the battery
charge. The proposed FC-ASCC is conducted by a sense mode
(SM) and a charge mode (CM) with a fuzzy-controlled strategy
under a safe-charge area (SCA). In this paper, modeling and
fuzzifying for describing the proposed system are conducted.
A prototype of a Li–ion battery charger with two batteries in
series package is designed and realized to assess the system
performance. The charging time of the proposed FC-ASCC
compared with the general CV mode has been reduced by
about 23%.
II. FC-ASCC
Shown in the dotted block of Fig. 1(a) is the proposed
FC-ASCC, which consists of a current/voltage converter
(C/V-C), a fuzzy-logic controller (FLC), an FCCS, and a clock
timer. All of them are driven by a constant voltage source
(CVS). The proposed FC-ASCC is operated in an SCA, which
is defined as a safe maximum in-charge voltage of the Li–ion
battery. The periodical SM and CM conduct the FC-ASCC with
and a charging period
defined in Fig. 1(b)
a sense period
and (c). In SM, the open-circuit voltage detection (OVD) and
the charging current detection (CCD) are the primary work
for checking the state of charge in the Li–ion battery. In other
words, the OVD is for detecting the open-circuit voltage
of the package battery in
, and the CCD is for sensing the
0278–0046/01$10.00 © 2001 IEEE
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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 48, NO. 3, JUNE 2001
Fig. 1. (a) Configuration of the proposed FC charge system. (b) Control sequence for (a). (c) Working state diagram for (a).
Fig. 2. Structure of FLC.
required charging current
in
. After the SM,
and
are then converted into a coded number through the
C/V-C. A suitable control algorithm from the FLC is then
deduced to the FCCS to charge the Li–ion battery with
in CM during the period . Remarkably, the minimum sense
is determined by the computing speed of the
period
s is
microprocessor and the number of charging periods
determined according to the defined SCA of the Li–ion battery.
HSIEH et al.: FUZZY-CONTROLLED Li–ION BATTERY CHARGE SYSTEM
Fig. 3.
587
Equivalent charging models for one-cell Li–ion battery. (a) General charging strategy. (b) Proposed FC charging strategy.
For ease of control, a digitally coded strategy is used in the
,
, and
are
proposed FC-ASCC. The coded
,
, and
, respectively. The FLC in
then given by
Fig. 2 consists of a fuzzifier, a rule library, an inference engine,
(
),
a defuzzifier, and three prescaling factors,
(
), and
(
). For ease of analysis and description
in our proposed charging rule, we presume that all battery cells
in the battery pack have the same characteristics. Thus, the
and
are
normalization factors of the package battery
defined as
(1)
and
Fig. 4. Predicted charging trajectories of the general ( - - -) and proposed FC
(—) charging processes for one Li–ion battery.
Thus, the open-circuit voltage
, sense current
, and
of the one-cell battery are, respectively,
charging current
given by
(2)
and
are the number of batteries for series package
where
is deand shunt package, respectively. The scaling factor
fined as
(3)
(4)
(5)
and
(6)
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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 48, NO. 3, JUNE 2001
Fig. 5. Membership functions of the charging strategy in FC-ASCC mode for (a) voltage sense, (b) current sense, and (c) the output of FLC.
The coded numbers
,
, and
are then represented by
TABLE I
CONTROL RULE TABLE FOR THE FC-ASCC
(7)
(8)
and
(9)
,
A set of fuzzy variables for the one-cell coded number (
) is then given through the fuzzifier. According to the prescribed rule library and the fuzzy variables, a deduced fuzzy set
from the inference engine is then obtained. Accordingly, after
, a suitable charging current
from the
defuzzifying the
FCCS is then provided for charging the Li–ion package battery
in CM. A cyclic charging process continues until the sense curis smaller than or equal to 0.01 C, where the battery
rent
is fully charged [8].
III. CONTROL STRATEGY
The proposed fuzzy-controlled and the general chargers for
one Li–ion battery are, respectively, modeled in Fig. 3(a) and
(b), in which the CC mode in each chargers is the same. The
FC-ASCC mode is proposed to replace the general CV mode
so as to proceed with the charging process in an SCA and reduce the charging time. The predicted charging trajectories of
the two charge systems are, respectively, depicted in Fig. 4 for
comparison. Remarkably, the charging performances are nearly
the same in both two CC modes, but the charging speed in the
FC-ASCC is obviously faster than that in the general CV mode.
in the general CV mode and the CM
The charging current
of the FC-ASCC for one Li–ion battery cell can be estimated by
(10)
,
, and
are, respectively, the in-charging
where
voltage, the open-circuit voltage, and the inner resistance of the
is detected
Li–ion battery. In Fig. 3(b), the sense current
with the nominal reference
at the CCD of SM during
V and can be described by
(11)
HSIEH et al.: FUZZY-CONTROLLED Li–ION BATTERY CHARGE SYSTEM
589
Fig. 6. Simulations of the proposed FC charging trajectories in 3-D Y-mesh diagram. (a) m = 0:2. (b) m = 0:5. (c) m = 0:8.
Remarkably, (11) is valid when the detected
at OVD of SM
. Interestingly, in (11) is
is not greater than 4.2 V during
inherently temperature dependent [1], but this effect can be inand no temperature consideration is
cluded in the measured
and
required in the proposed FC-ASCC. With the detected
, a suitable charging current
from FCCS is provided
for charging the Li–ion battery in CM during . The required
in the FCCS can then be described by
charging current
(12)
is a function of the FLC. Since the maximum fault
where
over voltage threshold in the one-cell Li–ion battery is 4.25 V
should be limited by
[15], [16], the in-charging voltage
(13)
From (10) and (13), the required charging current
can then be determined by
in CM
(14)
Substituting (11) into (14), we have
(15)
Equation (15) is the design reference for the safe-charge
consideration in determining the membership function in the
FLC. The membership function of the charging strategy for the
FC-ASCC is described in Fig. 5. Fig. 5(a) shows the degree of
(coded as
) versus
the voltage-sense fuzzy variable
(
) and is described by two
the open-circuit voltage
linguistic terms of Small and Big in trapezoid form. Fig. 5(b)
(
)
is the degree of the current-sense fuzzy variable
(
) and is described by Small, Middle, and Big
versus
in triangular form. Fig. 5(c) is the degree of the output fuzzy
(
) versus
(
) and is described by sinvariable
gleton types of Small, Middle, and Big. The singleton type used
is to minimize the accounting capacity of the microprocessor
used in the FC-ASCC. The singleton type Small is preset at
(i.e.,
H) since the trickle current in
the Li–ion battery is only 1% of the bulk current [15], where
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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 48, NO. 3, JUNE 2001
is the maximum charge current (i.e., bulk current) and
is defined as singleton type Big. The singleton type Middle is
(
). The value
defined by
is determined according to the charge trajectory to be used
is
and clearly depicted in Fig. 7, of which the selection of
described in detail in Section IV. The fuzzy control rules for
the FC-ASCC are briefly described as follows.
is Small (i.e.,
V and
1) When
), it means that the energy to be charged to the battery is large. In this sense, the rule is
is Small
is Big
(R.1)
is Big (i.e.,
V and
)
2) When
is Big (i.e.,
, and
),
and
the energy to be stored in the battery is still large and
the required charging current in CM would be Big (i.e.,
and
). The rule is
is Big
is Big
is Big
(R.2)
is Big (i.e.,
V and
)
is Middle (i.e.,
and
), the energy to be stored in the battery is not
still large and the required charging current in CM would
and
). The
be Middle (i.e.,
rule is
3) When
and
is Big
is Middle
is Middle
(R.3)
is Big (i.e.,
V and
)
is Small (i.e.,
and
), the energy to be stored in the battery is
small and the required charging current in CM would be
and
) to avoid
Small (i.e.,
overcharge. The rule is
4) When
and
is Big
is Small
is small
(R.4)
The complete fuzzy control rule for the FC-ASCC is tabulated
in Table I.
IV. DESIGN CONSIDERATIONS
The complete charging period and the value of the membership function are the key factors in designing the proposed
FC-ASCC. The complete period consists of the sense period
and the charge period . Two samples conducted in SM
include the detection of
in
and the
during period
in
. The charge period
is for charging the
sense of
is
Li–ion battery in CM mode. The sense time
primarily determined by the operation speed of the fuzzy inference and is much smaller than . For convenience in design,
. The Li–ion battery voltage varying
we presume that
with respect to time is quite a linear portion in CC mode [3],
is for describing a capacitor in
[9]. Since
Fig. 7. Required charging current i (t) in CM with respect to the sense current
i (t) in SM for various ms.
linear charge with a constant current , we can then approximately describe the Li–ion battery as a capacitor during the
charging process for ease of analysis. In each charging period
, the charge
incremented in Li–ion battery can then be
given by
(16)
is the charging current deduced from the FCCS at
. Since
is almost a constant current during the
charging period ,
where
Constant
Therefore, the open-circuit voltage
Li–ion battery can be given by
(17)
incremented in the
(18)
is the equivalent capacity of the Li–ion battery in
where
farads. From (16) and (18), we have
(19)
from the FC-ASCC is
Since the deduced charging current
distinct in each period , the totally accumulated charge
can then be given by
(20)
where is the number of charging times in CM. The total increon the Li–ion battery during
periods
mental voltage
is thus given by
(21)
For safe charging consideration, the in-charging voltage on the
battery voltage during CM mode should not be over 4.25 V
HSIEH et al.: FUZZY-CONTROLLED Li–ION BATTERY CHARGE SYSTEM
591
Fig. 8. (a) Realization block diagram of the proposed FC charge system. (b) Control time sequences for the charging strategy.
[15], [16]. Thus, the final incremental voltage given by
should be satisfied with
(22)
From (19) and (22), we have
(23)
The complete charging period
by
can then be estimated from (23)
(24)
For convenience in analysis, we take the results given from
Section V for describing the design consideration. Fig. 6 is a
three–dimensional (3-D) Y-mesh diagram for describing the
charging trajectories of the proposed FC charger in simulation,
in which three kinds of typical charging conditions such as
,
, and
are shown. It is clearly
shown that the charging trajectories during CC mode are all
Fig. 9. Remanent charge capacity percent with respect to the sense current
i (t) for Li–ion battery.
the same, but are different for various s in FC-ASCC mode.
in CM with respect to the sensed
in
The deduced
SM for various s is simulated in Fig. 7. Interestingly, we
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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 48, NO. 3, JUNE 2001
Fig. 10. Charging performance of the general (- - -) and proposed FC (—) charging systems. (a) Remanent capacity versus charging time. (b) Detected open-circuit
voltage v (t) and the in-charging voltage v (t). (c) Charging trajectories of the deduced i (t).
find that the charging trajectory in the FC-ASCC mode with
is the same as that in the general CV mode. When
, the deduced
in FC-ASCC is less than the
charging current in the general CV mode, conversely when
. In order to increase the charging speed,
is the preferred design reference for the proposed FC-ASCC.
However, the maximum deduced current should be limited by
value can be easily
(15) for safe-charge consideration. The
determined by plotting the equation (15) in Fig. 7, in which the
shaded area is the design reference.
V. REALIZATION AND EXPERIMENTATION
A design example of the proposed FC-ASCC for the Li–ion
battery is examined. Two Li–ion batteries (Panasonic CGR
and
18 650) to be charged are packaged in series (
). The final and the maximum permissible in-charge
voltages are, respectively, specified as 8.4 V (4.2 V/cell)
and 8.5 V (4.25 V/cell). For safe-charge consideration, the
(bulk curmaximum and minimum charging currents
(trickle current) are, respectively, specified
rent) and
A
C) and 5 mA (i.e.,
as 0.5 A (i.e.,
C), where
A is the
rated charge current for the package battery. The physical block
diagram of the proposed FC-ASCC and its control sequence
are shown in Fig. 8. The realized FC-ASCC is composed of
a timer, two switches, a constant voltage source, a constant
current source, a fuzzy-controlled current source circuit, an
A/D converter (ADC0804), a D/A converter (DAC0800), and
an FLC with latches (8-bit microprocessor EM78447B). In this
example, we can get
,
, and
from
(1)–(3). By experiments, the equivalent capacity of the battery
F and its inner series
is estimated as
. Since the maximum charging current
resistance
A, from (24), the maximum charge period
can be estimated as
(25)
s. The required sampling
In this design, we choose
, detecting
, and fuzzy infertime, including sensing
s; the charging time in CM is then
ence, is about
s. The permissible charging current in CM can then
by
be given from (15) with
(26)
The proper charging current in this design is then given from
(26) as shown in the shaded area of Fig. 7. It is clearly shown
HSIEH et al.: FUZZY-CONTROLLED Li–ION BATTERY CHARGE SYSTEM
that the maximal
value cannot be over 0.74 and we choose
as the design reference. The remanent charge cafor this package
pacity with respect to the sense current
Li–ion battery is measured in Fig. 9, in which the sense curis inversely proportional to the remanent charge carent
pacity. In words, it means that the remanent charge in the batis large. Thus, the remanent charge in the
tery is small if
.
battery can then be easily estimated by the sense current
The charging behaviors of the proposed FC-ASCC and the general charger are experimentally represented in Fig. 10. Fig. 10(a)
shows the charged capacity with respect to the charging time.
Fig. 10(b) shows the open-circuit voltage and the in-charging
voltage in detection and charging states, respectively. Clearly,
the open-circuit voltage is always less than in-charging voltage
until both voltages are almost equal to each other when the battery is fully charged. Fig. 10(c) shows the charging trajectories
. Obviously, the charging current for the FC-ASCC
of the
is greater than that in CV mode of the general charger before
reaches 0.01 C. Thus, the charging
the charging current
times for the proposed FC charger and the general charger are
243 and 280 min, respectively. The charging performance in the
FC-ASCC has been improved by about 23% compared with that
in the usual CV mode. Remarkably, the charging times in CC
mode for both systems are almost the same as 133 min.
VI. CONCLUSION
In this paper, an FC-ASCC has been proposed to replace the
general CV charge mode in a charger system. The proposed FC
charge system can actually increase the charge speed and continue the charge process in an SCA after the CC mode. Two
processes, SM and CM, included in the FC-ASCC are for periodically sensing the charging state and keeping the charging
trajectory in the SCA. A 3-D Y-mesh diagram was explored to
describe the trajectory of the charge behavior and was referred
to as the design reference. A prototype of the Li–ion charger was
examined with simulation and realization. The experimental results are very close to the theoretical prediction. The proposed
FC-ASCC, compared with the general CV mode, can improve
the charging performance about 23%.
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=
Guan-Chyun Hsieh (S’81–M’87–SM’95) was born
in Hua-Lien, Taiwan, R.O.C., in 1950. He received
the B.S. degree from National Taiwan Institute of
Technology, Taipei, Taiwan, R.O.C., the M.S. degree
from National Chiao-Tung University, Shinchu,
Taiwan, R.O.C., and the Ph.D. degree from National
Taiwan University, Taipei, Taiwan, R.O.C., in
1976, 1981, and 1986, respectively, all in electronic
engineering.
He is currently a Professor in the Department of
Electronic Engineering, National Taiwan University
of Science and Technology, Taipei, Taiwan, R.O.C., where he joined the faculty in 1981. He has engaged in research and teaching in the areas of power
electronics, electronic circuit design, control systems, and phase-locked servo
systems.
Dr. Hsieh received the 1993 Engineering Paper Award from the Chinese Institute of Engineers and the 1997 Best Joint Projects Award from the Ministry
of Education. He is a member of the Chinese Institute of Engineers and the Chinese Institute of Electrical Engineering.
Liang-Rui Chen was born in Changhua, Taiwan,
R.O.C., in 1971. He received the B.S. degree in
1994 and the M.S. degree in 1996, both in electronic
engineering, from National Taiwan University of
Science and Technology, Taipei, Taiwan, R.O.C.,
where he is currently working toward the Ph.D.
degree in the Department of Electronic Engineering.
Since 1999, he has been a Lecturer in the Department of Electronic Engineering, Chien Kuo Institute
of Technology, Changhua, Taiwan, R.O.C. His major
research interests are fuzzy control, phase/frequencylocked servo systems, battery chargers, and electronic circuit design.
Kuo-Shun Huang was born in Taipei, Taiwan,
R.O.C., in 1970. He received the B.S. degree in electrical engineering and the M.S. degree in automation
and control engineering from National Taiwan
University of Science and Technology, Taipei,
Taiwan, R.O.C., in 1997 and 1999, respectively.
Since 1999, he has been an R&D Engineer with
Sunplus Technology Company, Ltd., Hsinchu,
Taiwan, R.O.C. His major research interests are
intelligent control, battery chargers, and electronic
circuit design.