ArticlePDF Available

Optimized Operating Range for Large-Format LiFePO4/Graphite Batteries


Abstract and Figures

Long-term cycling performances of LiFePO4/graphite batteries have been investigated in different state-of-charge (SOC) ranges. It is found that batteries cycled in the medium SOC range exhibit superior cycling stability over those cycled at both ends of the SOC ranges. A variety of characterization techniques, including galvanostatic intermittent titration technique (GITT) analysis, model-based parameter identification, electrochemical impedance spectroscopy analysis, and entropy change test, were used to investigate the performance difference of the batteries cycled in different SOC ranges. The results reveal that batteries at the end of SOC exhibit much higher polarization impedance than those within the medium-SOC range. This result can be attributed to the significant structural change of the cathode and anode materials as revealed by the large entropy change within these SOC regions. Identification of the best operating conditions for LiFePO4/graphite batteries will significantly extend their cycle life. The general control principle obtained in this work, such as modulating the charge/discharge current to minimize the impedance extremes can also be used in the operation control of other battery systems.
Content may be subject to copyright.
A336 Journal of The Electrochemical Society,161 (3) A336-A341 (2014)
0013-4651/2014/161(3)/A336/6/$31.00 ©The Electrochemical Society
Optimized Operating Range for Large-Format LiFePO4/Graphite
Jiuchun Jiang,a,zWei Shi,a,b Jianming Zheng,bPengjian Zuo,bJie Xiao,b,Xilin Chen,b,∗∗
Wu Xu,b,and Ji-Guang Zhangb,z
aSchool of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
bEnergy & Environment Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
Long-term cycling performances of LiFePO4/graphite batteries have been investigated in different state-of-charge (SOC) ranges.
It is found that batteries cycled in the medium SOC range exhibit superior cycling stability over those cycled at both ends of
the SOC ranges. A variety of characterization techniques, including galvanostatic intermittent titration technique (GITT) analysis,
model-based parameter identification, electrochemical impedance spectroscopy analysis, and entropy change test, were used to
investigate the performance difference of the batteries cycled in different SOC ranges. The results reveal that batteries at the end
of SOC exhibit much higher polarization impedance than those within the medium-SOC range. This result can be attributed to the
significant structural change of the cathode and anode materials as revealed by the large entropy change within these SOC regions.
Identification of the best operating conditions for LiFePO4/graphite batteries will significantly extend their cycle life. The general
control principle obtained in this work, such as modulating the charge/discharge current to minimize the impedance extremes can
also be used in the operation control of other battery systems.
© 2013 The Electrochemical Society. [DOI: 10.1149/2.052403jes] All rights reserved.
Manuscript submitted September 20, 2013; revised manuscript received December 16, 2013. Published December 31, 2013.
The increasing concern over global warming and energy security
has stimulated great interest in developing electric vehicles (EV), in-
cluding pure EVs, plug-in hybrid vehicles, and hybrid EVs powered
by high-energy density rechargeable lithium-ion batteries (LIBs).14
Although various types of EVs using lithium ion batteries have been
marketed in the United States, Europe, Asia, and elsewhere in recent
years, mass market penetration of EVs still requires significant im-
provement in the energy density, reduction of cost, and enhancement
of cycle life of Li-ion batteries. Among the various Li-ion batter-
ies used in EVs, the battery based on LiFePO4/graphite chemistry
is very attractive because of its good safety characteristics and ex-
cellent cycle life. The long-term charge/discharge characteristics of
commercial LiFePO4/graphite batteries have been studied along with
applications of a battery management system in pure electric buses
during the Beijing Olympic Games and the Shanghai World Expo,
as well as in electric sanitation trucks in Beijing. To maximize the
charge/discharge performance and cycle life of batteries, it is criti-
cally important to develop a comprehensive method for understanding
the impact of actual operating conditions on battery cycle life. The
performance of LiFePO4-based batteries with olivine structures has
been studied extensively via approaches ranging from material studies
to modeling.59Correlations between capacity fading or power decay
and cell internal resistance as well as polarization impedance have
been investigated in many laboratories.1013
To maintain safe operation and long cycle life of batteries,
battery management systems play an important role. Temperature,
charge/discharge rate, and the state-of-charge (SOC) operating ranges
usually are considered to be the main factors that affect battery ag-
ing and degradation.14 Experience gained from EV use suggests that
different SOC ranges impact the battery cycle life to varying degrees,
and it is suspected that operating over a wide SOC range results in in-
creased capacity fade. Various equivalent circuit models (ECM) have
been used to simulate dynamic voltage and current, and to identify
the resistance and impedance of a battery system.1517 More precise
electrochemical models typically employ partial differential equations
with a number of unknown parameters, such as Li-ion concentration,
potential gradient in the electrolyte and the solid electrode material,
and other dynamic variables during battery operation.9,18 These pa-
rameters are useful for understanding the electrochemical reactions
between electrodes and the electrolyte, but are not desirable for use in
actual battery management systems. Moreover, the accuracy of these
models is still questionable. One source of error is that the ECM
Electrochemical Society Active Member.
∗∗Electrochemical Society Student Member.
parameters used in numerical fitting may vary with the SOC, temper-
ature, and state of health (SOH) of a battery, so the simulation results
are insufficient to reflect the practical operating conditions, especially
for a LiFePO4battery that exhibits a very flat voltage plateau.
Electrochemical impedance spectroscopy (EIS) analysis is an ef-
fective and non-destructive technique that can be used to obtain in-
formation about ion-transfer kinetics in an electrode and at the elec-
trode/electrolyte interface within different SOC ranges.1923 Perfor-
mance differences in different SOC ranges can be interpreted by com-
bining the universal parameters from the ECM and detailed parameters
from the EIS technique. In this work, a first-order ECM was used to
simulate the polarization voltage of the full cell, and then a second-
order ECM in combination with EIS parameters was used to deter-
mine the alternating current impedance of the battery under different
SOC regions. Various parameters such as ohmic resistance, polariza-
tion impedance, and electrode/electrolyte interface impedance were
identified and used to explain the battery degradation results when
cycled in different SOC ranges. The fundamental mechanisms respon-
sible for the different performances at different SOC ranges are also
Two types of LiFePO4/graphite batteries were investigated in this
work. Large format 20 Ah energy-type batteries supplied by ATL
(Amperex Technology Limited, China) were used for long-term cy-
cling and electrochemical impedance analysis. For entropy change
analysis, small coin cells consisting of LiFePO4cathode electrodes
and/or graphite anode electrodes disassembled from a 2 Ah cell man-
ufactured by A123 Systems were used. Electrochemical properties
of the batteries were measured galvanostatically in a voltage range
between 2.5 and 3.65 V on an Arbin-BTS2000 battery tester. The
batteries were tested in a thermostat chamber controlled at 25Cwith
a temperature fluctuation of ±0.1C. In the long-term cycle-life tests,
the batteries were cycled in four different SOC ranges, which are
0 to 25%, 25 to 50%, 50 to 75%, and 75 to 100%. The batteries
were charged/discharged for two hundred cycles at a C/2 charge rate
(1 C =20 A) and a 1 C discharge rate with a fixed capacity of 5 Ah,
followed by three full cycles. Then, the fixed capacity was readjusted
with the obtained full discharge capacity.
The galvanostatic intermittent titration technique (GITT) analysis
was conducted on the Arbin-BTS2000 battery tester at C/3 rate.24 The
cell was charged or discharged to a capacity corresponding to 5%
SOC (9 min) followed by a rest time interval of 30 min and the data-
logging interval was 1 s. This procedure was repeated in the voltage
) unless CC License in place (see abstract). address. Redistribution subject to ECS terms of use (see on 2015-02-20 to IP
Journal of The Electrochemical Society,161 (3) A336-A341 (2014) A337
window of 2.5 3.65 V with varying state of charge (SOC). The cell
resistance induced voltage drop or IR drop (U) was measured 1 s after
a current pulse was applied; the polarization voltage drop (Up)was
measured after 30 min of relaxation. EIS tests were carried out using an
electrochemical workstation (Zahner-Zennium) in a frequency range
from 1 kHz to 100 mHz with a perturbation current of 2 A. In the EIS
tests, rest time means the duration after charging or discharging to
the next 5% higher or lower SOC value. EIS spectra were tested with
different rest times to study the impact of rest time after the current
Entropy change, S, data were tested as a function of temperature
using an electrochemical thermodynamic measurement system (Vi-
aspace, ETMS-1000). To investigate the origin of the battery degra-
dation, the entropy changes of cathode, anode, and full cells were
measured and compared separately. Because the ETMS system can
only hold small cells, coin type cells consisting of a LiFePO4/Li half-
cell, a graphite/Li half-cell, and a LiFePO4/graphite full cell were pre-
pared. Ideally, the same electrode as those used in above-mentioned
electrochemical tests should be used for the entropy study. However,
it is very difficult to disassemble a 20 Ah cell due to safety con-
cern. As an alternative, LiFePO4cathode and graphite anode were
obtained from a disassembled 2 Ah cells manufactured by A123 Sys-
tems. The obtained electrodes were washed with dimethyl carbonate
(DMC) several times, punched into disks (ø =1.60 cm) and dried
completely under vacuum. CR2032 coin-type cells were assembled
with the electrodes as-prepared. Metallic lithium foil was used as the
counter electrode in the case of half-cells. Celgard K2045 polyethy-
lene (PE) membrane was used as the separator, and 1 M LiPF6dis-
solved in ethyl carbonate (EC) and dimethyl carbonate (DMC) (1:2
in volume) was used as the electrolyte. Samples were prepared in an
argon-filled glove box (MBraun Inc.). The temperature range used
during entropy measurements was 15 to 35C. Five continuous tem-
peratures with a temperature interval of 5C and a sustained time of
15 min were used to calculate the value of S. The voltage detection
resolution is 1 μV for entropy evaluation.
Results and Discussion
Cycling performance of high capacity cells at different SOC
ranges.— To identify the effects of operating SOC range on the long-
term cycling performance of LiFePO4/graphite batteries, cycle-life
tests were conducted with 20 Ah batteries at four different SOC ranges:
0 to 25%, 25 to 50%, 50 to 75%, and 75 to 100%. Two duplicate bat-
teries were tested in each SOC range for repeatability. To minimize
possible over-charge and decrease side reactions between the elec-
trodes and electrolyte, no constant voltage charge step was applied
during cycling. After every 200 cycles, three full charge/discharge
cycles were performed to obtain a retained reversible capacity and
thus readjust the capacity at each SOC range to be used in subsequent
cycles. The initial voltage profiles and the capacity retentions for bat-
teries cycled at the four SOC ranges are compared in Figure 1a and
1b, respectively. The results shown in Figure 1clearly indicate that
the battery cycled in SOC range of 75 to 100% exhibits the fastest
capacity degradation, followed by the battery cycled in the SOC range
of 0 to 25%. In comparison, batteries cycled in the mid-SOC ranges,
such as 25 to 50% and 50 to 75% SOC ranges, show superior cycling
performance with significantly reduced capacity fade, revealing that
the medium SOC range (25 to 75%) could be the preferred operating
range for the LiFePO4/graphite batteries.
To further verify the above results, cycling performance of
LiFePO4/graphite batteries (20 Ah cells from ATL) also were eval-
uated in other SOC ranges, including the mid-SOC range of 20 to
80%, both ends of SOC (0 to 20%, 80 to 100%), and full SOC range
(0 to 100%) at a charge/discharge rate of 1 C as shown in Figure 2.
The results clearly demonstrate that the battery cycled within the full
SOC range (0 to 100%) triggers an early termination at 80% of rated
capacity, followed by those cycled at two ends of SOC ranges (0 to
20% SOC or 80 to 100%). In contrast, the battery cycled in the mid-
SOC range of 20 to 80% (which used 60% of the rated capacity in
Figure 1. Performance of LiFePO4/graphite batteries cycled in various SOC
ranges: (a) voltage profiles (charged at C/2, discharged at 1 C rate); (b) capacity
retention as a function of cycle number.
each cycle) demonstrates significantly improved capacity retention,
as compared to those cycled in other SOC ranges. This result further
reveals the influence of the SOC range on the cycle life of the batteries
and confirms that cycle life of the batteries could be largely prolonged
if cycled within the medium SOC ranges.
Impedance of high capacity cells at different SOC ranges.— To
gain insight into the origin for the different cycling performance in
different SOC ranges, the evolution of battery resistance as a function
of SOC has been carefully investigated. GITT analysis was performed
to obtain the battery polarization during charge/discharge processes.
Figure 3a shows the open circuit voltage (OCV) of the battery as a
function of time or SOC (every current pulse represents a charge or
discharge capacity corresponding to 5% SOC). The cell resistance
induced voltage drop or IR drop (U) and the polarization voltage
drop (Up) are indicated in the inset of Figure 3a.
Figure 2. Effect of other SOC ranges (0 to 20%, 80 to 100%, and 0 to 100%)
on the cycling life of a 20 Ah LiFePO4/Graphite battery (charge/discharge at
1 C rate).
) unless CC License in place (see abstract). address. Redistribution subject to ECS terms of use (see on 2015-02-20 to IP
A338 Journal of The Electrochemical Society,161 (3) A336-A341 (2014)
Figure 3. (a) GITT curve as a function of time for LiFePO4/graphite cell. The current density and the amount of charge passed in a current pulse correspond to a
C/3 Rate and 5% SOC for the battery, respectively. (b) First-order RC equivalent circuit model. (c) Corresponding resistance Rand polarization impedance Rp
during charge/discharge processes.
The whole cell polarization (i.e., R, cell resistance; Rp, polariza-
tion impedance of whole cell, containing charge-transfer impedance
(Rp1) and diffusion impedance (Rp2); Cp, capacitance of interface)
in different SOC ranges was simulated with the first-order resis-
tance/capacitance (RC) model as shown in Figure 3b, which used a
RC circuit network to describe battery polarization and relaxation.12,25
The whole polarization voltage, UoUocv, can be obtained from the
equivalent circuit impedance Z, which is calculated using the follow-
ing relationship:
When the circuit has a current input, I,UoUocv can be expressed
by the inverse Laplace transformation as follows:
p(1 et
The internal resistances, R, and polarization impedances, Rp,at
different SOCs are calculated from the measured Uand Upvalues
shown in the inset of Figure 3a. The fitted results of Rand Rpare
plotted as a function of SOC in Figure 3c. The figure shows that the
cell resistance R, including contributions from the current collector,
electrolyte, and other cell parts, is very stable throughout the entire
SOC range. However, polarization impedances, Rp(=(UoUocv
U)/I), exhibits a bowl shape as shown in Figure 3c;thatis,Rp
becomes much higher at both the end of charge (EOC) or the end
of discharge (EOD) states than in the middle range of SOC (which
corresponds to the voltage plateau region of LiFePO4).
EIS analysis is another effective and non-destructive technique
that can be used to gain insight into the charge transfer kinetics in
the electrode and at the electrode/electrolyte interface at different
SOC ranges.1921 EIS spectra in the whole SOC ranges (5% SOC
interval) were recorded with different rest times and fitted with the
second-order RC/LRC model (Figure 4a)(L, wiring between elec-
trode paste and current collector;16 R, cell resistance; Rp1,charge-
transfer impedance; Cp1, capacitance of electrode surface layer; Rp2,
diffusion impedance; Cp2, capacitance of concentration polarization,
which occurs at certain SOCs and lower frequency ranges).17,26 Rp1
Figure 4. (a) Second-order RC/LRC Model, (b) curve fitting of the second-
order RC or LRC model via EIS test data measured at 50% SOC.
) unless CC License in place (see abstract). address. Redistribution subject to ECS terms of use (see on 2015-02-20 to IP
Journal of The Electrochemical Society,161 (3) A336-A341 (2014) A339
Figure 5. Impedance spectra at different SOC values: (a) EIS test at different rest times with various polarization states, (b) Rp1curve with 0 min, 10 min, and
60 min rest when charging, (c) Rp1curve with 0 min, 10 min, and 60 min rest when discharging, (d) EIS tests when charge with 10 min rest time /25C; (e) EIS
tests when discharge with 10 min rest time /25C, (f) Rp1curve with 10 min rest time.
is the impedance caused by electrode potential and surface electrode
processes, while Rp2 is the diffusion impedance mainly affected by
ionic concentrations. The second RC element is usually considered
as a Warburg impedance if the value of Rp2increases sharply at low
frequency,2729 although Rp1and Rp2are sometimes considered as a
united Rpduring EIS fitting process.15 Obviously, the second-order
ECM model, which includes information obtained from EIS mea-
surements, is more accurate than the first-order model (Figure 3b)in
estimating the battery internal resistance and polarization.
Because more precise charge-transfer impedance, Rp1, could be
identified from the second-order RC or LRC model, one can obtain
the diffusion impedance or Warburg impedance, Rp2, by subtracting
Rp1from the total Rpin the first-order RC model. By taking into
account the difference of the frequency response characteristics of an
actual battery and a “pure capacitor,” Cpis replaced by a constant
phase element, Q, which represents a certain degree of deviation
from capacitive characteristics. Impedance, ZQ, is represented by the
following equation:
Y·cos nπ
 =−
Y·sin nπ
where Yis a physical quantity used to describe the electric double-layer
and nis the strength of deviation. The closer the value of napproaches
1, the closer its characteristics approach those of an ideal capacitor.
Figure 4b shows fitting results of two kinds of second-order models
with and without inductance L, which shows that the second-order
model with Lprovides more accurate parameter analysis.30
Figure 5a compares EIS spectra collected with different rest times
for a fully charged battery.The figure shows that the battery impedance
increases with the increase of rest time. If the EIS spectra were not
tested in a full equilibrium state, a large hysteresis effect was ob-
served between charge and discharge at the same SOC. However, the
hysteresis effect varies with SOC, reflecting the ability of the Li-ion
transport rate and electronic conductivity at different SOCs. There-
fore, the model-based parameters also are affected by the polarization
state according to actual charge-discharge profiles, and different hys-
teresis characteristics with or without sufficient rest time could be
EIS spectra evolutions also were recorded with different rest times
to examine the effect of cell relaxation on the EIS spectra. The fitted
results of the charge-transfer impedance (Rp1) during charge/discharge
processes are summarized in Figure 5b5c, respectively. Obvious dif-
ferences of Rp1with different rest times can be clearly observed.
Although the Rp1increases with the increase of rest time (more
) unless CC License in place (see abstract). address. Redistribution subject to ECS terms of use (see on 2015-02-20 to IP
A340 Journal of The Electrochemical Society,161 (3) A336-A341 (2014)
equilibrated state), the evolution of charge-discharge polarization
impedance follows the same trend. Therefore, fitted results from EIS
spectra obtained with a 10-min rest time (Figure 5d,5e)isusedfor
further comparison, as shown in Figure 5f. At a low-SOC region, the
Rp1obtained during the charge process is higher than those obtained
during the discharge process, which becomes reverse at high SOC
region. Moreover, the differences between the values of Rp1curves
during the charge and discharge processes are broader near EOD and
EOC than in the mid-ranges of SOC as shown in Figure 2c,which
shows a significant polarization Rp. In this regard, the EIS technique
provides more accurate prediction of the favorable SOC range for
sustaining battery operation. A decreased power (i.e., current density
for charge or discharge) near the two ends of the SOC range will
significantly reduce possible structural deterioration, micro-cracking,
graphite exfoliation, lithium plating, and electrolyte decomposition in
these batteries.14
It is worth to note that the large polarization at the EOC (SOC
=100%) could result in poor rate performance of the LiFePO4/
graphite battery and increased capacity fading at lower SOC regions.
At the fully charged state, the electrochemical potential of the car-
bon anode may fall below the ELUMO of the carbonate electrolyte,
and the electrochemical potential of LiFePO4cathode approaches the
EHOMO of the carbonate electrolyte.31 This finding suggests that the
battery is not stable at the fully charged state (SOC =100%) when
side reactions between the electrolyte and the electrodes occur easily.
Evolution of the EIS spectra may indicate irreversible side reactions
at the EOC state, which is responsible for the fast capacity decay
of a battery cycled at higher SOC regions (75 to 100% SOC, see
Figure 1).
Curve fitting with both the first-order RC model and the EIS test
with the second-order LRC model significantly contributes to the
description of battery kinetic responses studied at various SOC ranges.
We made estimates of the ECM parameters to analyze the electrode
kinetic processes containing charge-transfer impedance and diffusion
impedance at each SOC point. The results discussed above illustrate
that drastic cell polarization and hysteresis occur at both ends of the
SOC range. This finding is well correlated with faster capacity fading
for batteries cycled at both ends of the SOC range. The principles
discussed above reveal the correlation between a deep polarization
state and poor cycling behavior, so a rational operating range should
be identified to expand the lifetime of the batteries.
Entropy changes and effect of SOC on the performance of small
LiFePO4/graphite cells.— Recently, entropy change has been used to
study the reversible heat generated by battery electrode material dur-
ing charge/discharge processes as well as the structural evolution of
electrode materials.32,33 Entropy changes will be significantly different
when positive and negative electrode materials with different crystal
structures are used in the battery. A large entropy change in some SOC
ranges is directly related to a large structural change/rearrangement.
Batteries cycled within these ranges may show faster capacity fade
than in other ranges during lithium ion insertion/de-insertion pro-
cesses. To compare the performance of the full battery and the entropy
changes of its components, coin type cells consisting of a LiFePO4/Li
half-cell, a graphite/Li half-cell, and a LiFePO4/graphite full cell were
prepared. The LiFePO4cathode and graphite anode were recovered
from a 2-Ah fresh commercial cell manufactured by A123 as described
in the experimental section. By comparing the half-cell and full-cell
capacities, the loading ratio of battery and Li-ion insertion/extraction
regions in both electrodes can be determined. As shown in Figure 6a,
the LPF cathode shows slightly higher capacity than that of graphite
anode (which may due to its specific design for high power oper-
ation). However, in the reassembled coin cell, the capacity of full
cell is lower than those of LFP cathode and graphite anode, indi-
cating that some graphite is still not fully charged during lithium
insertion process. Figure 6b shows the corresponding entropy change
curves for the Li/graphite half-cell, the Li/LiFePO4half-cell, and the
LiFePO4/graphite full cell. The LiFePO4cathode shows more en-
tropy change in the initial 10% and last 10% SOC regions than in
0 0.4 0.8 1.2 1.6 2 2.4 2.8
LFP halfcell
LFP fullcell
Graphite halfcell
0 0.4 0.8 1.2 1.6 2 2.4 2.8
LFP halfcell
LFP fullcell
Graphite halfcell
0 20 40 60 80 100 120 140 160 180 200
Cycle (n)
Capacity retention(%)
Figure 6. (a) Voltages profiles, (b) Scurves, (c) effect of SOC ranges on
the cycling performance of reassembled coin cells using electrodes (positive
electrode (LiFePO4), the negative electrode (graphite)) from A123 cells.
the mid-SOC ranges. Considering the fact that both the LiFePO4and
FePO4phases are very stable during charge/discharge processes, the
large entropy change in both ends of SOC regions can be ascribed
to the structural change or rearrangement during lithium insertion/de-
insertion process. On the other hand, the negative electrode exhibits
much more irregular entropy changes, which are attributed to the
multiple-phase changes of graphite at different Li+ion intercalation
stages, especially the phase transformation from Li0.5C6to LiC6.28,34
We need to notice that the contribution of the entropy change to
the cell operation depends on several other factors, especially on the
charge/discharge rate.33 In the high rate condition, the contribution of
the entropy change to the cell operation is relatively small. However,
in the low rate condition, the entropy change may make a significant
contribution to the battery operation.35
Cycling performance of LiFePO4/graphite coin cells (using re-
assembled electrodes taken from 2 Ah A123 cells) were evaluated
in SOC ranges of 0 to 30%, 35 to 65%, and 70 to 100% at a
charge/discharge rate of 1 C as shown in Figure 6c. During the for-
mation cycles, about 5% capacity loss is observed. The best capac-
ity retention appears with a battery cycled within the 35% to 65%
SOC range, which reveals that the method of dividing SOC range
by combining parameters from ECM and fitting parameters from EIS
technique is desirable and demonstrates the importance of the cycling
) unless CC License in place (see abstract). address. Redistribution subject to ECS terms of use (see on 2015-02-20 to IP
Journal of The Electrochemical Society,161 (3) A336-A341 (2014) A341
SOC range on the cycle life of the batteries. It is believed that this
methodology could also be widely applicable to predict the perfor-
mance of the batteries with different cell chemistries.
Long-term cycling performances of LiFePO4/graphite batteries
were investigated within different SOC ranges. The results show that
batteries cycled in the medium SOC range exhibit superior cycling
stability than those cycled at the two opposite ends of the SOC. A
variety of techniques, including GITT analysis, model-based param-
eter identification, and EIS spectra, reveal that batteries at both ends
of the SOC range exhibit much higher polarization impedance than
batteries cycled at the middle of the SOC range. These results can
be attributed to the significant side reactions that occur between elec-
trodes and electrolytes and the significant structural change of cathode
and anode materials at the ends of the SOC range. The general control
principle found in this work, such as modulating the charge/discharge
current to minimize the impedance extremes not only can improve
cycling performance of LiFePO4/graphite lithium ion batteries, but
also can be used in the operation control of other battery systems.
This work was supported by the National High Technology
Research and Development Program of China (Grant Numbers
2011AA05A108 and 2011AA11A246), the National Natural Science
Foundation of China (Grant Number 51277010), and by the Office
of Vehicle Technology of the U.S. Department of Energy through the
Batteries for Advanced Transportation Technologies Program.
1. J. Zheng, M. Gu, J. Xiao, P. Zuo, C. Wang, and J.-G. Zhang, Nano Lett.,13, 3824
2. J. Zheng, M. Gu, H. Chen, P. Meduri, M. H. Engelhard, J.-G. Zhang, J. Liu, and
J. Xiao, J. Mater. Chem. A,1, 8464 (2013).
3. H. Lin, J. Zheng, and Y. Yang, Mater. Chem. Phys.,119, 519 (2010).
4. J. Zheng, J. Xiao, Z. Nie, and J.-G. Zhang, J. Electrochem. Soc.,160, A1264 (2013).
5. A. K. Padhi, K. S. Nanjundaswamy, and J. B. Goodenough, J. Electrochem. Soc.,
144, 1188 (1997).
6. P. P. Prosini, M. Lisi, D. Zane, and M. Pasquali, Solid State Ionics,148, 45 (2002).
7. M. Takahashi, S. Tobishima, K. Takei, and Y. Sakurai, Solid State Ionics,148, 283
8. O. Toprakci, L. Ji, Z. Lin, H. A. K. Toprakci, and X. Zhang, J. Power Sources,196,
7692 (2011).
9. M. Safari and C. Delacourt, J. Electrochem. Soc.,158, A562 (2011).
10. T. Osaka, S. Nakade, M. Rajam¨
aki, and T. Momma, J. Power Sources,119–121, 929
11. M. Dubarry, B. Y. Liaw, M.-S. Chen, S.-S. Chyan, K.-C. Han, W.-T. Sie, and
S.-H. Wu, J. Power Sources,196, 3420 (2011).
12. B. Y. Liaw, R. G. Jungst, G. Nagasubramanian, H. L. Case, and D. H. Doughty, J.
Power Sources,140, 157 (2005).
13. M. Dubarry and B. Y. Liaw, J. Power Sources,194, 541 (2009).
14. J. Vetter, P. Nov´
ak,M. R.Wagner,C.Veit,K.C.M
oller, J. O. Besenhard, M. Winter,
M. Wohlfahrt-Mehrens, C. Vogler, and A. Hammouche, J. Power Sources,147, 269
15. M. Dubarry and B. Y. Liaw, J. Power Sources,174, 856 (2007).
16. T. Osaka, T.Momma, D. Mukoyama, and H. Nara, J. Power Sources,205, 483 (2012).
17. A. Eddahech, O. Briat, N. Bertrand, J.-Y. Deletage, and J.-M. Vinassa, International
Journal of Electrical Power & Energy Systems,42, 487 (2012).
18. N. A. Chaturvedi, R. Klein, J. Christensen, J. Ahmed, and A. Kojic, Ieee Control
Systems Magazine,30, 49 (2010).
19. D. Aurbach, J. Power Sources,89, 206 (2000).
20. D. Aurbach, B. Markovsky, G. Salitra, E. Markevich, Y. Talyossef, M. Koltypin,
L. Nazar, B. Ellis, and D. Kovacheva, J. Power Sources,165, 491 (2007).
21. J. M. Zheng, Z. R. Zhang, X. B. Wu,Z. X. Dong, Z. Zhu, and Y.Yang, J.Electrochem.
Soc.,155, A775 (2008).
22. J. Zheng, X. Wu, and Y. Yang, Electrochim. Acta,105, 200 (2013).
23. J. M. Zheng, X. B. Wu, and Y. Yang, Electrochim. Acta,56, 3071 (2011).
24. J. Zheng, W. Shi, M. Gu, J. Xiao, P. Zuo, C. Wang, and J.-G. Zhang, J. Electrochem.
Soc.,160, A2212 (2013).
25. M. A. Roscher, J. Assfalg, and O. S. Bohlen, Ieee Transactions on Vehicular Tech-
nology,60, 98 (2011).
26. J. Remmlinger, M. Buchholz, M. Meiler, P. Bernreuter, and K. Dietmayer, J. Power
Sources,196, 5357 (2011).
27. D. Andre, M. Meiler, K. Steiner, C. Wimmer, T. Soczka-Guth, and D. U. Sauer, J.
Power Sources,196, 5334 (2011).
28. D. Andre, M. Meiler, K. Steiner, H. Walz, T. Soczka-Guth, and D. U. Sauer, J. Power
Sources,196, 5349 (2011).
29. M. Ecker, J. B. Gerschler, J. Vogel, S. Kaebitz, F. Hust, P. Dechent, and D. U. Sauer,
J. Power Sources,215, 248 (2012).
30. Y. Zhang, C.-Y. Wang, and X. Tang, J. Power Sources,196, 1513 (2011).
31. J. B. Goodenough and Y. Kim, J. Power Sources,196, 6688 (2011).
32. C. Forgez, D. Vinh Do, G. Friedrich, M. Morcrette, and C. Delacourt, J. Power
Sources,195, 2961 (2010).
33. R. E. Williford, V. V. Viswanathan, and J. G. Zhang, J. Power Sources,189, 101
34. J. S. Filhol, C. Combelles, R. Yazami, and M. L. Doublet, J. Phys. Chem. C,112,
3982 (2008).
35. K. Jalkanen, T. Aho, and K. Vuorilehto, Journal of Power Sources,243, 354 (2013).
) unless CC License in place (see abstract). address. Redistribution subject to ECS terms of use (see on 2015-02-20 to IP
... FePO 4 , for example, undergoes a first-order phase transition from FePO 4 to LiFePO 4 , resulting in the coexistence of these two phases during lithiation. 10 Graphite, in contrast, forms a stable intermediate phase during a first-order phase transition, resulting in two separate two-phase coexistence regions including one between LiC 24 and LiC 12 and the other between LiC 12 and LiC 6 . 11 Over the past few decades, a number of analytical devices and techniques, including in situ X-ray diffraction (XRD), 12−15 ex situ electron microscopy, 16−18 electron energy-loss spectroscopy (EELS), 19 and Raman spectroscopy 20−22 have been developed to investigate changes in the crystal structure of battery electrode materials during cycling. ...
... 19,37,62 In fact, Figure 10a shows that both U ocv (x,T) and Similarly, Figure 10b shows U ocv (x,T) and ∂U ocv (x,T)/∂T for a battery system consisting of a FePO 4 working electrode and a lithium metal counter electrode in 1 M LiPF 6 in an EC/DMC electrolyte during lithiation. 10 Here also, electron energy-loss spectroscopy and in situ XRD measurements indicated a first order phase transition from FePO 4 to olivine LiFePO 4 during lithiation. 63−65 Figure 9b shows that both U ocv (x,T) and ∂U ocv (x,T)/∂T were constant for 0 ≤ x ≤ 1. ...
... (19) and (20). The lower operating SoC of the battery is considered as 20% based on this study [48] which states that the battery cycled at SoC range 20%-80% has lower degradation compared to operating beyond these limits. The upper operating limit for the battery is considered as 95% based on the charging curve of the battery. ...
Full-text available
Increasing environmental restrictions, create stringent regulations for the use and management of rivers and water bodies, thereby jeopardizing the operational flexibility of hydropower plants. The national plan for new environmental regulations in Sweden is expected to be implemented in 2025. Hence, it is imperative for the hydropower producers to consider alternatives which can overcome the environmental restrictions for providing flexibility. In this paper, a Mixed Integer Linear Programming (MILP) based algorithm for the short-term regulation of hydropower plants with energy storage is proposed. There are two stages of the algorithm: Future electricity market prices model using machine learning techniques, and the combined hydropower plant and battery system (CHBS)’s operation model using MILP. The designed algorithm is used to analyze the techno-economic feasibility of the operation of three hydropower plants Skattungbyn, Unnån and Hansjö, located in lower Oreälven river in Sweden. Three different electricity market scenarios were developed based on Swedish nuclear energy targets for 2040. The forecasted market prices act as inputs for the designed optimization algorithm. The algorithm optimizes the operation of hydropower plants with an objective to maximize revenue through harnessing flexibility enabled by storage. It is observed from the results that with the current battery costs (≈0.36 million €/MWh), the CHBS for short-term regulation is not profitable with NPV ranging from −1 to −4 million € and the cost of battery needs to be less than 50 000 €/MWh to make it economically feasible.
... Interestingly, smaller DOD and cycling at higher SOC leads to an increase of the capacity loss, which was already observed by other groups for LiFePO4 cells 200,201,206 . Cycling at higher SOC (>50% SOC) was therefore more detrimental than cycling over the whole SOC range (100 -0% SOC), this is valid for both ageing temperatures. ...
Full-text available
Degradation mechanisms in commercial Li-ion batteries have been extensively studied over the past decades. However, there are still open questions regarding the link between the observed changes on the system level of the battery with the actual degradation on the material level happening inside the battery. Therefore, different techniques are applied and findings combined to improve the understanding of material degradation influences on the system level behavior. A tailored electrochemical strain microscopy (t-ESM) technique, which is based on atomic force microscopy, is presented. The technique is applied to laboratory made silicon composite anodes and commercial LiFePO4 cathodes. The surface displacement induced by the Vegard strain is proportional to the ionic concentration change and activity of Li-ions within the probed volume under the tip. The probed volume spans only a few nanometers in depth inside the material. The results indicate a structural dependency, with higher mobility and activity at boundaries. The technique provides time constants and hence diffusion coefficients on the nano-scale. The electrochemical activity, which is analyzed with the t-ESM technique, is found to decrease due to ageing. The ageing of commercial battery cells is monitored using system level methods such as incremental capacity analysis (ICA), differential voltage analysis (DVA) and tracking of the open-circuit voltage (OCV). Ageing at 50% depth of discharge (DOD) leads to higher capacity fading compared to cycling over 100% of the available capacity. In total, 14 different features of the cell behavior are tracked during the ageing process using various analysis techniques. The intensity of the first discharge peak of the ICA curves is found to correlate well with the capacity fading and is used to predict the remaining capacity and lifetime. The loss of lithium and the loss of active material, especially at the cathode, are the main factors leading to the observed capacity decay. The post-mortem analysis reveals the formation of lithium fluoride crystals on the anode surfaces, aged at 55°C. The iron dissolution (from the electrode into the electrolyte) is shown to be temperature dependent and in addition dependent on the depth of discharge. Next to iron dissolution, vanadium dissolution (from the electrode into the electrolyte) from the cathode is observed. Micrometer sized agglomerates (consisting out of nano particles from cathode active material) are observed on the cathode surface, which decrease the surface conductivity, but does not directly correlate with the capacity fading. Ageing at -20°C leads to the formation of stable Li plating, which is subsequently observed at room temperature cycling.
... The degradation rate and lifetime of Li-ion batteries in different operating conditions has been examined and reported in various studies in the literature. Several cycle ageing studies have been reported for small (1.1-3 Ah) cylindrical lithium iron phosphate (LFP) cells [5][6][7][8][9][10], but only one study for large LFP pouch cells was found [11]. Additionally, in [12], Lewerenz et al. have examined the cycle ageing of 8 Ah cylindrical LFP cells in different operating conditions. ...
Full-text available
Incremental capacity analysis (ICA) is a widely used method for assessing Li-ion battery state of health (SOH). The ICA method is typically applied to low C-rate charging or discharging, which is seldom feasible in online SOH estimation in real applications. In this paper the applicability of the ICA method to higher C-rates is investigated with C/3, 1C and 2C charging data from cycle aged large format commercial LiFePO4/graphite cells, LiNiMnCoO2/graphite cells, and cells with Li2TiO3 anode. Alongside the ICA method, a less studied integrated voltage (IV) method is investigated with the same data set. The results show that both the ICA method and the IV method can be used for battery SOH estimation utilizing partial charging data. The results for the ICA method indicate an accuracy of 0.9–2.1% (RMSE) with C/3 charging for all studied cells, and corresponding accuracy also for some of the cell types studied with 1C and 2C charging currents. The accuracy of the IV method does not suffer from increasing charging current as heavily as the accuracy of the ICA method, and the SOH estimation error remains below 2.0% (RMSE) with all studied cell types up to 2C charging.
Charge storage reactions with multi-electron transfer represent an effective approach to obtaining higher energy density. V2O5 is a potential multi-electron reaction material, but suffers from the irreversible phase transformation and...
Solid-solid sulfur conversion reaction caused by cathode electrolyte interphase (CEI) can effectively prevent the dissolution of lithium polysulfides and theoretically improve the cycle stability of lithium-sulfur (Li–S) batteries. However, once the volume of reduction products (Li2S) exceeds the maximal volume of hosts, the as-formed CEI will be destroyed and significantly shorten the cycle life. In this study, we report a simple capacity control strategy to obtain a stable CEI which can greatly increase the total capacity contribution of Li–S batteries throughout the whole lifespan. By adjusting the discharging condition, Li–S cells achieve a prolonged cycle life over 950 cycles and a remarkable total capacity of 289 Ah g⁻¹ based on sulfur during the whole lifetime. Meanwhile, it is also found that the cycle life depends to a great extent on lithium anodes. This discharging strategy and understanding on the solid phase sulfur conversion under CEI mechanism can advance progress for the development of Li–S batteries.
This study proposes a fast yet accurate multiphysics model for a lithium‐ion battery (LIB) that estimates multiphysics responses under operational and abuse conditions. The proposed multiphysics model couples a novel electrochemical model and a thermodynamic‐chemical model. The electrochemical model modifies a conventional streamlined model by accounting for the state of charge dependency. The thermodynamic‐chemical model accounts for entropic, ohmic, and chemical reaction heating originating from thermal runaway, thereby replicating the chemical reaction of the main components in a LIB under abuse conditions. The proposed multiphysics model was calibrated through intensive experiments under operational and thermal abuse conditions. A comprehensive analysis revealed that the proposed model accurately estimated the electrochemical‐thermal characteristics of both cells, confirming the accuracy and robustness. Moreover, the proposed method is seven to eight times faster than a pseudo‐two‐dimensional model, implying that the proposed model is effective for elucidating multiphysics thermal runaway phenomena in a three‐dimensional LIB domain. Hence, the proposed model replicates thermal propagation inside a cell under electric abuse conditions. The versatility of the proposed fast yet accurate multiphysics model of LIBs was demonstrated with applications of an optimal cell design and a battery thermal management system. Framework of a verstile multiphysics model for thermal runaway estiamtion
Lithium-ion batteries (LIBs) based on olivine LiFePO4 (LFP) offer long cycle/calendar life and good safety, making them one of the dominant batteries in energy storage stations and electric vehicles, especially in China. Yet scientists have a weak understanding of LFP cathode degradation, which restricts the further development of LFP materials and batteries. Here, we critically review reports on LFP cathode degradation with respect to different electric parameters (including C-rates, storage, and long cycling), mechanical stresses, and thermal fields. The detailed chemical and physical aspects of degradation mechanisms at various scales (i.e., from atomic to devices) and their causes are comprehensively summarized, and discussions of related concerns are provided in each section. We close with a systematic overview of LFP degradation research and mediation strategies, suggesting future directions for developing robust, safe LFP batteries with long cycle life.
Full-text available
Lithium-rich, manganese-rich (LMR) layered composite cathode material Li[Li0.2Ni0.2Mn0.6]O2 synthesized by a co-precipitation method delivers a high discharge capacity of 281 mAh g−1 at a low current density of C/25. However, significant increase of cell polarization and decrease of discharge capacity are observed at voltage below 3.5 V with increasing current densities. Galvanostatic intermittent titration technique (GITT) analysis and electrochemical impedance spectroscopy (EIS) measurements demonstrate that lithium ion intercalation/de-intercalation reactions into/out of this material are kinetically controlled by Li2MnO3 component and its activated MnO2 component. The relationship between the electrochemical kinetics and rate performance as well as cycling stability has been systematically investigated. High discharge capacity of 149 mAh g−1 can be achieved at 10 C charge rate and C/10 discharge rate, indicating that the LMR cathode could withstand high charge rate (except initial activation process), which is very promising for practical applications. The results also reveal that the continuous formation of poorly conducting spinel phase is responsible for the capacity fading of LMR cathodes.
Full-text available
High voltage spinels LiNi0.5Mn1.5O4 (LNMO) with different contents of residual lattice Mn3+ have been evaluated in full cells using Li4Ti5O12 (LTO) as anode. Greatly improved cycling stability has been observed for all spinels in LTO-limited full cell, compared with those in LNMO-limited ones, while the underlying mechanisms are quite different. “Shallow cycling” of LNMO in LTO-limited cells does not require complete transition to the third cubic phase, reducing the phase boundaries that Li+ has to overcome and thus improving the cell performances. However, in LNMO-limited cells, influences of lattice Mn3+ are more easily exemplified in the Li+ deficient environment and superior electrochemical performance are observed for spinel with higher content of lattice Mn3+.
Full-text available
Li–S batteries are a complicated system with many challenges existing before their final market penetration. While most of the reported work for Li–S batteries is focused on the cathode design, we demonstrate in this work that the anode consumption accelerated by corrosive polysulfide solution also critically determines the Li–S cell performance. To validate this hypothesis, ionic liquid (IL) N-methyl-N-butylpyrrolidinium bis(trifluoromethylsulfonyl)imide (Py14TFSI) has been employed to modify the properties of the SEI layer formed on the Li metal surface in Li–S batteries. It is found that the IL-enhanced passivation film on the lithium anode surface exhibits very different morphology and chemical composition, effectively protecting lithium metal from continuous attack by soluble polysulfides. Therefore, both the cell impedance and the irreversible consumption of polysulfides on lithium metal are reduced. As a result, the Coulombic efficiency and the cycling stability of Li–S batteries have been greatly improved. After 120 cycles, the Li–S battery cycled in the electrolyte containing 75% IL demonstrates a high capacity retention of 94.3% at 0.1 C rate. These results reveal one of the main failure mechanisms in Li–S batteries and shine the light on new approaches to improve the reversible capacity and cyclability of Li–S batteries. This work provides important clues for the understanding and thus the improvement of Li–S battery systems through a different point of view.
Research into the monitoring of lithium-ion batteries has become increasingly important, due to their use in a variety of complex, high-performance, energy-storage applications in hybrid and electric vehicles (HEV and EV). This paper investigates the behavior and state-of-health monitoring of lithium-ion batteries. The first part presents a model for a high-energy-density lithium-ion cell dedicated to EV applications, based on Electrochemical Impedance Spectroscopy (EIS) measurements. The key characteristic of this model, based on an equivalent-circuit approach, is not only its simplicity, but also the fact it takes into account several important phenomena that occur inside lithium cells, such as the dependence of part of the internal resistance and the open-circuit voltage on the state of charge (SOC). The second part describes state-of-health (SOH) monitoring of a high-power-density lithium-ion cell, using recurrent neural networks (RNNs) to predict the deterioration in battery performance. This comprehensive approach was used to monitor several batteries dedicated to HEV and EV applications, covering the entire process, from behavior modeling to predicting performance degradation and use.
An isothermal model for the electrochemical behavior of a commercial graphite/LiFePO4 cell at 25 and 45 degrees C is developed. Although it does not embed any special feature of the porous electrodes and of the two-phase process of the LiFePO4 electrode, proper account of the experimental charge/discharge (from C/10 to 1C) and path-dependence effects of the commercial cell is achieved. The LiFePO4 electrode is treated based on a resistive-reactant concept with multiple particles whereas a single-particle approach is used to model the graphite electrode. In order to refine the model parameters for each electrode, half cells are made either from the recovered LiFePO4 or graphite electrodes vs. a Li counterelectrode. A detailed experiment/simulation analysis of half-cell and complete-cell data unfolds the impact of uniaxial pressure on the galvanostatic charge/discharge limitation and path dependence of the LiFePO4 electrode in the coin cell and the commercial cell.
The enthalpy and entropy changes in a commercial lithium-ion cell were studied by using potentiometric measurements. The experiments were done on the full cell and individually on its electrode materials, LiFePO4 and artificial graphite. The graphite electrode entropy change follows the amount of intercalated lithium, whereas the LFP electrode entropy change is independent of the lithium content. The full cell entropy change behavior can be concluded to originate from the graphite electrode. For the states of charge between 30 – 75 %, the full cell entropy change is positive in the discharge direction, causing the cell to absorb heat. Thus when low discharge currents are used, this entropy effect dominates over the irreversible, heat producing losses, and as a result the cell cools down. In the charge direction the entropy change has the same absolute value but is negative in sign. Because of this, the cell produces extra heat in addition to the irreversible heat production, and thus warms up. These phenomena were confirmed in a calorimetric experiment. The thermal behavior results can be utilized in designing the battery pack cooling system and in choosing favorable states of charge for the battery cycling.
Battery lifetime prognosis is a key requirement for successful market introduction of electric and hybrid vehicles. This work aims at the development of a lifetime prediction approach based on an aging model for lithium-ion batteries. A multivariable analysis of a detailed series of accelerated lifetime experiments representing typical operating conditions in hybrid electric vehicle is presented. The impact of temperature and state of charge on impedance rise and capacity loss is quantified. The investigations are based on a high-power NMC/graphite lithium-ion battery with good cycle lifetime. The resulting mathematical functions are physically motivated by the occurring aging effects and are used for the parameterization of a semi-empirical aging model. An impedance-based electric-thermal model is coupled to the aging model to simulate the dynamic interaction between aging of the battery and the thermal as well as electric behavior. Based on these models different drive cycles and management strategies can be analyzed with regard to their impact on lifetime. It is an important tool for vehicle designers and for the implementation of business models. A key contribution of the paper is the parameterization of the aging model by experimental data, while aging simulation in the literature usually lacks a robust empirical foundation.
To analyze impedance response of an electrochemical system, it is important to model the system with an adequate equivalent circuit. In the present work, an equivalent circuit was designed for the analysis of lithium ion batteries with the contributions of a variety of diffusion parameters resulting from the various particle sizes for the cathode and the solid-electrolyte interphase formed on the anode particles, as well as electrochemical reactions and inductive components. Residual errors resulting from the data fitting was investigated for a variety of equivalent circuits used. The electrochemical impedance of the electrodes in commercial lithium ion batteries at various states of charge was analyzed to evaluate the proposed circuit.
Strategies for Li-ion batteries that are based on lithium-insertion compounds as cathodes are limited by the capacities of the cathode materials and by the safe charging rates for Li transport across a passivating SEI layer on a carbon-based anode. With these strategies, it is difficult to meet the commercial constraints on Li-ion batteries for plug-in-hybrid and all-electric vehicles as well as those for stationary electrical energy storage (EES) in a grid.Existing alternative strategies include a gaseous O2 electrode in a Li/air battery and a solid sulfur (S8) cathode in a Li/S battery. We compare the projected energy densities and EES efficiencies of these cells with those of a third alternative, a Li/Fe(III)/Fe(II) cell containing a redox couple in an aqueous solution as the cathode. Preliminary measurements indicate proof of concept, but implementation of this strategy requires identification of a suitable Li+-ion electrolyte.