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Performance assessment and classification of retired lithium ion battery from electric vehicles for energy storage
i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y x x x ( 2 0 1 7 ) 1 e7
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Performance assessment and classification of retired lithium ion battery from electric vehicles for energy storage Qiangqiang Liao a,*, Miaomiao Mu a, Shuqi Zhao a, Lizhong Zhang a, Tao Jiang a, Jilei Ye b, Xiaowang Shen c, Guoding Zhou a a
Shanghai Key Laboratory of Materials Protection and Advanced Materials in Electric Power, Shanghai University of Electric Power, Shanghai 200090, China b Nanjing Branch of China Electric Power Research Institute, Nanjing 210003, China c State Grid Shanghai Municipal Electric Power Company, Shanghai 200122, China
article info
abstract
Article history:
The external and internal characteristics of retired lithium-ion batteries from electric ve-
Received 25 March 2017
hicles are evaluated using observational check, battery capacity measurement, pulse
Received in revised form
characteristic curve and electrochemical impedance spectroscopy. Non-parametric sta-
4 June 2017
tistical tests have been introduced to assess the correlation between battery capacity and
Accepted 6 June 2017
impedance. The results show that observational check and capacity measurement are only
Available online xxx
preliminary ways to screening and classification of retired batteries from electric vehicles. The voltage of pulse discharge is an important indicator for evaluating consistency among
Keywords:
retired batteries. Of all factors influencing on battery capacity loss from the point of view of
Retired lithium-ion battery
impedance, Warburg impedance is principal and charge transfer resistance is second.
Consistency
There is no correlation between capacity loss and ohmic resistance. Performance assess-
Pulse discharge
ments and consistency sectionalization of retired batteries need synthetic judgment by
Correlation
their different performance parameters. Of all 60 retired batteries investigated in this work,
Electrochemical impedance
20 batteries in good appearance are divided into three groups in the light of synthetic
spectroscopy
classifications of capacity, voltage of pulse discharge, charge transfer resistance and lithium ion diffusion coefficient while other 40 batteries disqualified in appearance are fundamentally taken no account of reuse. © 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Introduction Large-sized lithium-ion batteries have been introduced into energy storage for power system [1e3], and electric vehicles [4e6] et al. The accumulative installed capacity of electrochemical energy storage projects had reached 105.5 MW in China by the end of 2015, in third place preceded only by
United States and Japan [7]. Of all electrochemical energy storage projects in China, the quotient of lithium-ion batteries was maximal and achieved 66%. The sales of electric vehicles powered by lithium-ion batteries were 331092 units in China in 2015 and 3.4 times more than those in 2014. Lithium-ion batteries whose capacity decays to 70e80% after they are employed in electric vehicles for several years need to be replaced with new ones in order to ensure safety in operation
* Corresponding author. E-mail address: [email protected] (Q. Liao). http://dx.doi.org/10.1016/j.ijhydene.2017.06.043 0360-3199/© 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. Please cite this article in press as: Liao Q, et al., Performance assessment and classification of retired lithium ion battery from electric vehicles for energy storage, International Journal of Hydrogen Energy (2017), http://dx.doi.org/10.1016/j.ijhydene.2017.06.043
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and obligatory road haul of electric vehicles [8,9]. However, retired lithium-ion batteries still have certain residual capacity, which can be used for electric bicycles and excursion vehicles as power source, or energy storage in electricity grid [10]. Energy storage technologies such as battery energy storage attract more and more attention all over the world because the intermittence of blooming renewable energy generation will have negative impact on electricity grid security [11e13]. Generally, utility-scale energy storage has not been applied extensively because it remains exceptionally costly. Low cost of retired lithium-ion batteries brings an opportunity to their reuse for electricity storage [14,15]. However, lithium-ion batteries in electric vehicles are confronted with varied complex environments while they are in service on board, which bring about diverse decay of battery performance, thus aggravating inconsistency among batteries [8,16]. Therefore, it is necessary to assess and classify retired batteries from electric vehicles so as to exploit their residual capacity as much as possible on the premise of security. However, the significant inconsistency of retired lithium ion batteries is a key aporia of their reuse. It is a business of consuming time and energy in the light of actual capacity for consistency sectionalization. The establishment of rapid detection indexes significantly correlative to battery capacity will contribute to quick consistency sectionalization, thereby achieving the goal of inexpensive reuse of retired batteries. Retired lithium-ion batteries for reuse are becoming research hotspots along with blooming of electric vehicles. Ahmadi et al. [17,18] considered that the EV battery lost 20% of its capacity during its first use in the vehicle and a further 15% after its second use in the ESS over 10 years and retired batteries reuse in grid storage substituted format ural gas generation for peak regulation could double the benefits of greenhouse gas emissions reduction, which one was derived from the reduction of natural gas and the other came from clean electricity consumption of electric vehicles. Neubauer et al. [19] found that retired batteries still had the potential of cost-effective energy storage in spite of their second use would not lower significantly high cost of lithium ion batteries. Heymans et al. [15] also thought that retired batteries energy storage systems would better economic effectiveness and declined greenhouse gas emissions when household energy use increased. Zhou et al. [20] predicted cycle life of retired electric vehicle batteries and discovered that the relationship of capacity retention and cycle number agreed with Gaussian function. Schneider et al. [21,22] put forward a methodology to classify discarded NiMH and Li-Ion cells from mobile phones through disassembly, visual inspection, voltage verification and charge retention in the cycles and believed that nearly 40% NiMH cells and 45% Li-Ion cells assessed were available. Aziz et al. [23] gave theoretical and experimental evidence of the feasibility of a building energy management system consisting of a 20 kW photovoltaic (PV) panel, five electric vehicles and five retired batteries packs which each one has a capacity of 16 kWh. Tong et al. [24] configured a 15 serial 9 parallel retired battery pack with available capacity of 13.9 kWh in an off-grid PV vehicle charging system, using 135 retired lithium-ion batteries which had been selected in the light of residual capacity. In general, an energy storage system is situated in a stationary and indoor
environment and is not confronted with high charge or discharge rates, so it is feasible that retired lithium-ion batteries are used for grid storage. In this paper, retired batteries performance is characterized using observational check, battery capacity measurement, pulse characteristic curve and electrochemical impedance spectroscopy and then they are classified according to the consistency of characteristic parameters for the purpose of packing retired batteries safely and reliably.
Experimental The tested lithium ion phosphate batteries are a sum of 60 cells produced by Shanghai Aerospace Power Technology Co. Ltd, China, retired from electric vehicles. The nominal capacity of every battery is 15 A h and its nominal and maximal voltage values are 3.2 V and 3.7 V, respectively. A lot of their performance such as external appearance, capacity, voltage and internal resistance is characterized in order to ensure that they are worthy of reuse. Further, the reusable retired batteries are classified in the light of their characteristic consistency before battery packing. All measurements are at temperatures of ~20 C set by an air conditioner.
Observational check The external appearances of retired batteries are checked. Retired batteries under such situations as bulge, weeping and pocking are not reused but disassembled for recycling.
Determination of battery capacity Charge and discharge measurements at constant current are performed to determine battery capacity by Bitrode MCV 2200-5 instruments (USA) because capacities of retired batteries have declined in varying degrees after their use in electric vehicles for several years. According to the standard entitled “Technical specifications of performance test for smart grid energy storage batteries” (DB31/T817-2014, China) [25], the test procedure is described as follows. (1) The battery discharges with a constant current relative to 1/3 C-rate (5 A) until the voltage arrives at 2.7 V. (2) Rest for 1 h. (3) The battery charges with 1/3 C-rate current until the voltage reaches 3.65 V, then veers constant voltage charge until the charging current Icharge is reduced to 1/ 30 C-rate (0.5 A). (4) Rest for 1 h. (5) The battery discharges with 1/3 C-rate current (Idischarge) until the voltage gets to 2.7 V. (6) The capacity C (in Ah) is counted according to Formula (1) from a discharge test at constant current after a complete charge - discharge cycle. Z C¼
3600 Idischarge dt
(1)
Please cite this article in press as: Liao Q, et al., Performance assessment and classification of retired lithium ion battery from electric vehicles for energy storage, International Journal of Hydrogen Energy (2017), http://dx.doi.org/10.1016/j.ijhydene.2017.06.043
i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y x x x ( 2 0 1 7 ) 1 e7
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Experimentation of pulse discharge Pulse discharge/charge test is an effective method of evaluating the consistency among batteries because the discrepancy of internal resistance of cells will give rise to big voltage variation when high-rate current is exerted cells at several seconds [26]. Pulse discharge tests in the experiment are also implemented by Bitrode MCV 2-200-5 instruments and the procedure is as follows. (1) The battery charges with 1/3 C-rate current until the voltage reaches 3.65 V, then veers constant voltage charge until the charging current is reduced to 1/30 Crate. (2) Rest for 2 h. (3) Discharge at 1 C-rate (15 A) current for 10 s, then rest for 40 s. (4) Discharge at 3 C-rate (45 A) current for 10 s, then rest for 40 s. (5) Discharge at 5 C-rate (75 A) current for 10 s, then rest for 40 s. (6) Charge at 1 C-rate current for 10 s, then rest for 40 s. (7) Finally, repeat the step (1).
Experimentation of electrochemical impedance Electrochemical impedance spectroscopy (EIS) is measured at the open circuit voltage with an amplitude of 5 mV (AC) in the frequency range from 100 kHz to 10 mHz using a PGSTAT 302 electrochemical workstation (Autolab, Switzerland) after batteries rest for 1 h at 100% state of charge (SOC). Analysis of impedance data matching a suitable equivalent circuit yields different electrochemical parameters by ZSimpWin3.60 software (EChem Software, Michigan, USA), an EIS data analysis software that provides simple and versatile equivalent circuit model fitting.
Results and discussion
Fig. 1 e Examples of retired lithium ion batteries which are disqualified in appearance. 1. bulge; 2. weeping; 3. Pocking.
divided into 3 groups according to capacity class, which the first group contains 13 batteries named samples 1#, 2#, 3#, 4#, 8#, 9#, 10#, 12#, 15#, 16#, 17#, 19# and 20# in the range of 12e14 A h, the second includes 3 batteries named samples 5#, 7# and 14# in the reach of 10e12 A h, and the third is comprised of 4 batteries named samples 6#, 11#, 13# and 18# in the field of 8e10 A h. Meanwhile, the distribution characteristics of their capacities are studied using a piece of statistics software named Statistical Product and Service Solutions (SPSS) (IBM Corporation, New York, USA) [27] when all twenty batteries are considered as a whole. IBM SPSS Statistics is an integrated family of products that addresses the entire analytical process, from planning to data collection to analysis, reporting and deployment. The results show that the average capacity is 12.06 A h and their mean square deviation is 1.71. S-W test, one of non-parametric tests, is suitable for the sample size less than or equal to 2000 in SPSS software [28]. The capacities of these batteries will submit to normal distribution if their significance level is more than 0.05 [29]. The significance level derived from S-W test is 1.151, much
Observational check The inconsistency of retired batteries will be prominent owing to greatly different operating conditions of electric vehicles. Such appearance as deformation, bulge, breakage, weeping, pocking or damage of poles can reveal variation of physical and chemical properties, suggesting that such retired batteries would not be reused. Sixty retired batteries have been checked in appearance and forty of them are in bad appearance (examples in Fig. 1). Twenty of them in good appearance are marked samples 1e20#, respectively, in favor of subsequent description.
Capacity analyses Actual capacities of retired batteries need to be calibrated again because they decay in varying degrees while they are in service on board. Fig. 2 shows scatter diagrams of actual capacities of samples 1e20#. All twenty retired batteries are
Fig. 2 e Scatter diagrams of actual capacities of samples 1e20#.
Please cite this article in press as: Liao Q, et al., Performance assessment and classification of retired lithium ion battery from electric vehicles for energy storage, International Journal of Hydrogen Energy (2017), http://dx.doi.org/10.1016/j.ijhydene.2017.06.043
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more than 0.05, suggesting that the distribution of these 20 batteries' capacities is normal.
Analyses of pulse discharge curves Fig. 3 shows pulse discharging and charging voltage curves of partial retired batteries. The voltage variation of sample 4# is not obviously consistent with other samples during discharging at 3 or 5 C-rate current although samples 1#, 3#, 4#, 9#, 12# are ranked in the first group according to capacity class and their voltage variations are approximately consistent during discharging or charging at 1 C-rate current. Moreover, the bigger the discharge rate, the more inconsistent the voltage variation. Table 1 displays voltage of retired batteries at different charging and discharging rates, which is picked up at the pulse time of 5 s. Seen from Table 1, the maximal voltage variations among these 20 batteries are 0.191 V and 0.079 V during discharging and charging at 1 C-rate current, respectively, while the maximal voltage variations are 0.410 V and 0.505 V during discharging at 3 and 5 C-rate current, respectively. The inconsistency among retired batteries will be prominent at pulse current of high rate as a result of their difference of polarization resistance. All twenty retired batteries are divided into 3 groups in the light of voltage at the pulse time of 5 s during 5 C-rate discharge. The first rank whose voltage is more than 2.7 V contains samples 1#, 2#, 3#, 5#, 7#, 8#, 9#, 11#, 12#, 13#, 14#, 16#, 18# and 19#. The second rank whose voltage is between 2.7 V and 2.5 V includes samples 4#, 6#, 10#, 15# and 17#. And the third rank whose voltage is smaller than 2.5 V is comprised of sample 20#.
Electrochemical impedance study The impedance model is a good way to describe the electrical behavior of batteries, which can be divided into different parts such as charge transfer, inductance and diffusion. Electrochemical impedance spectra of 20 batteries are measured at 100% SOC in order to investigate the consistence of retired batteries from the point of view of inner resistance.
Electrochemical impedance spectra of partial retired batteries are presented in Fig. 4. Electrochemical impedance spectra of 7#, 12#, 13#, 14# and 18# have big discrepancy, especially diffusion sections in low frequency region although they are divided into one group in the experiment of pulse discharge. For each curve of electrochemical impedance spectra, the approximate straight line portion in the fourth quadrant is the manifestation of inductive resistance L, which gives rise to the lagging of current behind voltage. Corresponding to Zim value at 0 mU in high frequency region, Zre value at real axis is ohmic resistance Rs. An obvious capacitive loop in intermediate frequency region is attributed to charge transfer resistance Rct whose value is approximately equal to the diameter of the capacitive loop and double-layer capacitance QCdl at the electrode/electrolyte interface [31]. An oblique line at low frequency range reflects the existence of Warburg impedance ZW [31], related to the diffusion process of lithium-ion inside active material particles. It is more reasonable that constant phase element QZw replaces ZW because the slope of the oblique line is not 45 . Therefore, an equivalent circuit model in Fig. 5 is proposed and different electrochemical parameters are derived by ZSimpWin 3.60 software. Resolved Rs and Rct values of all 20 batteries with their capacities are plotted in Fig. 6. The classification of batteries is judged if both Rs and Rct values are smaller than 7 mU, or one of them is between 7 and 10 mU, or bigger than 10 mU. Batteries whose Rs and Rct values are both smaller than 7 mU involve samples 1#, 2#, 4#, 7#, 8#, 9#, 10#, 11#, 12#, 13#, 14#, 15#, 16#, 17#, 19# and 20#. Rct values of samples 3#, 6# and 18# are between 7 and 10 mU and that of sample 5# is more than 10 mU. Concentration polarization impedance is a more important factor influencing on capacity loss of battery than ohmic resistance and charge transfer resistance. Lithium-ion diffusion coefficient DLiþ has a corresponding relation to concentration polarization impedance. The smaller DLiþ, the bigger the concentration polarization. DLiþ is counted by Formula (2) [32]: DLiþ ¼
R2 T2 ; 2A2 n4 F4 C2 s2
(2)
where ideal gas constant R is 8.314 J mol1 K1, absolute temperature T is 298.15 K, the number of electron transfer n is 1, Faraday constant F is 96487 C mol1, the cross-sectional area of electrodes is 0.01 m2, the concentration of lithiumion C is 7.69 103 mol m3 [33], and s is Warburg factor. s has a certain relationship with Zre in Formula (3): Zre ¼ RS þ Rct þ su0:5 ;
Fig. 3 e Pulse discharging and charging voltage curves of partial retired batteries.
(3)
where u is angular frequency, Zre is the real part of impedance spectroscopy corresponding to u, Rs is ohmic resistance and Rct is charge transfer resistance. According to Formula (3), Warburg factor s is the slope of the line when abscissa is u0.5 and ordinate is Zre. Then lithium-ion diffusion coefficient DLiþ can be calculated when s is substituted into Formula (2). Fig. 7 shows the relationships of all 20 batteries between their capacities and diffusion coefficients DLiþ, demonstrating that both of them have positive correlation. Samples 1#, 2#, 3#, 4#, 5#, 7#, 8#, 9#, 10#, 11#, 12#, 14#, 15#, 16#, 17#, 19# and 20# are in
Please cite this article in press as: Liao Q, et al., Performance assessment and classification of retired lithium ion battery from electric vehicles for energy storage, International Journal of Hydrogen Energy (2017), http://dx.doi.org/10.1016/j.ijhydene.2017.06.043
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Table 1 e Voltages of retired batteries at different charging and discharging rates (Unit: V). Sample Discharge 1C Discharge 3C Discharge 5C Charge 1C Sample Discharge 1C Discharge 3C Discharge 5C Charge 1C 1# 2# 3# 4# 5# 6# 7# 8# 9# 10#
3.264 3.260 3.263 3.241 3.254 3.205 3.241 3.262 3.263 3.080
3.055 3.042 3.054 2.955 3.025 2.922 2.956 3.037 3.045 2.747
2.865 2.847 2.865 2.659 2.812 2.657 2.705 2.839 2.847 2.525
3.418 3.443 3.412 3.439 3.421 3.456 3.440 3.424 3.419 3.473
Fig. 4 e Electrochemical impedance spectra of partial retired batteries.
11# 12# 13# 14# 15# 16# 17# 18# 19# 20#
3.259 3.250 3.237 3.264 3.198 3.271 3.197 3.239 3.271 3.108
3.036 3.007 2.993 3.021 2.888 3.065 2.879 2.991 3.076 2.666
2.824 2.837 2.770 2.802 2.606 2.878 2.596 2.758 2.898 2.393
3.422 3.436 3.433 3.434 3.471 3.416 3.468 3.430 3.408 3.487
Fig. 6 e Scatter diagrams of capacities and Rs, Rct of retired batteries.
Fig. 5 e An equivalent circuit model for the electrochemical impedance spectra of retired batteries.
the same rank and samples 6#, 13# and 18# are in another rank if the consistency of retired batteries is judged in the light of DLiþ values more or less than 6 1014 cm2 s1. S-W tests of ohmic resistance Rs, charge transfer resistance Rct and diffusion coefficients DLiþ are performed to assess if these data follow normal distribution, respectively. Then the correlation between capacity and one of them are analyzed, respectively. The results show that the significance levels of Rs, Rct and DLiþ are 0.862, 0.186 and 0.834, respectively, much more than 0.05, suggesting that the distributions of Rs, Rct and DLiþ of these 20 batteries are normal. Pearson's correlation coefficient can weigh degree of correlation between them if two data sets obey normal distribution [34]. Correlation degrees of capacity and one of them (Rs, Rct and DLiþ) are weighed
Fig. 7 e The relationship between the capacities and the diffusion coefficients DLiþ of retired batteries.
by Pearson's correlation coefficient because the distributions of these 20 batteries' capacities, Rs, Rct and DLiþ are normal. Significant correlation is set at the 0.05 level. Two data sets are correlative if their significance level is less than 0.05; if not, they are disrelated. The results display that Pearson's correlation coefficient between capacity and Rs is 0.364, but their significance level is 0.114, more than 0.05, suggesting that the
Please cite this article in press as: Liao Q, et al., Performance assessment and classification of retired lithium ion battery from electric vehicles for energy storage, International Journal of Hydrogen Energy (2017), http://dx.doi.org/10.1016/j.ijhydene.2017.06.043
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relationship between capacity loss and Rs is not correlative. Pearson's correlation coefficient between capacity and Rct is 0.538 and their significance level is 0.014, less than 0.05, indicating that the relationship between capacity and Rct is moderately negative correlation. Pearson's correlation coefficient between capacity and DLiþ is 0.729 and their significance level is 0.000, less than 0.05, revealing that the relationship between capacity and DLiþ is significantly positive correlation, just like the illustration in Fig. 7. Because capacity is not a correlate of Rs, these 20 batteries are divided into three groups in the light of comprehensive judgment of capacity, voltage of pulse discharge, charge transfer resistance and diffusion coefficient. The first group includes samples 1#, 2#, 8#, 9#, 12#, 16# and 19# whose capacities are between 12 and 14 A h, voltage of pulse discharge is more than 2.7 V, charge transfer resistance is less than 7 mU and diffusion coefficient is bigger than 6 1014 cm2 s1. The second group involves samples 3#, 4#, 7#, 10#, 14#, 15#, and 17# whose capacities are between 10 and 14 A h, voltage of pulse discharge is more than 2.5 V, charge transfer resistance is less than 10 mU and diffusion coefficient is bigger than 6 1014 cm2 s1. The third group contains samples 5#, 6#, 11#, 13#, 18# and 20#. The samples in the third group have either small capacities, or low voltages of pulse discharge, or big charge transfer resistance, or small diffusion coefficient, showing more inconsistency. The batteries in the first or second group can be packed and reused for energy storage, respectively, but the charge and discharge regime of energy storage system must be set in consideration of the battery of the worst performance in one group. It is recommended that the batteries in the third group not be reused for their inconsistency.
Conclusions (1) Observational check and capacity measurement are only preliminary ways to screening and classification of retired batteries from electric vehicles. (2) The voltage of pulse discharge is an important indicator for evaluating consistency among retired batteries. (3) Of all factors influencing on battery capacity from the point of view of impedance, Warburg impedance is principal and charge transfer resistance is second. There is no correlation between capacity and ohmic resistance. (4) Performance assessments and consistency sectionalization of retired batteries need synthetic judgment by their different performance parameters.
Acknowledgements The work was sponsored by Natural Science Foundation of Shanghai (17ZR1411200), Alliance Plan of Shanghai Municipal Promotion Association for Transformation of Scientific and Technological Achievements (LM201658) and Social Science Programs of the Education Ministry (16YJAZH035), China.
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Please cite this article in press as: Liao Q, et al., Performance assessment and classification of retired lithium ion battery from electric vehicles for energy storage, International Journal of Hydrogen Energy (2017), http://dx.doi.org/10.1016/j.ijhydene.2017.06.043
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ScienceDirect journal homepage: www.elsevier.com/locate/he
Performance assessment and classification of retired lithium ion battery from electric vehicles for energy storage Qiangqiang Liao a,*, Miaomiao Mu a, Shuqi Zhao a, Lizhong Zhang a, Tao Jiang a, Jilei Ye b, Xiaowang Shen c, Guoding Zhou a a
Shanghai Key Laboratory of Materials Protection and Advanced Materials in Electric Power, Shanghai University of Electric Power, Shanghai 200090, China b Nanjing Branch of China Electric Power Research Institute, Nanjing 210003, China c State Grid Shanghai Municipal Electric Power Company, Shanghai 200122, China
article info
abstract
Article history:
The external and internal characteristics of retired lithium-ion batteries from electric ve-
Received 25 March 2017
hicles are evaluated using observational check, battery capacity measurement, pulse
Received in revised form
characteristic curve and electrochemical impedance spectroscopy. Non-parametric sta-
4 June 2017
tistical tests have been introduced to assess the correlation between battery capacity and
Accepted 6 June 2017
impedance. The results show that observational check and capacity measurement are only
Available online xxx
preliminary ways to screening and classification of retired batteries from electric vehicles. The voltage of pulse discharge is an important indicator for evaluating consistency among
Keywords:
retired batteries. Of all factors influencing on battery capacity loss from the point of view of
Retired lithium-ion battery
impedance, Warburg impedance is principal and charge transfer resistance is second.
Consistency
There is no correlation between capacity loss and ohmic resistance. Performance assess-
Pulse discharge
ments and consistency sectionalization of retired batteries need synthetic judgment by
Correlation
their different performance parameters. Of all 60 retired batteries investigated in this work,
Electrochemical impedance
20 batteries in good appearance are divided into three groups in the light of synthetic
spectroscopy
classifications of capacity, voltage of pulse discharge, charge transfer resistance and lithium ion diffusion coefficient while other 40 batteries disqualified in appearance are fundamentally taken no account of reuse. © 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Introduction Large-sized lithium-ion batteries have been introduced into energy storage for power system [1e3], and electric vehicles [4e6] et al. The accumulative installed capacity of electrochemical energy storage projects had reached 105.5 MW in China by the end of 2015, in third place preceded only by
United States and Japan [7]. Of all electrochemical energy storage projects in China, the quotient of lithium-ion batteries was maximal and achieved 66%. The sales of electric vehicles powered by lithium-ion batteries were 331092 units in China in 2015 and 3.4 times more than those in 2014. Lithium-ion batteries whose capacity decays to 70e80% after they are employed in electric vehicles for several years need to be replaced with new ones in order to ensure safety in operation
* Corresponding author. E-mail address: [email protected] (Q. Liao). http://dx.doi.org/10.1016/j.ijhydene.2017.06.043 0360-3199/© 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. Please cite this article in press as: Liao Q, et al., Performance assessment and classification of retired lithium ion battery from electric vehicles for energy storage, International Journal of Hydrogen Energy (2017), http://dx.doi.org/10.1016/j.ijhydene.2017.06.043
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and obligatory road haul of electric vehicles [8,9]. However, retired lithium-ion batteries still have certain residual capacity, which can be used for electric bicycles and excursion vehicles as power source, or energy storage in electricity grid [10]. Energy storage technologies such as battery energy storage attract more and more attention all over the world because the intermittence of blooming renewable energy generation will have negative impact on electricity grid security [11e13]. Generally, utility-scale energy storage has not been applied extensively because it remains exceptionally costly. Low cost of retired lithium-ion batteries brings an opportunity to their reuse for electricity storage [14,15]. However, lithium-ion batteries in electric vehicles are confronted with varied complex environments while they are in service on board, which bring about diverse decay of battery performance, thus aggravating inconsistency among batteries [8,16]. Therefore, it is necessary to assess and classify retired batteries from electric vehicles so as to exploit their residual capacity as much as possible on the premise of security. However, the significant inconsistency of retired lithium ion batteries is a key aporia of their reuse. It is a business of consuming time and energy in the light of actual capacity for consistency sectionalization. The establishment of rapid detection indexes significantly correlative to battery capacity will contribute to quick consistency sectionalization, thereby achieving the goal of inexpensive reuse of retired batteries. Retired lithium-ion batteries for reuse are becoming research hotspots along with blooming of electric vehicles. Ahmadi et al. [17,18] considered that the EV battery lost 20% of its capacity during its first use in the vehicle and a further 15% after its second use in the ESS over 10 years and retired batteries reuse in grid storage substituted format ural gas generation for peak regulation could double the benefits of greenhouse gas emissions reduction, which one was derived from the reduction of natural gas and the other came from clean electricity consumption of electric vehicles. Neubauer et al. [19] found that retired batteries still had the potential of cost-effective energy storage in spite of their second use would not lower significantly high cost of lithium ion batteries. Heymans et al. [15] also thought that retired batteries energy storage systems would better economic effectiveness and declined greenhouse gas emissions when household energy use increased. Zhou et al. [20] predicted cycle life of retired electric vehicle batteries and discovered that the relationship of capacity retention and cycle number agreed with Gaussian function. Schneider et al. [21,22] put forward a methodology to classify discarded NiMH and Li-Ion cells from mobile phones through disassembly, visual inspection, voltage verification and charge retention in the cycles and believed that nearly 40% NiMH cells and 45% Li-Ion cells assessed were available. Aziz et al. [23] gave theoretical and experimental evidence of the feasibility of a building energy management system consisting of a 20 kW photovoltaic (PV) panel, five electric vehicles and five retired batteries packs which each one has a capacity of 16 kWh. Tong et al. [24] configured a 15 serial 9 parallel retired battery pack with available capacity of 13.9 kWh in an off-grid PV vehicle charging system, using 135 retired lithium-ion batteries which had been selected in the light of residual capacity. In general, an energy storage system is situated in a stationary and indoor
environment and is not confronted with high charge or discharge rates, so it is feasible that retired lithium-ion batteries are used for grid storage. In this paper, retired batteries performance is characterized using observational check, battery capacity measurement, pulse characteristic curve and electrochemical impedance spectroscopy and then they are classified according to the consistency of characteristic parameters for the purpose of packing retired batteries safely and reliably.
Experimental The tested lithium ion phosphate batteries are a sum of 60 cells produced by Shanghai Aerospace Power Technology Co. Ltd, China, retired from electric vehicles. The nominal capacity of every battery is 15 A h and its nominal and maximal voltage values are 3.2 V and 3.7 V, respectively. A lot of their performance such as external appearance, capacity, voltage and internal resistance is characterized in order to ensure that they are worthy of reuse. Further, the reusable retired batteries are classified in the light of their characteristic consistency before battery packing. All measurements are at temperatures of ~20 C set by an air conditioner.
Observational check The external appearances of retired batteries are checked. Retired batteries under such situations as bulge, weeping and pocking are not reused but disassembled for recycling.
Determination of battery capacity Charge and discharge measurements at constant current are performed to determine battery capacity by Bitrode MCV 2200-5 instruments (USA) because capacities of retired batteries have declined in varying degrees after their use in electric vehicles for several years. According to the standard entitled “Technical specifications of performance test for smart grid energy storage batteries” (DB31/T817-2014, China) [25], the test procedure is described as follows. (1) The battery discharges with a constant current relative to 1/3 C-rate (5 A) until the voltage arrives at 2.7 V. (2) Rest for 1 h. (3) The battery charges with 1/3 C-rate current until the voltage reaches 3.65 V, then veers constant voltage charge until the charging current Icharge is reduced to 1/ 30 C-rate (0.5 A). (4) Rest for 1 h. (5) The battery discharges with 1/3 C-rate current (Idischarge) until the voltage gets to 2.7 V. (6) The capacity C (in Ah) is counted according to Formula (1) from a discharge test at constant current after a complete charge - discharge cycle. Z C¼
3600 Idischarge dt
(1)
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Experimentation of pulse discharge Pulse discharge/charge test is an effective method of evaluating the consistency among batteries because the discrepancy of internal resistance of cells will give rise to big voltage variation when high-rate current is exerted cells at several seconds [26]. Pulse discharge tests in the experiment are also implemented by Bitrode MCV 2-200-5 instruments and the procedure is as follows. (1) The battery charges with 1/3 C-rate current until the voltage reaches 3.65 V, then veers constant voltage charge until the charging current is reduced to 1/30 Crate. (2) Rest for 2 h. (3) Discharge at 1 C-rate (15 A) current for 10 s, then rest for 40 s. (4) Discharge at 3 C-rate (45 A) current for 10 s, then rest for 40 s. (5) Discharge at 5 C-rate (75 A) current for 10 s, then rest for 40 s. (6) Charge at 1 C-rate current for 10 s, then rest for 40 s. (7) Finally, repeat the step (1).
Experimentation of electrochemical impedance Electrochemical impedance spectroscopy (EIS) is measured at the open circuit voltage with an amplitude of 5 mV (AC) in the frequency range from 100 kHz to 10 mHz using a PGSTAT 302 electrochemical workstation (Autolab, Switzerland) after batteries rest for 1 h at 100% state of charge (SOC). Analysis of impedance data matching a suitable equivalent circuit yields different electrochemical parameters by ZSimpWin3.60 software (EChem Software, Michigan, USA), an EIS data analysis software that provides simple and versatile equivalent circuit model fitting.
Results and discussion
Fig. 1 e Examples of retired lithium ion batteries which are disqualified in appearance. 1. bulge; 2. weeping; 3. Pocking.
divided into 3 groups according to capacity class, which the first group contains 13 batteries named samples 1#, 2#, 3#, 4#, 8#, 9#, 10#, 12#, 15#, 16#, 17#, 19# and 20# in the range of 12e14 A h, the second includes 3 batteries named samples 5#, 7# and 14# in the reach of 10e12 A h, and the third is comprised of 4 batteries named samples 6#, 11#, 13# and 18# in the field of 8e10 A h. Meanwhile, the distribution characteristics of their capacities are studied using a piece of statistics software named Statistical Product and Service Solutions (SPSS) (IBM Corporation, New York, USA) [27] when all twenty batteries are considered as a whole. IBM SPSS Statistics is an integrated family of products that addresses the entire analytical process, from planning to data collection to analysis, reporting and deployment. The results show that the average capacity is 12.06 A h and their mean square deviation is 1.71. S-W test, one of non-parametric tests, is suitable for the sample size less than or equal to 2000 in SPSS software [28]. The capacities of these batteries will submit to normal distribution if their significance level is more than 0.05 [29]. The significance level derived from S-W test is 1.151, much
Observational check The inconsistency of retired batteries will be prominent owing to greatly different operating conditions of electric vehicles. Such appearance as deformation, bulge, breakage, weeping, pocking or damage of poles can reveal variation of physical and chemical properties, suggesting that such retired batteries would not be reused. Sixty retired batteries have been checked in appearance and forty of them are in bad appearance (examples in Fig. 1). Twenty of them in good appearance are marked samples 1e20#, respectively, in favor of subsequent description.
Capacity analyses Actual capacities of retired batteries need to be calibrated again because they decay in varying degrees while they are in service on board. Fig. 2 shows scatter diagrams of actual capacities of samples 1e20#. All twenty retired batteries are
Fig. 2 e Scatter diagrams of actual capacities of samples 1e20#.
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more than 0.05, suggesting that the distribution of these 20 batteries' capacities is normal.
Analyses of pulse discharge curves Fig. 3 shows pulse discharging and charging voltage curves of partial retired batteries. The voltage variation of sample 4# is not obviously consistent with other samples during discharging at 3 or 5 C-rate current although samples 1#, 3#, 4#, 9#, 12# are ranked in the first group according to capacity class and their voltage variations are approximately consistent during discharging or charging at 1 C-rate current. Moreover, the bigger the discharge rate, the more inconsistent the voltage variation. Table 1 displays voltage of retired batteries at different charging and discharging rates, which is picked up at the pulse time of 5 s. Seen from Table 1, the maximal voltage variations among these 20 batteries are 0.191 V and 0.079 V during discharging and charging at 1 C-rate current, respectively, while the maximal voltage variations are 0.410 V and 0.505 V during discharging at 3 and 5 C-rate current, respectively. The inconsistency among retired batteries will be prominent at pulse current of high rate as a result of their difference of polarization resistance. All twenty retired batteries are divided into 3 groups in the light of voltage at the pulse time of 5 s during 5 C-rate discharge. The first rank whose voltage is more than 2.7 V contains samples 1#, 2#, 3#, 5#, 7#, 8#, 9#, 11#, 12#, 13#, 14#, 16#, 18# and 19#. The second rank whose voltage is between 2.7 V and 2.5 V includes samples 4#, 6#, 10#, 15# and 17#. And the third rank whose voltage is smaller than 2.5 V is comprised of sample 20#.
Electrochemical impedance study The impedance model is a good way to describe the electrical behavior of batteries, which can be divided into different parts such as charge transfer, inductance and diffusion. Electrochemical impedance spectra of 20 batteries are measured at 100% SOC in order to investigate the consistence of retired batteries from the point of view of inner resistance.
Electrochemical impedance spectra of partial retired batteries are presented in Fig. 4. Electrochemical impedance spectra of 7#, 12#, 13#, 14# and 18# have big discrepancy, especially diffusion sections in low frequency region although they are divided into one group in the experiment of pulse discharge. For each curve of electrochemical impedance spectra, the approximate straight line portion in the fourth quadrant is the manifestation of inductive resistance L, which gives rise to the lagging of current behind voltage. Corresponding to Zim value at 0 mU in high frequency region, Zre value at real axis is ohmic resistance Rs. An obvious capacitive loop in intermediate frequency region is attributed to charge transfer resistance Rct whose value is approximately equal to the diameter of the capacitive loop and double-layer capacitance QCdl at the electrode/electrolyte interface [31]. An oblique line at low frequency range reflects the existence of Warburg impedance ZW [31], related to the diffusion process of lithium-ion inside active material particles. It is more reasonable that constant phase element QZw replaces ZW because the slope of the oblique line is not 45 . Therefore, an equivalent circuit model in Fig. 5 is proposed and different electrochemical parameters are derived by ZSimpWin 3.60 software. Resolved Rs and Rct values of all 20 batteries with their capacities are plotted in Fig. 6. The classification of batteries is judged if both Rs and Rct values are smaller than 7 mU, or one of them is between 7 and 10 mU, or bigger than 10 mU. Batteries whose Rs and Rct values are both smaller than 7 mU involve samples 1#, 2#, 4#, 7#, 8#, 9#, 10#, 11#, 12#, 13#, 14#, 15#, 16#, 17#, 19# and 20#. Rct values of samples 3#, 6# and 18# are between 7 and 10 mU and that of sample 5# is more than 10 mU. Concentration polarization impedance is a more important factor influencing on capacity loss of battery than ohmic resistance and charge transfer resistance. Lithium-ion diffusion coefficient DLiþ has a corresponding relation to concentration polarization impedance. The smaller DLiþ, the bigger the concentration polarization. DLiþ is counted by Formula (2) [32]: DLiþ ¼
R2 T2 ; 2A2 n4 F4 C2 s2
(2)
where ideal gas constant R is 8.314 J mol1 K1, absolute temperature T is 298.15 K, the number of electron transfer n is 1, Faraday constant F is 96487 C mol1, the cross-sectional area of electrodes is 0.01 m2, the concentration of lithiumion C is 7.69 103 mol m3 [33], and s is Warburg factor. s has a certain relationship with Zre in Formula (3): Zre ¼ RS þ Rct þ su0:5 ;
Fig. 3 e Pulse discharging and charging voltage curves of partial retired batteries.
(3)
where u is angular frequency, Zre is the real part of impedance spectroscopy corresponding to u, Rs is ohmic resistance and Rct is charge transfer resistance. According to Formula (3), Warburg factor s is the slope of the line when abscissa is u0.5 and ordinate is Zre. Then lithium-ion diffusion coefficient DLiþ can be calculated when s is substituted into Formula (2). Fig. 7 shows the relationships of all 20 batteries between their capacities and diffusion coefficients DLiþ, demonstrating that both of them have positive correlation. Samples 1#, 2#, 3#, 4#, 5#, 7#, 8#, 9#, 10#, 11#, 12#, 14#, 15#, 16#, 17#, 19# and 20# are in
Please cite this article in press as: Liao Q, et al., Performance assessment and classification of retired lithium ion battery from electric vehicles for energy storage, International Journal of Hydrogen Energy (2017), http://dx.doi.org/10.1016/j.ijhydene.2017.06.043
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Table 1 e Voltages of retired batteries at different charging and discharging rates (Unit: V). Sample Discharge 1C Discharge 3C Discharge 5C Charge 1C Sample Discharge 1C Discharge 3C Discharge 5C Charge 1C 1# 2# 3# 4# 5# 6# 7# 8# 9# 10#
3.264 3.260 3.263 3.241 3.254 3.205 3.241 3.262 3.263 3.080
3.055 3.042 3.054 2.955 3.025 2.922 2.956 3.037 3.045 2.747
2.865 2.847 2.865 2.659 2.812 2.657 2.705 2.839 2.847 2.525
3.418 3.443 3.412 3.439 3.421 3.456 3.440 3.424 3.419 3.473
Fig. 4 e Electrochemical impedance spectra of partial retired batteries.
11# 12# 13# 14# 15# 16# 17# 18# 19# 20#
3.259 3.250 3.237 3.264 3.198 3.271 3.197 3.239 3.271 3.108
3.036 3.007 2.993 3.021 2.888 3.065 2.879 2.991 3.076 2.666
2.824 2.837 2.770 2.802 2.606 2.878 2.596 2.758 2.898 2.393
3.422 3.436 3.433 3.434 3.471 3.416 3.468 3.430 3.408 3.487
Fig. 6 e Scatter diagrams of capacities and Rs, Rct of retired batteries.
Fig. 5 e An equivalent circuit model for the electrochemical impedance spectra of retired batteries.
the same rank and samples 6#, 13# and 18# are in another rank if the consistency of retired batteries is judged in the light of DLiþ values more or less than 6 1014 cm2 s1. S-W tests of ohmic resistance Rs, charge transfer resistance Rct and diffusion coefficients DLiþ are performed to assess if these data follow normal distribution, respectively. Then the correlation between capacity and one of them are analyzed, respectively. The results show that the significance levels of Rs, Rct and DLiþ are 0.862, 0.186 and 0.834, respectively, much more than 0.05, suggesting that the distributions of Rs, Rct and DLiþ of these 20 batteries are normal. Pearson's correlation coefficient can weigh degree of correlation between them if two data sets obey normal distribution [34]. Correlation degrees of capacity and one of them (Rs, Rct and DLiþ) are weighed
Fig. 7 e The relationship between the capacities and the diffusion coefficients DLiþ of retired batteries.
by Pearson's correlation coefficient because the distributions of these 20 batteries' capacities, Rs, Rct and DLiþ are normal. Significant correlation is set at the 0.05 level. Two data sets are correlative if their significance level is less than 0.05; if not, they are disrelated. The results display that Pearson's correlation coefficient between capacity and Rs is 0.364, but their significance level is 0.114, more than 0.05, suggesting that the
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relationship between capacity loss and Rs is not correlative. Pearson's correlation coefficient between capacity and Rct is 0.538 and their significance level is 0.014, less than 0.05, indicating that the relationship between capacity and Rct is moderately negative correlation. Pearson's correlation coefficient between capacity and DLiþ is 0.729 and their significance level is 0.000, less than 0.05, revealing that the relationship between capacity and DLiþ is significantly positive correlation, just like the illustration in Fig. 7. Because capacity is not a correlate of Rs, these 20 batteries are divided into three groups in the light of comprehensive judgment of capacity, voltage of pulse discharge, charge transfer resistance and diffusion coefficient. The first group includes samples 1#, 2#, 8#, 9#, 12#, 16# and 19# whose capacities are between 12 and 14 A h, voltage of pulse discharge is more than 2.7 V, charge transfer resistance is less than 7 mU and diffusion coefficient is bigger than 6 1014 cm2 s1. The second group involves samples 3#, 4#, 7#, 10#, 14#, 15#, and 17# whose capacities are between 10 and 14 A h, voltage of pulse discharge is more than 2.5 V, charge transfer resistance is less than 10 mU and diffusion coefficient is bigger than 6 1014 cm2 s1. The third group contains samples 5#, 6#, 11#, 13#, 18# and 20#. The samples in the third group have either small capacities, or low voltages of pulse discharge, or big charge transfer resistance, or small diffusion coefficient, showing more inconsistency. The batteries in the first or second group can be packed and reused for energy storage, respectively, but the charge and discharge regime of energy storage system must be set in consideration of the battery of the worst performance in one group. It is recommended that the batteries in the third group not be reused for their inconsistency.
Conclusions (1) Observational check and capacity measurement are only preliminary ways to screening and classification of retired batteries from electric vehicles. (2) The voltage of pulse discharge is an important indicator for evaluating consistency among retired batteries. (3) Of all factors influencing on battery capacity from the point of view of impedance, Warburg impedance is principal and charge transfer resistance is second. There is no correlation between capacity and ohmic resistance. (4) Performance assessments and consistency sectionalization of retired batteries need synthetic judgment by their different performance parameters.
Acknowledgements The work was sponsored by Natural Science Foundation of Shanghai (17ZR1411200), Alliance Plan of Shanghai Municipal Promotion Association for Transformation of Scientific and Technological Achievements (LM201658) and Social Science Programs of the Education Ministry (16YJAZH035), China.
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