Fast-charging investigation on high-power and high-energy density pouch cells with 3D-thermal model development

Accepted Manuscript Fast-charging investigation on high-power and high-energy density pouch cells with 3D-thermal model development Joris Jaguemont, Noshin Omar, Mohamed Abdel-Monem, Peter Van den Bossche, Joeri Van Mierlo PII: DOI: Reference:

S1359-4311(17)34542-8 http://dx.doi.org/10.1016/j.applthermaleng.2017.09.068 ATE 11125

To appear in:

Applied Thermal Engineering

Received Date: Accepted Date:

10 July 2017 13 September 2017

Please cite this article as: J. Jaguemont, N. Omar, M. Abdel-Monem, P.V. den Bossche, J.V. Mierlo, Fast-charging investigation on high-power and high-energy density pouch cells with 3D-thermal model development, Applied Thermal Engineering (2017), doi: http://dx.doi.org/10.1016/j.applthermaleng.2017.09.068

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Fast-charging investigation on high-power and high-energy density pouch cells with 3D-thermal model development Joris Jaguemonta,b,, Noshin Omara,b , Mohamed Abdel-Monema,b,c , Peter Van den Bosschea,b , Joeri Van Mierloa,b a Vrije

Universiteit Brussel, Pleinlaan 2 1050 Brussel, Brussels b MOBI-ETEC, Vrije Universiteit Brussel c Helwan University, Faculty of Engineering, Cairo, Egypt

Abstract In this paper, insight of thermal behaviour of lithium-ion batteries under fast-charging profiles is investigated. Although battery thermal behaviour has been studied by published models, the reported modeling addresses a specific application: fast-charging applications. Most papers in literature present the fast-charging application from an electrical point-of-view. There, lacks a comprehensive electro-thermal model which can capture both the heat generation, voltage and current variation during the whole fast-charging process. In this study, two charging profiles that are commonly used for fast-charging applications are applied on two lithium-ion chemistries: lithium nickel manganese cobalt oxide (NMC) and lithium titanate (LTO). The first one is designed for high-energy density and the other made for high-power applications. To enlarge the study scope, the batteries have been tested at three environmental temperatures : 25 C, 10 C and 45 C. In addition, a three-dimensional thermal model has been developed within the frame of open source computational fluid dynamics (CFD) to analyze the thermal behaviour of lithium-ion batteries (LiBs). Thermal evolutions of the cells during the profile are recorded to witness the temperature distribution and the validation of the model. The model has indeed well captured the evolution process of the cells from electrical and thermal point-of-views and achieved reasonably good agreement with the measurements. For example, LTO-based cells have shown an interesting behavior for which the battery was able to undergo a fast-charge at any tested temperature and the temperature still remained stable (a temperature rise of less than a 3 C). These parametric studies demonstrate that the model methodology can be used to predict LiB temperature distribution under fast-charging profiles. Keywords: 3D-thermal model, extreme temperatures, NMC, LTO, fast-charging.

1. Introduction Dwindling natural resources and global warming have steered world-wide interests to profusely research about vehicles with alternative energy sources for propelling purposes, i.e. electric and hybrid electric vehicles (EVs/HEVS) [1, 2]. Through the transitions to EVs/HEVS, the general battery-powered vehicle problems come from the lithium-ion battery (LiB) and its performances [3]. In order to achieve the most ideal performance, LiBs often balance between several issues for which can be considered as obstacles for the EV/HEV 

Corresponding author Email addresses: [email protected] (Joris Jaguemont), [email protected] (Noshin Omar), [email protected] (Mohamed Abdel-Monem), [email protected] (Peter Van den Bossche ), [email protected] (Joeri Van Mierlo) Preprint submitted to Applied Thermal Engineering

market penetration: cost [4], safety [5], recycling issue [6], capacity [7, 8]. Since EVs/HEVS target a wide-range mobility, the use of the high-capacity battery can be seen as highpriority in promoting the marketability of EVs/HEVs. Unfortunately, the larger the battery capacity is, the longer is take to charge it for which it does not fit the driver’s interest. Further, increasing the capacity would require to increase the material and then the total cost of ownership [3]. To prevent this, battery charging controls have been investigated in the literature and as it is now, fast-charging method has become a thriving area of research in the field of EVs/PHEVs [9, 10]. However, since fast-charging profile involve highcurrent rates, eects on battery durability and temperature abilities are greatly concerned by this application [11, 12, 13]. In fact, LiBs may rupture, ignite or even explode when it is subjected to high-rate charging, poor September 14, 2017

ventilation, overcharging, or overheating. If the heat dissipation of the battery to the surroundings is less than the heat generation, the accumulated heat within the battery will accelerate the thermal reactions [5, 14, 15, 16]. Thus, the temperature aspect may be dangerous and needs to be understood. Therefore, insight of the thermal properties and performance of the LiBs under fastcharging profiles is crucial to observe. Several fastcharging profiles have been reported in the literature, with mainly the objective of increasing the C-rate of the charging profile [2, 17, 18, 19]. In [20, 21], Abdelmonem et al., proposed dierent dynamic fast-charging current profiles: constant current (CC) charging, constant voltage (CV), and constant current-constant voltage with negative pulse profiles (CCNP-CV). Nonetheless, Abdel-Monems study only demonstrated the eect of these profiles on the electrical and lifetime aspect of a LiB and ageing behavior. There, based on the observation above, a lack a comprehensive study on the thermal eect of fast-charging profile on LiB has to be overcome. Hence, in this study, the eect of the same current profiles on the thermal behavior is proposed. Two cell technologies are investigated: lithium nickel manganese cobalt oxide (NMC) and lithium titanate (LTO). Their characteristics bring the study to a wider-scope, this is because NMC is more suited for high-energy applications and LTO for high-power ones. In addition, the eect of the environment temperature is observed with three ambient temperatures tested: 25 C, 10 C and 45 C, one optimal and two extremes representation of low-temperature and high-temperature operations, respectively [22, 23, 24, 25]. Furthermore, since an electro-thermal study for fast-charging applications is missing in the literature, to extend this study, a model development is proposed. It exists numerous battery electro-thermal models being developed by several researchers mainly focusing on electrochemical modeling [26, 27, 28, 29]. These models as thorough as they are, can simulate the thermal runaway processes or electro-thermal behavior of LiBs at subcell levels. Nonetheless, in-depth parameters (size of the electrode,conductivity, etc.) and complex equations (Poisson’s law) are required to function theses models for which longer computational time is increased and costly tests are needed [28], which at the end it is not suitable for thermal automotive applications. No model exists with a simplified modeling approach for the electro-thermal characteristics of liBs under fastcharging profiles. However, such predictability will be of assistance to battery thermal management systems (BTMSs) and development eective thermal strategy measures against thermal runaway.

Then, the present study aims to develop a model based on a equivalent circuit model (ECM) and a 3D temperature estimation and it is developed on a joined COMSOL/Matlab interface [30, 31]. The objective of the model is to reproduce the thermal and electrical aspects of the two studied LiB-chemistries under the fastcharging profiles at dierent temperatures. The model runs with a simplified level of modeling with instead a 1D-electrical model, coupled with a 3D-thermal model for which in this approach the electrochemical reactions are not considered and a faster computational time is reported. The model is validated through comparison with published experimental data not reported yet in literature for which a main contribution can be observed. Such a model would be of assistance to aid battery management systems (BMSs) by evaluating a fast-computational meshing method to solve complex heat-diusion problems, proposing a simplified modeling approach in order to establish conveniently a potential BTMS and investigating the evolution process under fast-charging methods, which is currently lacking in the literature. The paper is organized in such a way that Section 2 deals with the experimental protocol for parameter assessment. Section 3 describes the model development, Section 4 illustrates the simulation results and model validation, and finally, conclusions are given in Section 5. 2. Experimental setup 2.1. Cell features The electro-thermal behavior of pouch Li-ion cells is investigated to observe the influence of fast-charging methods. Two types of cell chemistries are tested in this study, namely NMC and LTO. As one highpower cell for EVs, HEVs, the LTO-based cell is composed of LiNi0.33 Mn0.33 CoO2 (NMC) positive electrode and Li1.33 Ti1.67 O4 (LTO) negative. And for highenergy density application, the NMC-chemistry is made of LiNi0.33 Mn0.33 CoO2 (NMC) positive electrode and LiC6 (Graphite). Their nominal capacities of these pouch cells are 20 Ah, and 5 Ah, respectively. The thermal characterization and validation tests were carried out according to the conditions presented in Table 1. 2.2. Experimental test bench As shown in Fig.1, the cells were test in an experimental setup. The cells were placed in an climatic chamber in a highly hermetic equipment which facilitates the reproduction of a stable environmental temperature, called, Ttest . It provides eective evaluation of 4

Table 1: Characteristic of the NMC and LTO cells

Properties

NMC

LTO

Length of the cell,mm

217

23

Width of the cell,mm

130

173

Thickness of the cell,mm

7.1

4

Weight of the cell,g

428

262

Length of the tabs,mm

40

40

Width of the tabs,mm

30

85

Nominal voltage,V

3.65

2.2

Nominal capacity, Ah

20

5

End of charge voltage, V

4.2

2.8

End of discharge voltage, V

3

1.5

Ac impedance (1 KHz), mohm

3

0.7

Specific energy, Wh/kg

174

42

1. Capacity test;

Energy density, Wh/L

370

90

2. Hybrid pulse power capability (HPPC) [34];

Specific power (DoD 50%, 10 s), W/kg

2300

2250

Power density (DoD 50%, 10 S), W/L

4600

4400

Recommended charge Current, A

10

5

Maximum discharge Current, A

100

150

Mechanical

Electrical Figure 1: Experimental test bench

properties shown in Table 1 are used in the following tests:

3. Open-circuit voltage (OCV) [35, 36]. All this tests have been performed at the three tested temperatures, i.e.: 10 C, 25 C and 45 C to extant the boundaries of the model. An insight description of the tests has already been made in a previous study [23]. Additionally, to obtain the surface-heat distribution of the pouch cells, surface temperature of the cells were recorded. A Ti25 thermal camera captured IR images at regular time intervals. To achieve accurate results from the IR camera, the surface of the cells were painted uniformly with a pitch-black paint and placed in a dark environment (to avoid reflected heat interference). The comparison results of the IR pictures and the model are shown in Section 4 .

the thermal and safety properties of the sample. In the present study, a thermocouple was attached to the cell surface to obtain the temperature variation during the test using an NTC 5K thermistor (EPCOS R , Munich, Germany), with a measuring range of 0/100 C and a tolerance of 1%. It was placed near the positive tab because studies [32, 33] have shown that is a spot where the maximum heat is observable. As shown in Fig.1, the cell was cycled by a battery cycler (A ACT 0550 (80 channels) battery tester (PEC R )) through the connection between the cell tabs. During the fast-charging tests, the temperature, voltage and current variation of the cells were recorded by a remote computer controlling all the cycling statins, from which the electro-thermal behavior of the cells could be obtained synchronously.

2.4. Charging protocol The fast-charging protocol consists of applying highcharging current, namely 4C (80A for NMC cells and 20A for LTO chemistry), until the battery voltage reaches the maximum voltage (max voltage as in Table 1) followed by a CV phase until the cut-o current reaches (0.05C) where C is the capacity of the cell (Ah). In this study, two cases (listed below) have been selected to investigate the impact of the fast-charging methods on LiBs.

2.3. Thermal characterization of the pouch cells In order to characterize the electro-thermal behavior of a Li-ion cell precisely, the geometry, and electrical

1. Constant-current constant voltage (CC-CV); 5

2. Constant current negative pulse constant voltage (CCNP-CV) [37].

In the CC phase of the CC-CV charging, a constant 4C-charging current is applied to the cell battery until the battery voltage reaches a maximum allowable battery voltage. 4C is a value commonly documented in literature [20]. And then, in the CV phase, the charging current diminished while holding the maximum allowable battery voltage until the charging current reaches a predetermined cut-o current, generally 0.05C. The other fast-charging methods are just a alternate version of the CC phase while the CV remains the same [20]. In the CCNP-CV, a constant charging current (4C) followed by a 2C (40A for NMC, and 10A for LTO) negative pulse and a 2-s rest time were applied until the battery voltage reaches the maximum allowed voltage., as shown in Fig.2. The pulse width of the negative pulse aects the charging process and depends on the value of the discharge capacity during the charging process. Thus, the discharge capacity during the charging is fixed in this case to be approximately 0.1 Ah to avoid the cell deterioration [20]. In a previous related study [20], the authors have shown the influence of the negative pulse current on the capacity fading. Based on that result, charging profile with negative pulse at a very low frequency (mHz) has a reduced impact on the lifetime of the cell. Indeed, the negative pulse of the CC-CVNP technique at a very low pulse frequency (20 mHz) can be utilized to decrease the diusion resistance and thus it accelerates the diusion of Li+ ions through the active materials in order to improve the active material utilization. Nonetheless, the thermal aspect of this profile has not been studied. Therefore, the current of negative pulse has been selected, in this work, to the same frequency, 20 mHz, in order to a comparative study regard the thermal eect on pouch cells.

Figure 2: Top: fast-charging profiles. Case 1: CC-CV, case 2: CCNPCV. Bottom: Charging protocol sequence.

3. Model development In this study, alternatively to fast-charging experiments, a model capable of reproducing the thermal and electrical behavior of the pouch cells is proposed. The next subsections describe the development of the model.

The proposed sequence for the data collection procedure for fast-charging test for which the experimental test shown in Fig.1 is used, is described in Fig.2. After a preconditioning test consisting of three complete charge-discharge cycles at 25 C to 10% state-of-charge (SoC); the cell is tempered at the tested temperature. Then, one of the fast-charging profile described abode is applied for the cell to reach 90% SoC. After each fast-charging test, the cell is completely discharged at 25 C with a 1C (20A for NMC and 5A for LTO) constant discharging current to 10% SoC in order to be able to compare the impact of the dierent profiles and ambient temperatures.

3.1. Pouch-cell geometry Fig.3 presents the 3D-schematic of the two pouch cells. In general and as it is currently modeled in the literature by several researchers [29][38], the battery is composed of many layers, containing a negative current collector (C-C), negative electrode, separator, positive electrode and positive C-C). Nonetheless, running a model integrating the layer composition of a pouch cell needs a long computational time for which a lengthy list of parameters is required. Then, in order to simplify the model, a modeling approach using three elements is proposed instead. As show by Fig.3, the cell 6

is composed of three domains: positive tab, negative tab and core. In this context, the core is assumed to be a consisting-equivalent flat element to be configured as a stack of layers. Simply speaking, the several layers composing the pouch cell are represented by the core for which also the thermal parameters are dierently acknowledged. For example, the anisotropicity of the thermal conductivities are assumed, in the x- and y-axis, the conductivities show a higher-value than in the z-direction resulting from the single layer assumption [39, 23]. Additionally, the thermal conductivities in the y-direction and the z-direction are found similar, as reported in the literature [28], thus the same values are used. Finally, the CFD software COMSOL was used to generate an extremely coarse mesh to decrease the meshing eort, consisting of 6059 domain , 3639 boundary elements, and 773 edge elements. The Heat transfer in Solids physic is used to process the heat equations.]

3D-thermal model section as mentioned in the previous subsection. As shown by Fig.5, the ECM is a 2nd-order Thevenin model for which a combination of voltage sources, resistors, and capacitors is defined [41]. Simply speaking, the cell’s voltage response is calculated with the joined series resistor and two RC-parallel networks at an initial SoC, SoCinit . The SoC of the cell is calculated using extended kalman filter (EKF), it depends on the initial capacity (Ah) also dependent on temperature. As it is not the focus of the paper, the EKF methodology will not be explained here. Nonetheless, readers are invited to check [41, 1] for more information. The output voltage equation is calculated with the following equation, [42]: V batt = OCV

R0 I batt

R1 I1

R2 I2

(1)

where OCV is the open-voltage source (V), Ibatt the battery current (A) and I1 and I2 , the currents in the RC circuits, R1 //C1 and R2 //C2 , respectively. In (1), the electrical parameters (capacitances, resistances and OCV) are obtained with the thermal characterization explained in Section 2.3. The resistances are then used to estimate the heat generated in the core and tabs domain, as will be explained in the next subsection.

3.2. Description of the model In this paper, a simplified approach for a 3Dthermal model is proposed. The approach is shown in Fig.4. Usually, a 3D-thermal-electrochemical model uses 1D-electrochemical equations coupled with a 3Dtemperature estimation model to study cells temperature and voltage characteristics [40], [28]. However, as mentioned before, the approach is rather time consuming and the parameter requirement involves invasive and expensive techniques [40]. In this study, the model is based on a Matlab/COMSOL Livelink interface, associating an 0D-electro-thermal model and a 3D-thermal model. Any input load profile in the electrical model yields to the output voltage, applied current and the heat source estimation at the core domain. Then, as shown in Fig.4, the output heat sources are infused into the 3D-thermal model and evenly distributed in the core and tabs domains. The Matlab interface controls the 0D-electro-thermal model, while the COMSOL software computes the 3D-thermal representation. In this manner, the acknowledged electrochemical reactions are simplified to reduce the computational time and the meshing eort of the model. At the end, this simplify modelling approach aims to serve as a basis for future BTMSs.

3.4. Thermal modeling To calculate the thermal behavior of the pouch cell, the following factors are taken into account in the model: the charge and discharge current, the resistance of the current collector and electrode, the heat generated from the electrical behavior, the heat generated from the thermal reactions between the pouch cell domains and the heat loss due to the environment. The heat generation power of the cell is evaluated from the modified enthalpy-of-electrochemical-reaction following the energy balance study of Bernardi et al. [43, 44]: qg

= qohmic = R0 :I 2 + R1 I12 + R2 I22

(2)

where qg is the heat flux (W), and qohmic , the heat effects of the ohmic and polarization resistance, called irreversible” heat . The 0D-model calculates the volumetric heat generation signal only dependent on time, with the internal resistances and the OCV, as shown by the equations of (1)-(2). By considering a high-current application (fast-charging profile), the entropic reaction of the cell, or the reversible heat is not regarded [42]. Further, for each thermal reaction, several assumptions on the physical properties of cell are proposed in

3.3. Electrical modeling To calculate the electrical output characteristics of the pouch cell, an equivalent circuit modeling (ECM) approach has been developed to assess both the output voltage of the cell and the heat generation used for the 7

(a) Simple representation of the NMC thermal model.

(b) Simple representation of the LTO thermal model.

Figure 3: graphic representation of the pouch cells and the equivalent core model for thermal modeling.

evolution with temperature is not considered in this study. 3. Current distribution and heat generation in the cell are isotropic in the cell during each chargedischarge process. 4. Except for the thermal conductivity, materials inside the cell are also defined as isotropic for which they have uniform physical properties; In the core domain, considering the assumptions listed above, the energy balance equation of the cell under adiabatic condition based on [43] can be written as: Figure 4: Schematic of the complete model

mC p

T t

=

2

qg

2

2

+ kx Tx2 + ky Ty2 + kz Tz2

qconv (3)

with m is the mass of the cell (kg), Cp the specific heat of cell (J.kg-1 .K-1 ), T is the cell temperature (K), qg is the internal generation heat (W), and kn (n indicates x, y and z)) is the thermal conductivity (W.m-1 .K-1 ) along the x-direction, y-direction and z-direction, respectively. As mentioned earlier, the conductivities in the x-direction and y-direction are equivalent. Lastly, for the energy balance of the cell and the boundary conditions of the model, the heat transfer with the surroundings is calculated by following the convection equation [44]:

Figure 5: Schematic of the 2nd-order Thevenin model [41]

qconv

order to simplify the computing process the heat generation process inside the pouch cell [45]:

= hS (T amb T )

(4) 2

with S the cross-sectional area (m ) and h the convection transfer coecient (W/m2 .K). In this case the cell is cooled by natural convection, thus h equals 5 W/m2 .K. The thermal parameters for each domain are listed in Table 2. Since it is dicult to acquire the thermal parameter with experiment, their values are based on previous studies [47, 48, 49].

1. The internal radiation heat can be ignored resulting from its negligible overall eect; 2. Cell specific heat and thermal conductivity are assumed to be constant during operation [46], their 8

Table 2: Dynamic parameters used for the thermal model [47, 48, 49]

Domain

Cp

h

k

(J.kg-1 .K-1 )

(W.m-2 .K-1 )

(W.m-1 .K-1 )

903

5

170

Negative tab

385

5

LTO core

1437

5

NMC core

1978

5

Positive tab

could lead to a final battery temperature where several hazards can happen and even thermal runaways. Further, the results of the simulation for the NMCcell with the two fast-charging method are presented in Fig.7. The first thing that can be noticed is that, the global shape of the temperature evolution seems to correspond with the one observed with the experimental tests for the two tests. Secondly, in the CCNP-CV plot, the experimental temperature profile appears to be sequenced due to the reason that the thermal camera selfcalibrated itself during the recording. Lastly, as shown in Fig.7, the spatial distribution which shows a hot region observed for the NMC cell in the center, is evenly reproduced by the 3D-thermal model with the same hot spot depicted near the positive tab. The reason is due to the high thermal resistivity of the aluminum composing the positive tab which produces more heat than the copper-based negative tab [50, 32]. Regarding the LTO chemistry, results displayed in Fig.8 showed the same agreed temperature distribution between the model and experimental work for which the positive is slightly hotter than the negative tab for the obvious same reasons stated earlier. Nonetheless, the results clearly contrast with the NMC cell when looking at the final temperature. Indeed, the gradient for the LTO chemistry is found lower (around 17 C), also a 2 dierence between the beginning and the end of the CC phase. This demonstrates the good and thermal stability of the LTO-based cell. Moreover, something to be pointed out when looking at the temperature evolution of the LTO cell for the two fast-charging methods is the temperature curvature significantly increasing at the end of the CC phase (at 700s for the CCNP-CV test and 600s for the CC-CV profile). After a little literature perusing, the reason for this thermal behavior is resulting from the internal resistance evolution of the LTO cell. As shown in Fig.9, the charging resistance evolution, given by the manufacturer is higher at a low depth-ofdischarge (DoD), i.e. at high SoC, meaning higher heat is generated while charging at high SoC regions, considering equation (1). Alternatively, the discharge internal resistance is higher at high DoDs, i.e. at low SoC points. Probably, electrochemical reactions such intercalation / de-intercalation play a role in this opposite behavior but in-depth studies need to be investigated to confirm it. Additionally, considering the LTO internal resistance behavior, a innovative thermal management strategy can clearly be established where the best SoC points can be tracked to yield to the maximum / minimum heat generation in a specific automotive application or in cold weather situations. Finally, the capacity eciency reported in Table 3 for

398

= ky = 49 kz = 0.1 kx = ky = 39 kz = 0.3 kx

4. Results and discussion All test results of the fast-charging study are described in this section, sorted by the tested temperatures: 25 C, 45 C and 10 C. The initial conditions required in the simulation sets the initial environment and the ambient temperature to the tested temperature. For example, for the test at 10 C, the battery starting temperature is 10 C, as well as the ambient. For validation purposes, the thermal behaviour of the LiBs has been simulated using the two fast-charging profile displayed in Fig.6a and Fig.6b as an example. In this context, the 3D thermal picture at the highest temperature point is compared with the 3D model, also, the corresponding temperature evolution with time is shown. As it can be expected from Fig.6a and Fig.6b, the highest temperature point in the test matches the end of the CC phase in both situations because of the continuous high current applied. For this reason, only the CC part will be shown in the results and discussion section. For the electrical model, a specific subsection has been realized for which some of tests are displayed in order to point out particular electrical aspect fo the pouch cells and also the validation of the model. Both tests results and capacity characteristics at three dierent ambient temperatures for all the test are reported in Table 3. Also, in this table, the charge capacity eciency with is the ratio of the charge capacity in the CC phase over the initial capacity obtained at 25 C. 4.1. Room temperature simulation results Fig.7 shows the charging performances of the NMC cell at the ambient temperature for the CC-CV and the CCNP-CV tests. The thermal evolution graphs of the NMC cell show a quick temperature gradient of almost 20 C. Indeed, due the composition of the NMC-based cell, the material tends to provoke a high thermal generation when applying a high current. This signifies that fast-charging a battery pack composed of NMC cell 9

(a) CCNP profile

(b) CC-CV profile

Figure 6: applied load profiles for the simulations: example with a NMC battery.

the dierent tests concur with the statement made earlier for which the fast-charging profile is supported in a more ecient way for the LTO-based cell with 90% of the cell charged against 60% for the NMC cell in the CC phase. Generally, fast-charging systems in charging station tend to recover 80% of the capacity [19, 18, 37].

a mere three-degree variation was observed. Nevertheless, the same curvature is detected at the end of the CC phase for which a sudden increase in temperature is observable. At 45 C, this curve appears to be not really problematic (1.2 C of temperature elevation) but it still needs to be considered. Additionally, as reported by Table 3, the charging efficiency has increased for both chemistries and tests. The reason is due to the speed of the lithiation increased by the high-temperature which enables higher capacity. From the table and the above results, it clearly encourages the use of LTO-based chemistry in automotive applications due to their thermal stability.

4.2. High-temperature simulation results Fig.10 and Fig.11 present the high-temperature tests for NMC and LTO. Again, the NMC-based technology shows a high ending temperature of around 60 C. Nonetheless, it can be noted that the temperature elevation (ending temperature - initial temperature) is less than at 25 C. This is due to the fact that the resistance is lower at high temperature, hence less heat is generated. Still, the high-current application provokes a high final temperature of 60 C at the end of the CC, which is not optimal because fast ageing eect happen at this thermal point. Also, a remark could be done on the temperature distribution by comparing the thermal pictures of the NMC cell and the 3D-model result at 25 C, and 45 C. In reality, other the fact that a good agreement is displayed between the 3D thermal picture and the output temperature of the model, the environmental temperature does not really aect the surface distribution of the temperature. The same pattern is observed with the temperature localized at the center of the cell. By comparing the two chemistries, the test at 45 C, emphasizes the fact that LTO is a interesting candidate for extreme-conditions operation. Indeed, for both tests the overall cell temperature starting actually at 47 C rose up to 49 C in the center and 48 C for the edges,

4.3. Low-temperature simulation results The model and experimental results of the NMC surface temperature distribution and temperature evolution at 10 C are shown in Fig.12. The results show that because the internal resistance rises, the temperature elevation is higher than at ambient or 45 C. Nonetheless, it can be seen that the heat generation is inside the is less with the CC-CV than the CCNP-CV. This is results of the specificity of the negative pulse profile where the discharge phase in the CCNP provokes higher internal heat generation due to exothermic heat. This heat in fact warms the battery and reduces the internal resistance which serves as a current blocker at low-temperatures. Certainly, this specific charging profile can be investigated in thermal management strategy for fast-charging applications. Alternatively, with the CC-CV profile, as it will be shown in the next subsection NMC voltage limit is reached rapidly because of the high internal re10

Table 3: Capacity results for the two tests at three temperatures

Type of cell

T( C)

Ttest

NMC NMC NMC NMC NMC NMC LTO LTO LTO LTO LTO LTO

25 25 10 10 45 45 25 25 10 10 45 45

CC-CV CCNP-CV CC-CV CCNP-CV CC-CV CCNP-CV CC-CV CCNP-CV CC-CV CCNP-CV CC-CV CCNP-CV

Capacity results 1C capacity (Ah) Capacity at 25 C after CC (Ah) 20.5 12.80 20.5 10.05 20.5 9.6 20.5 9.1 20.5 14.1 20.5 14.8 4.7 4.1 4.7 4.4 4.7 3 4.7 3.2 4.7 4.3 4.7 4.55

sistance, thus the CC phase is shorten, hence the lower heat generation. Fig.12 shows the evolution of the average temperature of the simulation (orange) and experiment (blue) under the fast-charging profiles. It is clear that both curvatures are similar, showcasing the good aspect of the 3D-thermal model. With regards to the LTO technology displayed in Fig.13, the results show that the center of the LTO cell surface has the highest temperature, followed by the edge of LTO cell surface, and the electrodes have the lowest temperature because they are exposed to more ambient temperature. Additionally, the temperature evolution over testing time displays the same typical curvature at the end of the CC phase for which more than 2 C temperature elevation is observed. This is also due to a higher internal resistance yielding to more heat generated. This specific LTO curvature found when charging at high SOC could in fact be an interesting mechanism for fast-charging at low-temperature for which it could help recuperate capacity. Indeed, with a quick look at the charging eciency in Table 1, one can observed that at low-temperatures, fast-charging a battery is quite challenging because only 45% of the NMC cell is charged against 65% for the LTO cell, which the strong stability of this chemistry compared to others. Still, a strategy integrating the specific curvature could be interesting to investigated. Finally, the variations of the thermal distribution of the model and the experimental test revealed by Fig.13 show also that the 3D-thermal is in good agreement for which less 1 C is found by comparing, which verifies the eectiveness of the thermal model.

Charging time to reach Vmax 576 515 458 433 633 693 746 884 967 557 764 904



Charging e ciency (%) (s) 62.5 59 46.6 44.4 68.7 72.2 87 93.3 63.6 67.7 91.2 96.5

4.4. Electrical model validation In this subsection, the electrical model is validated using the experimental tests. At the same time, some valuable information regarding the electrical perfomances of the two chemistries are given. In case of pure investigation, some of the tests realized in the framework of this study are shown. Also ,the model deviation is considered with the root-mean-square error and is defined as follow :

error

= RMS E(Valmeas ; Valsim )

(5)

where Valmeas is the measured value and Valsim is the simulated value and Valmeas . Fig.14 displays the simulated and the measured voltage output of the NMC cell for dierent tests: CCNPCV at 25 C, CCNP-CV at 10 C and CC-CV at 0 C. At a low temperature, because the internal resistance rises, the NMC voltage limit is reached rapidly (Fig.14, bottom). Then, this leads directly to a shortened CC phase with longer CV phase. Hence, the lower heat generation observed at 10 C in the last subsection. Subsequently the CCNP-CV test profile of the NMC at 10 C (Fig.14, middle) shows a CC phase less harmed by the cold temperature with a longer CC phase than the CCCV profile for which a higher terminal temperature was found. Nonetheless, by comparing the CCNP-CV test profile of the NMC at 10 C and 25 C, the discharging pulse happen more frequently at the beginning due to the internal resistance. Then, the battery warms up and the discharging pulses follow the expected protocol. At the end, it can be noted that a important bond between 11

Figure 8: fast-charging tests and validation results of the model for LTO technology at 25 C including 3D thermal pictures, temperature evolution and voltage behavior.

CC-CV at 0 C. It can be observed that the LTO chemistry show no electrical limits in undertaking the fastcharging profiles at extreme temperatures. The profiles are executed without complications except at 10 C (Fig.15, bottom) for which a lower capacity value resulting from the cold weather is found. Still, the results display the interesting ability of the LTO-chemistry regarding its electrical performance for fast-charging application which is due to its high-power capability. Alternatively, Fig.14 and Fig.15 show the measured and estimated voltage for the two chemistries under the loading profiles condition. A good agreement can be observed for all technologies. It can be observed that the error remains below 4% almost over the full duration of the validation tests. This implies that the electrical model can be used in further application for which

Figure 7: fast-charging tests and validation results of the model for NMC technology at 25 C including 3D thermal pictures, temperature evolution and voltage behavior.

the temperature and the electrical performance exist and also that NMC pouch cells, being energy-based cells, are not suited for high-power application. In the same way, Fig.15 shows the simulated and the measured voltage output of the LTO-based cell for different tests: CC-CV at 45 C, CCNP-CV at 25 C and 12

Figure 9: charge and discharge resistance evolution [manufacturer].

a thermal or energy management strategy can be established at dierent temperature.

5. Conclusion In this paper, the objective has been to perform fastcharging methods on Li-ion batteries and see the impact of the high-current approach on the thermal generation of pouch cells. In this context, two charging profiles were investigated: a standard CC-CV and less wellknown, CCNP-CV. Both were applied on a high-power cell, LTO-based chemistry (5 Ah), and on a high-energy cell, NMC-based chemistries (20 Ah). Several tests were performed at three ambient temperatures, namely: 25 C, 10 C and 45 C. As seen from the results, experiments showed that at 25 C, the NMC cell performed well with a temperature distribution fairly uniform after the CC phase (highest temperature region). However, when the external temperature is below the room temperature, 10 C for example, the results showed an inability for the NMC to conduct the fast-charging profiles resulting from the increase of the internal resistance. As a result, the CC phase was reached immediately and the charging process switched to the CV phase where the charging current slowly decreases, hence the poor charging performances. But, when the CCNP was applied, the CC phase appeared to be less aected by the coldness of the environment. Indeed, the discharging pulses of the CCNP phase helped increasing more rapidly the temperature of the NMC cell due to more significant exothermic reactions during the discharge for which the cell warmed up and its internal resistance reduced. At higher

Figure 10: Fast-charging tests and validation results of the model for NMC technology at 45 C including 3D thermal pictures, temperature evolution and voltage behavior.

temperature, 45 C for example, the environmental temperature did not really aect the surface distribution of the temperature because the same pattern was found. Regarding the LTO pouch cell, experiments showed that at 25 C, the temperature distribution is cleanly uniform, with 1 C of maximal temperature dierence. Further, for the other temperatures, the results showed a higher temperature evolution at 10 C resulting from the rise of the internal resistance of the cell, leading to higher heat generation. Subsequently, the lowest temperature gradient was found minimal at 45 C, thanks to the strong thermal stability of the titanate chemistry. Additionally, a specific trend showed up during the testing, the temperature curvature significantly increasing 13

Figure 11: Fast-charging tests and validation results of the model for LTO technology at 45 C including 3D thermal pictures, temperature evolution and voltage behavior.

at the end of the CC phase. Due to a high charging resistance at high SoC points, the LTO temperature rapidly rose up. Considering this specific trend, a innovative thermal management strategy can clearly be established where the best SoC points can be tracked to yield to maximum temperature during cold weather for example. At the end, both fast-charging profiles could be applied on the battery at all the tested temperature which emphasizes LTO as a good candidate for high-power applications. Nonetheless, tests could be performed in the future to analyze these eects on battery cell ageing. Indeed, during fast-charging tests, ageing phenomena happen since high-current profiles at extreme temperatures are applied. These hazardous deteriorations are noteworthy for decreasing the capacity and increase the resistance for which both are implied in the electro-thermal aspect of a LiB.

Figure 12: Fast-charging tests and validation results of the model for NMC technology at 10 C including 3D thermal pictures, temperature evolution and voltage behavior.

Alternatively, a three-dimensional electro-thermal model has been developed within the frame of matlab/COMSOL Livelink coupling electric parameter with heat transfer and energy balance for a single pouch cell. Indeed, no model currently exists with a simplified modeling approach for the electro-thermal characteristics of LiBs under fast-charging profiles. However, such predictability will be of assistance to battery thermal management systems (BTMSs) and development eective thermal strategy measures against thermal runaway. Therefore, the proposed model solved a coupled system of equations that described the relations between the electrical and thermal characteristics of the cell as 14

Figure 13: Fast-charging tests and validation results of the model for LTO technology at 10 C including 3D thermal pictures, temperature evolution and voltage behavior.

well as their interactions with the surroundings. The model has been validated with significant experimental data for the predictions of voltage, current and temperature variation within the cell under various discharging current rates. The model has reproduced well the evolution process of a cell for the fast-charging application dedicated to this study. Given that the physics and structure of the model in this work had been developed for generic environmental conditions and configurations, the model can be easily extended to other LiBs and LiB modules with dierent combinations of materials, geometries, operating conditions and cooling eects. In addition, the model can potentially be used to assist BMSs. The published data in this study has shown interesting thermal behaviors, like the specific trend of the LTO cell, for which it could be interesting to integrate in future applications. Indeed,

Figure 14: fast-charging tests and validation results of the electrical model for NMC technology at 25 C. Top to bottom: CCNP-CV at 25 C, CCNP-CV at 10 C and CC-CV at 10 C.

such a predictive tool can be further to tailored to assist the design of battery thermal management systems from the safety perspective for fast-charging application. In addition, to further improve the pouch cell model it is key to have a more accurate solution method com15

ment strategy will be considered still in the scope of fast-charging applications but also a more comprehensive numerical study on the electrochemical-thermal coupled model. Acknowledgements This research has been made possible, thanks to the research project ’BATTLE’ and was funded by the Flemish Agency for Vlaandere is undertaken (IWT130019). Further, we acknowledge Flanders Make for the support to our research team. References [1] D. Linden, T. B. Reddy, HANDBOOK OF BATTERIES 3rd Edition, 2002. [2] D. Anse´an, M. Gonz´alez, J. Viera, V. Garc´ıa, C. Blanco, M. Valledor, Fast charging technique for high power lithium iron phosphate batteries: A cycle life analysis, J. Power Sources 239 (2013) 9–15. [3] I. Dincer, H. S. Hamut, J. Nader, Thermal Management of Electric Vehicle Battery Systems, wiley ed., 2017. [4] D. L. Wood, J. Li, C. Daniel, Prospects for reducing the processing cost of lithium ion batteries, J. Power Sources 275 (2015) 234–242. [5] S. Abada, G. Marlair, A. Lecocq, M. Petit, V. Sauvant-Moynot, F. Huet, Safety focused modeling of lithium-ion batteries: A review, J. Power Sources 306 (2016) 178–192. [6] A. Sonoc, J. Jeswiet, V. K. Soo, Opportunities to Improve Recycling of Automotive Lithium Ion Batteries, Procedia CIRP 29 (2015) 752–757. [7] K. Yiu, Battery Technologies for Electric Vehicles and Other Green Industrial Projects, Power Electron. Syst. Appl. (PESA), 2011 4th Int. Conf. (2011). [8] S. Pelletier, O. Jabali, G. Laporte, M. Veneroni, Battery degradation and behaviour for electric vehicles : Review and numerical analyses of several models, Transp. Res. Part B 0 (2017) 1–30. [9] C. Zhang, J. Jiang, Y. Gao, W. Zhang, Q. Liu, X. Hu, Charging optimization in lithium-ion batteries based on temperature rise and charge time, Appl. Energy 194 (2017) 569–577. [10] K. Zaghib, M. Dontigny, A. Guerfi, P. Charest, I. Rodrigues, A. Mauger, C. M. Julien, Safe and fast-charging Li-ion battery with long shelf life for power applications, J. Power Sources 196 (2011) 3949–3954. [11] K. Amine, J. Liu, I. Belharouak, High-temperature storage and cycling of C-LiFePO4/graphite Li-ion cells, Electrochem. commun. 7 (2005) 669–673. [12] J. Shim, R. Kostecki, T. Richardson, X. Song, K. A. Striebel, Electrochemical analysis for cycle performance and capacity fading of a lithium-ion battery cycled at elevated temperature, J. Power Sources 112 (2002) 222–230. [13] M. Kassem, J. Bernard, R. Revel, S. P´elissier, F. Duclaud, C. Delacourt, Calendar aging of a graphite/LiFePO4 cell, J. Power Sources 208 (2012) 296–305. [14] X. Feng, M. Fang, X. He, M. Ouyang, L. Lu, H. Wang, M. Zhang, Thermal runaway features of large format prismatic lithium ion battery using extended volume accelerating rate calorimetry, J. Power Sources 255 (2014) 294–301.

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Highlights: • Insight investigation of fast-charging profiles • The influence of extreme temperatures on lithium-ion batteries is discussed. • We present the development of 3D-thermal model for high-power (LTO) and high-energy cells (NMC). • A 3D simplification of the thermal model couplings can reduce computation time.