Numerical study of a novel battery thermal management system for a prismatic Li-ion battery module

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10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, 10th International Conference on Applied Energy China(ICAE2018), 22-25 August 2018, Hong Kong, China

Numerical study of a novel battery thermal management system for Numerical The study a novel Symposium battery thermal system for 15thof International on Districtmanagement Heating and Cooling a prismatic Li-ion battery module a prismatic Li-ion battery module Assessing the feasibility of using the heat demand-outdoor Wenzheng Liaa, Xiaoru Zhuangaa, Xinhai Xua,b, * Wenzheng Li a, Xiaoru Zhuangdistrict , Xinhai heat Xua,b,*demand forecast temperature function for long-term School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, 518055, China a

a Shenzhen Lab of Mechanisms and Control in Aerospace, Harbin Institute of Technology, Shenzhen 518055, China SchoolKey of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, 518055, China a,b,c a a b c b Shenzhen Key Lab of Mechanisms and Control in Aerospace, Harbin Institute of Technology, Shenzhen 518055, China b

I. Andrić

*, A. Pina , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Correc

a IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal Abstract b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France Abstract c Département Systèmes Énergétiques et Environnement - IMT Atlantique,by 4 rue Kastler, 44300 Nantes, The life time and performance of Li-ion batteries are significantly influenced theAlfred operating temperature. In France order to maintain The life time and and avoid performance of Li-ion batteries are significantly by of thethe operating to maintain performance temperature related degradation, the highestinfluenced temperature batteriestemperature. are requiredIntoorder be below 35 oC, C, performance and avoid temperature related degradation, the highest of the required to are be below and the temperature variation between batteries in a module needs temperature to be less than 5 obatteries C. Theseare requirements hardly35 to obe o and the temperature variation betweenbattery batteries in a module needs system to be less than 5in C. These requirements are hardly satisfied by the traditional air cooling thermal management (BTMS) an extreme ambient condition of 40to obe C. Abstract satisfied byathe traditional air cooling battery systeminvestigated (BTMS) in for an aextreme condition 40 oC. Therefore, novel water cooling BTMS was thermal proposedmanagement and numerically moduleambient consisting of 15 of prismatic Therefore, novel water cooling was proposed andresults numerically investigated a module consisting of 15 prismatic temperature lithium ironaphosphate batteries at 1BTMS C discharging rate. The show that the averagefortemperature of 34.5 oC and District heating networks are commonly addressed in the literature as one of the most effectiveo solutionso for decreasing the andrate temperature lithium ironwithin phosphate at 1than C discharging The results show thatinlet the average temperature 34.5 difference each batteries battery less 1.8 oC canrate. be obtained if the water temperature is 28 Cofand the Cflow is 1 g/s. greenhouse gas emissions from the buildingo sector. These systems require high investmentso whicho are returned through the heat C can be batteries obtainedinif the the module water inlet temperature is 28 and thebattery flow rate is 1 g/s. difference within each battery less between than 1.8 individual The Caverage temperature The average temperature variation is less than 0.5 C. sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease, C. The average battery temperature The average temperature variation between individual thethe module less than reduces as the water flow rate increases. However, batteries the effectin of wateris flow rate 0.5 on othe battery temperature is far less prolonging the investment return period. reduces as than the water flow ratetemperature. increases. However, the effect of the water flow rate on the battery temperature is far less significant the water inlet The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand significant than the water inlet temperature. forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 Copyright © 2018 Elsevier Ltd. All rights reserved. that vary in both construction period (low, medium, high) and three district ©buildings 2019 The Published by Elsevier Ltd. and typology. Three weather scenarios Copyright ©Authors. 2018 Elsevier Ltd. Allresponsibility rights reserved. Selection and peer-review under of the scientific committee of the 10th International Conference on Applied This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were th Selection and peer-review under responsibility of the scientific committee of the 10 International Conference on Applied Energy (ICAE2018). Peer-review under responsibility of the scientific committee ICAE2018developed – The 10th International on Applied Energy. compared with results from a dynamic heat demand model,ofpreviously and validated byConference the authors. Energy (ICAE2018). The results showed that when only weather change is considered, the margin of error could be acceptable for some applications Keywords: BTMS; Li-ion battery; thermal management; minichannel; liquid cooling (the errorBTMS; in annual was lower than 20%minichannel; for all weather scenarios considered). However, after introducing renovation Keywords: Li-iondemand battery; thermal management; liquid cooling scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the 1. Introduction in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and 1.decrease Introduction renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the Electric vehiclesThe (EVs) aresuggested considered promising alternative for parameters traditionalforinternal combustion engine coupled scenarios). values couldasbea used to modify the function the scenarios considered, and Electric vehicles (EVs) are considered as a promising alternative for traditional internal combustion engine vehicles (ICEVs) [1]. Li-ion batteries are one of the most critical components in EVs as the energy storage unit improve the accuracy of heat demand estimations.

vehicles (ICEVs) [1]. Li-ion batteries are one of the most critical components in EVs as the energy storage unit © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. * Corresponding author.

address:author. [email protected] * E-mail Corresponding Keywords: Heat demand; Forecast; Climate change E-mail address: [email protected] 1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility the scientific 1876-6102 Copyright © 2018 Elsevier Ltd. All of rights reserved. committee of the 10th International Conference on Applied Energy (ICAE2018). Selection and peer-review under responsibility of the scientific committee of the 10th International Conference on Applied Energy (ICAE2018). 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 – The 10th International Conference on Applied Energy. 10.1016/j.egypro.2019.01.771

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Wenzheng Li et al. / Energy Procedia 158 (2019) 4441–4446 W. Li, X. Zhuang, X. Xu/ Energy Procedia 00 (2018) 000–000

which can support fast acceleration and long driving mileage. The lifetime and performance of Li-ion batteries are significantly influenced by the operating temperature. However, a large amount of heat can be generated in EVs with frequent charge and discharge cycles due to chemical reactions and ohmic resistance [2]. An operating temperature in the range of -20 and 60 oC is required for Li-ion batteries to avoid temperature-related degradation and possible thermal runaway [3]. Moreover, the temperature difference between individual cells and modules in a pack is required to be less than 5 oC [4]. Therefore, the battery thermal management system (BTMS) is necessary to effectively and efficiently remove the excessive heat from the batteries. Three major cooling techniques for Li-ion batteries are air cooling, liquid cooling and phase change material (PCM) cooling. Air cooling and liquid cooling are more commercially matured than PCM cooling. Although air cooling has advantages including low cost, weight, complexity and ease to maintain, it is not suitable for batteries working in abuse conditions such as high discharging rate or ambient temperature due to the low thermal conductivity of air [5]. For air cooling of prismatic pouch Li-ion batteries, Park [6] numerically compared the performance of BTMSs with traditional U-shape and Z-shape designs of ducts. Fan et al. [7] numerically studied the effects of gap spacing and air flow rate on the thermal management of an air-cooled module contain eight prismatic Li-ion cells operating under an aggressive driving profile. It was found that the temperature rise of the batteries can be reduced by lowering the gas spacing or increasing the air flow rate. A trade-off is required to achieve the satisfied cooling performance at acceptable fan power consumption. Recently, fins [8] and metal foams [9,10] were embedded into the flow channels in order to enhance heat transfer. For liquid cooling, Lan et al. [11] proposed a new BTMS design with minichannel aluminum tubes twisting around a 55 Ah single Li-ion battery. Heat generation rate of the battery is 7.6 W. Water at 27 oC flows inside the minichannels at 3.3 g/s to cool down the battery. Numerical results show that the maximum temperature of 27.8 oC and temperature difference of only 0.8 oC can be achieved at a discharge rate of 1 C. Zhang et al. [12] further experimentally verified the cooling performance of such a BTMS design for a battery pack. A sheet of flexible graphite was inserted between the cell wall and the tubes in order to enhance heat transfer. Experimental results indicate that great battery cooling performance was achieved and the temperature difference between cells in the pack was below 5 oC. Another commonly used design concept is to inserting a cold plate with straight minichannels into neighboring prismatic cells. Huo et al. [13] and Qian et al. [14] conducted the parametric analysis of the number of channels, flow direction, and water velocity in such designs. Most of the previous research on liquid cooling of prismatic battery modules assumed the coolant water entering each cold plate was uniform. However, the structure to ensure uniform distribution of water in separate cold plates is usually not discussed. Moreover, most of the studied liquid cooling BTMS is not modular design. The present study proposed a novel modular designed liquid cooling BTMS including the coolant water distribution structure. Numerical method was employed to investigate its cooling performance for a module consisting of 15 large capacity (70 Ah) batteries at ambient temperature of 40 oC. The total heat generation rate of each battery is around 15.5 W. 2. Methodology 2.1. Battery modeling Fig 1(a) shows the simplified model of the studies 70 Ah prismatic lithium iron phosphate battery. Fig 1(b) shows the structure of the battery. Table 1 lists all the necessary parameters of each component in the lithium iron phosphate battery. Heat generated within the battery during the discharging process consists of the heat originated from the battery kernel and the heat produced by the terminals. Bernardi et al. [15] proposed a formula which is widely used to calculate the heat generation in the kernel as shown in Eq. (1). dUOC  I  (1)  qk  IRr  T  Vk  dT  where qk is the volumetric heat generation rate of the battery kernel, W/m3; Vk is the volume of the battery kernel, m3; I is the discharging current, A; Rr is the internal resistance, Ω; T is the temperature, K; and dUOC/dT is a coefficient which is empirically taken as -0.5 mV/K. The Joule heat generation heat originated from the terminal is calculated by the following equation,



Wenzheng Li/etEnergy al. / Energy Procedia 158 (2019) 4441–4446 Author name Procedia 00 (2018) 000–000

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I 2 Rt (2) Vt where qt is the volumetric heat generation rate of the battery terminal, W/m3; Rt is the resistance of the terminal, Ω; Vt is the volume of the terminal, m3. The overall effective thermal capacity of the battery is calculated based on the equation as follows,  i CP,iVi (3)  CP  Vi qt 

where i denotes each part of the battery as shown in Fig 1(b); ρ is the density, kg/m3; Cp is the specific heat, J/(kg.K); V is the volume, m3. The thermal conductivity of the battery is anisotropic because the battery is stacked by components with different thermal properties. The battery thermal conductivity in the in-plane direction and through-plane direction are calculated by Eq. (4) and (5), respectively.  i Li (4) =  Li

 =

L L 

i

(5)

i

i

Where L is the thickness of each component, μm; λ is the thermal conductivity, W/(m.K).

Fig. 1. (a) The simplified model of the studied battery; (b) the structure of the studied battery; and (c) the numerically calculated temperature distribution in different planes at 40 oC ambient temperature Table 1. Parameters of different components in the studied battery. PO4 phosphate

Graphite

Diaphragm

Copper foil

Aluminum foil

Thickness, μm

19.9

21.6

3.46

1.3

1.3

Thermal conductivity, W/(m.K)

1.48

1.04

0.38

398

238

Density, kg/m

1200

2500

960

8900

2700

Specific heat, J/(kg.K)

3500

710

2100

390

880

3

2.2. BTMS design Fig 1(c) indicates that the battery temperature can reach 63 oC in the absence of a battery thermal management system (BTMS). The temperature can be even higher if multiple batteries forming a module. In order to keep the highest temperature in a module below 35 oC, and maintain the difference between the highest and lowest temperature in the module less than 5 oC, a novel liquid cooling BTMS as shown in Fig 2 was proposed. A cooling plate with four straight channels is inserted in two adjacent batteries. Water flows through the channels in opposite

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directions at the two sides of a battery. A water distribution structure is put on top of the module in order to uniformly distribute the water into each cooling plate equally. The cooling water converges into one channel at the bottom of each plate and then is collected by a tube placed outside of the module.

Fig. 2. (a) Oblique view, and (b) top view of the novel BTMS for 7 batteries

2.3. CFD setting The 3D models were created in Solidworks and then imported into ICEM for meshing. UDF was compiled into Fluent to define the heat generation rate. The QUICK scheme was used to solve the convection terms in the convection-diffusion equation. The SIMPLE scheme was employed to solve the pressure-velocity coupling. Natural convection with the heat transfer coefficient of 3.9 W/m2.K was set for the surfaces exposed to the ambient. The ambient temperature was set at 40 oC. The grid number of 20,776 was selected for one battery after grid independence tests. 3. Results and discussion 3.1. Cooling of the battery module Fig 3 shows the temperature distribution of the battery module at 1 C discharging rate with the water flow rate of 1 g/s. Temperature of the cooling water at the inlet was set as 30 oC. The results indicate that the highest temperature in the module was cooled down below 37 oC. Two batteries at the ends of the modules have relatively lower temperature than the other batteries.

Fig. 3. Temperature distribution of the module at 1 C with the water flow rate of 1 g/s and inlet temperature of 30 oC

Fig 4 compares the average temperature in the A-A plane of each battery in the module with the water flow rate of 1 g/s at different water inlet temperatures. The discharging rate is also 1 C. The results show that the average



Wenzheng Li et al. / Energy Procedia 158 (2019) 4441–4446 Author name / Energy Procedia 00 (2018) 000–000

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temperature in the A-A cross section of each battery in the module is significantly influenced by the water inlet temperature. The average temperature in the battery is still higher than 36 oC when the water inlet temperature is 30 o C. However, the average temperature decreases to below 35 oC if the water inlet temperature is kept at 28 oC. Although the ambient temperature is 40 oC, it is still feasible to achieve the water inlet temperature of 28 oC with air conditioning. Fig 4 also indicates that the variation of batteries’ average temperatures is in a small range of 0.5 oC, which suggests that great temperature uniformity is obtained with the novel BTMS design. However, the temperature variation inside one single cell also needs to be considered. Fig 5 shows the difference of the highest and the lowest temperatures in each battery of the module at different cross sections with the water flow rate of 1 g/s and inlet temperature of 30 oC. The discharging rate is kept at 1 C. The results indicate that the temperature difference in each battery is the maximum in the C-C cross section. Because the surfaces adjacent to the cooling plate have the lowest temperature and the A-A plane in the centre of each battery has the highest temperature. However, the maximum temperature difference in the C-C cross section is still within 2 oC. The temperature difference in all the cross sections becomes smaller as the inlet water temperature decreases from 30 to 26 oC. Therefore the temperature distribution uniformity satisfactorily meets the cooling requirements of the BTMS for the battery module.

Fig. 4. Average temperature in the A-A plane at 1 C with the water flow rate of 1 g/s and various inlet temperatures

Fig. 5. Temperature difference at 1 C with the water flow rate of 1 g/s and inlet temperature of 30 oC

Fig 6 indicates the effect of the water flow rate on the average temperature of each battery in the module. The discharging rate is 1 C, and the ambient temperature is 40 oC. The inlet water temperature is set as 30 oC and the flow rate varies between 0.3 and 5 g/s. It can be seen that the average temperature in the A-A cross section decreases and the temperature difference between batteries decreases as the water flow rate increases. However, the average temperature in each battery is still higher than 35 oC even the water flow rate increases to 5 g/s. Therefore, it can draw the conclusion that the effect of the water flow rate on the battery temperature is far less significant than that of the water inlet temperature. The water inlet temperature has to be maintained below 28 oC in order to cool the temperature of batteries in the module down to 35 oC.

Fig. 6. Average temperature in the A-A plane at 1 C with the inlet water temperature of 30 oC at various flow rates

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4. Conclusions The performance of a novel modular water cooling BTMS was numerically investigated for a module consisting of 15 large capacity (70 Ah) prismatic lithium iron phosphate batteries at 1 C discharging rate. The average battery temperature and temperature variation were compared at different water inlet temperature and water flow rate. The results show that both the average temperature and the temperature variation inside a battery or between batteries in the module decrease as the water inlet temperature decreases or the water flow rate increases. However, the effect of the flow rate on temperature is far less significant than the water inlet temperature. When the water inlet temperature is 28 oC and the flow rate is 1 g/s, the average temperature around 34.5 oC and temperature difference within each battery less than 1.8 oC can be obtained. In this case, the temperature variation between individual batteries in the module is less than 0.5 oC. The proposed BTMS shows great cooling performance for batteries with relatively high heat generation rate at small water flow rate and moderate water inlet temperature. Acknowledgements Support from Shenzhen Peacock Plan and Shenzhen Key Lab Fund of Mechanisms and Control in Aerospace (ZDSYS201703031002066) is gratefully acknowledged. References [1] Campanari S, Manzolini G, Iglesia FG. Energy analysis of electric vehicles using batteries or fuel cells through well-to-wheel driving cycle simulations. Journal of Power Sources 2009; 186: 464-477. [2] Liu R, Chen J, Xun J, Jiao K, Du Q. Numerical investigation of thermal behaviors in lithium-ion battery stack discharge. Applied Energy 2014; 132:288-297. [3] Väyrynen A, Salminen J. Lithium ion battery production. The Journal of Chemical Thermodynamics 2012; 46: 80-85. [4] Pesaran AA. Battery thermal models for hybrid vehicle simulations. Journal of Power Sources 2002; 110: 377-382. [5] Liu H, Wei Z, He W, Zhao J. Thermal issues about Li-ion batteries and recent progress in battery thermal management systems: A review. Energy Conversion and Management 2017; 150: 304-330. [6] Park H. A design of air flow configuration for cooling lithium ion battery in hybrid electric vehicles. Journal of Power Sources 2013; 239: 30-36. [7] Fan L, Khodadadi JM, Pesaran AA. A parametric study on thermal management of an air-cooled lithium-ion battery module for plug-in hybrid electric vehicles. Journal of Power Sources 2013; 238: 301-312. [8] Mohammadian SK, Zhang Y. Thermal management optimization of an air-cooled Li-ion battery module using pin-fin heat sinks for hybrid electric vehicles. Journal of Power Sources 2015; 273: 431-439. [9] Mohammadian SK, Zhang Y. Cumulative effects of using pin fin heat sink and porous metal foam on thermal management of lithium-ion batteries. Applied Thermal Engineering 2017; 118: 375-384. [10] Saw LH, Ye Y, Yew MC, Chong WT, Yew MK, Ng TC. Computational fluid dynamics simulation on open cell aluminum foams for Li-ion battery cooling system. Applied Energy 2017; 204: 1489-1499. [11] Lan C, Xu J, Qiao Y, Ma Y. Thermal management for high power lithium-ion battery by minichannel aluminum tubes. Applied Thermal Engineering 2016; 101: 284-292. [12] Zhang T, Gao Q, Wang G, Gu Y, Wang Y, Bao W, Zhang D. Investigation on the promotion of temperature uniformity for the designed battery pack with liquid flow in cooling process. Applied Thermal Engineering 2017; 116: 655-662. [13] Huo Y, Rao Z, Liu X, Zhao J. Investigation of power battery thermal management by using mini-channel cold plate. Energy Conversion and Management 2015; 89: 387-395. [14] Qian Z, Li Y, Rao Z. Thermal performance of lithium-ion battery thermal management system by using mini-channel cooling. Energy Conversion and Management 2016; 126: 622-631. [15] Bernardi D, Pawlikowski E, Newman J. A general energy balance for battery systems. Journal of The Electrochemical Society 1985; 132: 512.