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Battery Pack DesignMVKF25-vt17
Mechanical and electrical layout, Thermal modeling, Battery management
25-27/4
Avo Reinap, IEA/LU
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Goals• Design and dimensioning of battery pack
based on suitable models– evaluate suitable battery technologies, specify cell
and packing, electric and thermal termination– battery development and energy management
systems, predict state of charge, health, function, ..– test battery compatibility to operating conditions,
current waveforms
Ageing model Thermal model
Electrical model
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Background A
• Vehicular application– Electrification improves energy
usage – hybrids• use ICE at 35% instead of 10-
20% efficiency• Reuse deceleration energy for
acceleration– Pure renewable fuel/energy
• System view– Charging, static vs dynamic– Compatability, AC current loading
Avo R 3
Battery and Propulsion
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Background B
• Part-III Battery usage– Pack design (Ch5) – Management (Ch6)– State and degradation (Ch7)
• Part-I & II Li-ion battery technology– Cell components (Ch1)– Cell materials (Ch3)– Cell design (Ch4)
Avo R 4
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Background C
• Electrical machine design• Directly air-cooled cooled
laminated machine windings• Indirect oil-cooled stator-core
and end-turns• Enhanced winding thermal
conductivity
Fig.Ref.: EDPC’14, EDPC’15
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Content
• Design– path from topology
sketching to practical realization
• Cell, Module, Pack/Bank• Battery = Energy storage
[Wh] & Power supply [W]– Applications: Vehicle/Grid– Technologies: Li-ion
• Battery cell– Geometries and dimensions– Characteristics and
properties
• Cell “virtual” packing• Electro-Thermal models• Packing examples• Thermal design
– Cells, modules, backs• Battery Management System
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Design
• A cross-road of different disciplines• Multi-dimensional (analysis) & multi-objective (synthesis)• ..
Construction Production
Energy Conversion
kg kW, kWh
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Specific energy and power
• Specific energy originates from material chemistry
– Capacity capability
• Specific power is related to material physics and production
– Internal power losses and thermal constrains – durability and safety
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Value chain for EV batteries
• From cell realization to recycling (excluding raw materials)• Vehicle power (performance), energy (range) and integration (BMS)
Fig.Ref.: B. Averill, P. Eldredge, “General Chemistry: Principles, Patterns and Applications”
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Lithium-ion batteries:How do they work?
https://www.youtube.com/watch?v=2PjyJhe7Q1g
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Electrochemical cell
• Chemical reaction = two half-reactions: oxidation+reduction=redox– Side reactions due to thermal loads, pressure?
• Active, electrodes, non-active, the rest including electrolyte, components
B. Averill, P. Eldredge, “General Chemistry: Principles, Patterns and Applications”
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Lithium Battery Technologies
• Optimal performance and lifetime capacity
• Case sensitive: application vs cell configuration
Abbr Wh/kgLithium cobalt oxide LiCoO2 LCOLithium manganese oxide LiMn204 LMO 4.0V 114-159 Lithium iron phosphate LiFePO4 LFP 3.2V 114-138Lithium nickel manganese cobalt oxide LiNiMnCo02 NMC 3.7V 93-171Lithium nickel manganese aluminum oxide LiNiCoAlO2 NCALithium titanate Li4Ti5O12 LTO
R. Purkayastha, R.M. McMeeking, "A Linearized Model for Lithium Ion Batteries and Maps for their Performance and Failure" ASME
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Cell material properties example
material Thickness [μm]
Thermal conductivity
[W/mK]
Electrical conductivity
[S/m]+ I collector aluminum 20 238 37.8e6+ Electrode 106 1.58 (wet) 13.9 (wet)Electrolyte wetSeparator 25 0.34 (wet)- Electrode 111 1.04 (wet) 100 (wet)- I collector copper 14 398 59.6e6
case 162 0.16
M. Yazdanpour, “A circuit-based approach for electro-thermal modeling of Lithium-Ion batteries”
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Thermal management system• Historic usage affects availability of
energy and power in future– BMS = preferred and “optimized”
usage– BTMS includes temperature control
• Purpose of BTMS– Maintain operational temperature– Assure temperature uniformity
• Challenges– Temperature increase at high power
load– Heat-up time in prior to start-up
Avo R 14
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Battery performance degradation
• Degradation – deterioration of useful capacity and power capabilities
• Identification of physical and chemical processes behind degradation mechanisms . Origins related to technology and usage.
• SoH – state of health remaining capacity due to ageing
http://epg.eng.ox.ac.uk/content/degradation-lithium-ion-batteries
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Battery failure
• Safety=thermal stability– BTMS is very important for
performance and safety
• Failure mechanisms– External/internal – internal short
circuits– Mechanical, electrical, thermal
– abusive conditions
• Failure propagation from cell to module and pack
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Thermal runaway
• Rapid temperature increase– Most likely due to internal
spontaneous short circuits due to impurities (that can grow during time as side effect of chemical reactions)
• Avoid thermal runaway– Overcharge/discharge protection
activated by over pressure– Current interrupt device (CID)– Positive temperature coefficient
(PTC) – Separator specified for PTC & CID,
layered separators for reducing internal short circuits
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Question 1.1
Avo R 18
• What are the criteria for the design of suitable thermal management system for a battery back?– Battery (cell) design? – Parameters related to heating?– Factors influencing the heat transport and
dissipation?
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Battery modelling A
Avo R 19
• Simple approach @ limited data• Cell voltage U=Eo-RoI where Ro is internal resistance
and Eo is open circuit voltage (OCV) – Ignoring that Eo and Ro depends on SoC and temperature
• Heating power Q=(RoI)2 only Ohmic losses– Ignoring reversible heat loss, Ro depends on SoC and
temperature
• Transient temperature rise T=QRh(1-e-t/RhCh)– Thermal properties are not an easy target!
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Equivalent circuit relations
Relation Electrical circuit
Magnetic circuit
Thermal circuit
Cooling circuit
Potential U=E·l N·I=H·l =G·l P=·l
Flow I=J·A Φ=B·A Q=q·A Q=v·A
Conductive element
G=γ·A/l
G=μ·A/l G=λ·A/l G=·A/l
Ohm’s Law U=I·R N·I=Φ·R =Q·R P=Q·R
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Battery modelling B
• Depth of discharge DoD 0 1 max(Ucell) min(Ucell)
• Inner voltage source (OCV) E(DoD)=Ucell(I,DoD)Rdch(DoD)*I
• Charge Rch and discharge Rdchresistors depends only on DoD
– Usually Eo and Ro available– Also ∆U and ∆T
Avo R 21
Ageing model
Electrical model
current Thermal model
power
temperaturevoltage
DoD SoH
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Cell construction• Electrode arrangement: spiral
wound jelly roll, stacked electrodes, bobbin type
• Geometry: Cylindrical, Prismatic, Pouch, Button
• Components– Case: plastic (PET) or metallic
(steel, Al)– Core=active components
+collectors, separator– Terminals
www.toray-eng.com
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18650 Li-ion
• Standard (size) cylindrical Li-ion cells ø18h65mm
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Prismatic Cells
• Some cell producers– Hitachi, Samsung-SDI,
Panasonic (Sanyo)
Prismatic cell L, [mm] W, [mm] T, [mm] M, [kg] U, [V] C,[Ah] p, [W/kg] c, [Wh/kg]
Hitatchi-1 148 91 26.5 0.72 3.6 28 2300 140SDI-1 37SDI-2 60SDI-3 94
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Kokam’s SLPB cell
• SLPB – Superior Lithium Polymer Battery
• Pouch type improved heat dissipation due to larger surfaces
• Example 240Ah 4.8kg cell– Pheat=1.1kW @ 480A– Acool=2x0.15 m2
– V=46.2x32.7x1.58 cm
Kokam.com
0 500 1000 1500 2000 250060
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SLPB160460330
specific power, pcell [W/kg]
spec
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ener
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cell [W
h/kg
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Kokam large cells
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Overview of cell producers for xEVs
• It is easier to find producer than product ;)
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Battery back sizing
• Number of series connected cells in strings– Ns=Udc/Ucell
• Number of parallel connected strings– Np=Energy/(Ns*[Wh/kg]*[kg])– Np=Energy/(Ucell*”cell capacity”)
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Calculation example
• Ch4 – Cell data• Ch5 – EV and HEV spec
– 300 V * 100 A– Pmax = 2*30kW– P/E ratio 2 and 20
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Specification list
LinkSource Sink
• Forced heating/cooling for battery back– Concepts, topologies, realization ideas, …
• Battery cell – Construction, properties, heat sources, thermal loads, …
• Heat conductor– Thermal accessibility, thermal contacts, …
• Cooling plate– Realisation, performance, …
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Question 1.2
Avo R BTMS 30
• Battery pack specification– Power demand?– Capacity?– Weight or size?
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Thermal design
• Methods, models, calculation examples for thermal design• Practical realisation examples from some car manufacturers
Heat
Electricity
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Thermal modelling
LinkSource Sink
• Models 1D, 2D, 3D analytic or numeric– Computation time vs accuracy, …
• Single cell, a module of cells, battery back – Specification of equivalent cell volume with specific losses, …
• Assembling, heat transport and temperature distribution– Mechanical assembly and thermal accessibility, thermal contacts
• Integration of active cooling circuits– Realisation, estimation of coolant flow and performance, …
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Thermal integration
• Direct cooling where it is most needed in order to minimize heat transport through the solids that causes interior temperature rise and uneven temperature distribution
• Consider the effects of thermal cycling and expansion
• Experiences from other electric drive components
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Thermal design simplifies control and BMS
• Cells (EL+Chemi) – modules (Heat) – battery pack (Duty)
• Battery thermal management – Keep temperature & use
little energy for operation– Keep it Simple is the rule of
the day • Prototype development and
prototyping supported buy models– CAD (SW) – components
and parts (Ansys or Comsol – fluids and solids) – system (Simulink/Matlab)
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cell Rcell surf
Ccell P
fluidRlink
Thermal model
• representing physical reality (?)• Main focus on only on reasonable
cell surface temperature surf as cell is remains unknown (?)
– surf = fluid + R*P• Thermal resistances: simplifications
vs idealisation• Practical realization for fluid
dynamics• Thermography for rapid thermal
assessment influidoutfluid
h
cellcell
cellsurf
cellcell
cPQ
CRCP
dtd
,,
1
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Model library
• Impedance based equivalent circuit models, dynamic experiment based
• Physics and chemistry-based models relay on model parameterisation and properties
• Energy or power-flow models are typically used on a system level
• Empirical models black box models suitable for control not design
Avo R 36
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Cell library
• Selected cell examples: cylindrical, prismatic, pouch
• This information is used for virtual packing and rough estimation on temperature rise and distribution
Manufacturer configuration Geometry Voltage Capacity Specific power Weight
[mm] [V] [Ah] [W/kg] [g]Panasonic Cylindrical Ø18.5x65.3 3.6 3.2 120 48.5
Hitatchi Prismatic 148x91x26.5 3.6 28 2300 720Kokam Pouch 462x327x15.8 3.6 240 360 4780
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Cell “virtual” packing
• For 300V there is need of 84series connected 3.6V cells
• First draft of 148x26.5 mm prismatic cell arrangement where 5 mm distance is left between the rows and groups of 7 cells
• First draft of ø18 mm 4 parallel cylindrical cell arrangement with cooling channel in between the cells
• Not only visualization but a parameterized model with coupling to finite element analysis (FEA)
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Electric connection of cells
• Series-parallel connections• Connection-bars and cables
are part of heat generation but also distribution
• Nickel plate + spot welding = healthy low resistance connections
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Estimation of thermal conductivity
• Equivalent thermal conductivity of a coil is given by the filling factor of the conductor foil (copper in this example) and the thermal conductivity of the medium between the conductor foils
• jelly-roll:12% Al+Cu λ>200W/mK, 6% eparator λ<0.35W/mK, rest λ~1W/mK
• Across coil or roll λ~1W/mK, along λ>>1W/mK
inscond
fcondfins
ins
f
cond
f
eff
kkLkLkLL
11
fcondfins
inscondeff kk
1
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Using 2D FE for sketching• FEMM electromagnetism,
heat transfer, electric currents
• Easy to use, library of Matlabfunctions– Drawing the endpoints of the lines
and arc segments for a region,– Connecting the endpoints with
either line segments or arcsegments to complete the region,
– Defining material properties and mesh sizing for each region,
– Specifying boundary conditionson the outer edges of the geometry.
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Battery pack with cylindrical cells• “Empty” space between cells• Cross-flow through battery
module– Narrow spacing – expectedly no
cooling– Large spacing for sake of better
cooling is often considered impractical
• CFD vs “fast” design approaches
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Battery back with prismatic cells
• Temperature homogenization analysis• Analysis of thermal runaway
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Battery pack with pouch cells
• Coupled electro-thermal FE+model order reduction (MOR) simulation compared to thermographic images
– A reduced order model (ROM) based on singular value decomposition (SVD)
• Direct air-cooled Li-ion pouch battery cell in order to improve the understanding (modelling) and practical realization of battery module
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Vehicular application
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Chevy 104kW 20kWh
• GM Volt and Spark EV use thin prismatic shaped cooling plates in between the cells with the liquid coolant circulating thru the plate.
• The Volt cooling scheme is very effective from a cooling point of view but it is complicated. The cells are encased in multiple plastic frames
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Tesla S 285kW 70kWh
• Tesla snakes a flattened cooling tube thru their cylindrical cells resulting in a very simple cooling scheme with very few points for leakage.
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BWM i3 125kW 21-33kWh
• The BMW i3 cools the bottom of the battery case with refrigerant eliminating the liquid coolant entirely.
• New energy dense lithium ion cells (50% more)
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Integration example by BMW
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Integration example by Tesla
• 60kWh, 352V, 14 modules, 6216 cells in groups of 74=6x14• 85kWh, 402V, 16 modules, 7104 cells
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Integration example by Tesla
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Accommodation of cylindrical cells
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• Single stage heat transfer insufficient hA vs UA
Cool-plate and coolant
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CoolantAir H2 C02 H20 Tr Oil
, degC 20 120 20 120 20 120 20 120 20 120c, kJ/kgK 1.00 1.01 14.2 14.5 0.85 0.94 4.19 4.25 1.71 2.11, kg/m3 1.20 0.89 0.08 0.06 1.83 1.36 999 946 879 816λ,mW/mK 26 33 178 227 16 24 594 686 111 102, uPas 18 23 8 11 14 19 1000 200
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Conjugate heat transfer• The character of flow is
described by Reinolds number,
• the heat transfer is expressed by Nusselt number
• and the coolant is described by Prandtl number
• The hydraulic diameter is related to the geometric layout of the cooling channel
hin
h DAQvD
1Re
bulkwall
hh k
qDDkhNu
kcpPr
perimeterareaDh
4
dcool
dcond
L Lh
out in
win
cQPcool
cool
heat
hAP
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Heat transfer mapping
• Driving parameters for cooling P=f(out,Q) at in
• Flow (Re) and coolant (Pr) characterization
• Heat transfer – correlations (Nu) and – coefficient h
• Wall and winding temperature• Pressure across cooling channel
– Power for supply• Expected cooling power
P=f(w,Q) at in
0 100 200 300 400 500 600 700 800 900 100020
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flow rate, Q [L/min]
outle
t tem
pera
ture
, ou
t [ C
]
Cooling power, p=cpQ(out-in) [W]
0 100 200 300 400 500 600 700 800 900 100020
40
60
80
100
120
140
160
180
200
220
200
200
200
400
400
400
600
600
600
800
800
800
1000
1000
1000
1200
1200
1200
1400
1400
1600
flow rate, Q [L/min]
outle
t tem
pera
ture
, ou
t [ C
]
Reynolds number, Re=2dhQ/(A) [-]
0 100 200 300 400 500 600 700 800 900 100020
40
60
80
100
120
140
160
180
200
220
6.6
6.6
6.6
6.8
6.8
6.8
7
7
77.
2
7.2
7.2
7.4
7.4
7.4
7.6
7.6
7.6
7.8
7.8
7.8
8
8
8
8.2
8.2
8.48.6
flow rate, Q [L/min]
outle
t tem
pera
ture
, ou
t [ C
]
Nusselts number, Nu=f(Re,Pr) [-]
0 100 200 300 400 500 600 700 800 900 100020
40
60
80
100
120
140
160
180
200
220
340
360
360
360
380
380
380
380
400
400
400
400
420
420
420
440
flow rate, Q [L/min]
outle
t tem
pera
ture
, ou
t [ C
]
Heat transfer coefficient, h=Nu k/Dh [W/(m2K)]
0 100 200 300 400 500 600 700 800 900 100020
40
60
80
100
120
140
160
180
200
220
20
20
2020
40
40
40
40
60
60
60
80
80
80
100
100
120
120
140
160flow rate, Q [L/min]
outle
t tem
pera
ture
, ou
t [ C
]
Temperature across boundary, Pcool/(hAcool) [C]
0 100 200 300 400 500 600 700 800 900 100020
40
60
80
100
120
140
160
180
200
220
20002000
40004000
60006000
8000
8000
800010000
10000
12000
1200014000
flow rate, Q [L/min]
outle
t tem
pera
ture
, ou
t [ C
]
Pressure drop, dP [Pa]
0 100 200 300 400 500 600 700 800 900 100020
40
60
80
100
120
140
160
180
200
220
5050
50
100100
100
150150
150
200200
flow rate, Q [L/min]
outle
t tem
pera
ture
, ou
t [ C
]
Ideal cooling supply power, dPQ [-]
0 100 200 300 400 500 600 700 800 900 10000
50
100
150
200
250
100
100100 100
300
300
300300
500
500
500
700
700
700
900
900
900
1100
1100
1300
1300
1500
flow rate, Q [L/min]
wal
l tem
pera
ture
, ou
t [ C
]
Cooling power, p=cpQ(out-in) [W]
0 5 10 15 20 25 30 35 40 45 5020
21
22
23
24
25
26
27
28
29
30
flow rate, Q [L/min]
outle
t tem
pera
ture
, ou
t [ C
]
cooling power, p=cpQ(out-in) [W]
10001000
1000
10001000
4000
4000
4000
4000
7000
7000
7000
10000
10000
10000
13000
13000
c=3500J/kgK, =900kg/m3
B. Sundén, “Introduction to Heat transfer”
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Avo R MVKF25-vt17 Battery Pack Design 59Avo R 59
Thermal analysis of cell assembly
• Geometric data– Defined by German standard
DIN 91252
• Heat transfer inside the cell– From cell to module and
pack– Cell = Jelly-roll (heater) +
carrier (assembly)
• Heating power – Worst case P=I2Ro=50W
Hitachi 3.6v 35Ah 0.8mΩ@10A155x27x118 incl terminals 810g
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Avo R MVKF25-vt17 Battery Pack Design 60Avo R 60
Thermal accessibility of a cell
• Available thermal connection areas– Large long sides 2x134cm2
but low thermal conductivity– Sides, lateral sides 2x24cm2
and Bottom side 39cm2
• Bottom and short sides have expectedly better inherit thermal contact
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Avo R MVKF25-vt17 Battery Pack Design 61Avo R 61
Inside a battery cell
• Cell dimensions are known, jelly-roll geometry only guessed• Heat conductivity defined in-plane and cross-plane for whole cell
unit and jelly roll (including heat capacity)• Important part for thermal models are termination and equivalent
jelly-roll
DIN SPEC 91252:2011Lundgren et al 2016
H. Lundgren et al, ”Thermal Management of Large-Format Prismatic Lithium-Ion Battery in PHEV Application”
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Avo R MVKF25-vt17 Battery Pack Design 62
Surface temperature response
• Thermal vs electric power extraction and comparison
• Thermal conductivity– Through-foil
0.95W/mK– Along foil 30.8 W/mK
H. Lundgren et al, ”Thermal Management of Large-Format Prismatic Lithium-Ion Battery in PHEV Application”
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Avo R MVKF25-vt17 Battery Pack Design 63Avo R 63
2D FE over cross-sections
Case Qbase[W]
Qlateral[W]
max[oC]
1 50 0 60
2 33 17 55
3 21 29 44λcell=1 W/mK
λcell=20 W/mK
Qv=140W/dm3, surf=30oC
6054484236
Temperature , [C]
30
2
1
3
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Avo R MVKF25-vt17 Battery Pack Design 64Avo R 64
Observations A
• Battery cell– P=50 W heating, 1/R=0.6 0.5 0.28 K/W, ∆=30 25 14 K
• Heat conductor– Ideal 1/R=0 K/W, ∆=0 K
• Cooling plate– Ideal fluid=wall=surf=30oC
LinkSource Sink
50 W per cell
surf=30oC wall=30oC fluid=30oCcell= surf+Δ
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Avo R MVKF25-vt17 Battery Pack Design 65Avo R 65
Realization A
• Mechanical assembly in “cross” plane direction
• Thermal enhancement both in plane directions– Lateral clamp or forcing plate– Battery to base contact
• ..
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Avo R MVKF25-vt17 Battery Pack Design 66Avo R 66
Cell clamped into heat conductor
Case Qbase[W]
Qlateral[W]
max[oC]
1 34 16 51
2 32 18 54
3 27 23 72
Qv=140W/dm3, surf=30oC
6054484236
Temperature , [C]
30
-0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
length, [m]
heig
ht, [
m]
10μm gap ∆gap=3oC100μm gap ∆gap=21oC
3
2
1
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Avo R MVKF25-vt17 Battery Pack Design 67Avo R 67
Cell linked to cool-plate
Case Qbase[W]
Qlateral[W]
max[oC]
1-30 36 14 53
2-h1 35 15 68
3-h2 35 15 148
Qv=140W/dm3, fluid=25oC
6054484236
Temperature , [C]
30
h1=1000W/Km2 wall ∆wall=15oCh2=200W/Km2 wall ∆wall=95oC
-0.1 -0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08 0.1
-0.02
0
0.02
0.04
0.06
0.08
length, [m]
heig
ht, [
m]
32
1
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Avo R MVKF25-vt17 Battery Pack Design 68Avo R 68
Transient heating
• 5 minutes between the frames (FEMM transient HT)• Hot side of the scale (usually presented in between 20-30oC)• One dominating heat capacitance only
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Avo R MVKF25-vt17 Battery Pack Design 69Avo R 69
Summary
• Battery cell– ∆b=30 25 14 K @ 50W – actual load is lower
• Heat conductor– Insufficient thermal contact 0.1 mm air ∆c=20K @ 50W
• Cooling plate– Insufficient heat transfer h2=200W/Km2 wall ∆wl=95oC
LinkSource Sink
50 W per cell
surf= wall+Δc wall= fluid+Δw fluid=30oCcell= surf+Δb
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Avo R MVKF25-vt17 Battery Pack Design 70
Evaluation of direct forced cooling
• Cooling channel arrangements
• Thermography of heat transients
– 300 A DC– 400-500 L/min
• Location of hot-spots – “turns” of the layer
edges where the cross section is less than 10 mm2
– Edge layer 1 is closest to air-gap
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Avo R MVKF25-vt17 Battery Pack Design 71Avo R 71
Thermal control and management
• ..by thermal design and active cooling• J. Li, Z. Zhu, “Battery Thermal
Management Systems of Electric Vehicles”, MSc Chalmers 2014
• 29.5/17.7 kWh• 1700/270 kg
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Avo R MVKF25-vt17 Battery Pack Design 72Avo R 72
Energy ManagementBattery management system
• Monitoring – measure what is important• Control – keep it optimal and constrained• Diagnosis – keep battery cells healthy
Information
Energy
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Avo R MVKF25-vt17 Battery Pack Design 73
Battery Management System - BMS
• Best and safe use of energy• Voltage U+∆U and temperature
+∆ management: cell balancing or equalizer, check margins
• Charge/discharge– Integration of current – SoC– Power and capacity fade – SoH
Avo R 73
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Avo R MVKF25-vt17 Battery Pack Design 74
Charge and discharge control
• maintain the voltage limits while respecting the current and temperature limits
• LOW Constant current charging followed by voltage and temperature control
• HIGH current for constant voltage charging• Combined CV+CC
Avo R 74
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Avo R MVKF25-vt17 Battery Pack Design 75
Cell balancing
• Voltage equalization, which is to fill up energy and maximize capacity and life by ”removing” unbalanced weak links
• Active/passive –taking/wasting energy
Avo R 75
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Avo R MVKF25-vt17 Battery Pack Design 76
BMS development
• Overall functional safety is better match to global FPGA than to local micro processor units– parallelism for performance with fail-safe logic
Avo R 76
https://www.altera.com/solutions/industry/automotive/applications/electric-vehicles/battery-management-system.html
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Avo R MVKF25-vt17 Battery Pack Design 77
BMS function structure
• I/O, monitoring, decisions and safety relevant funtionsAvo R 77
http://www.avl-functions.de/Battery-Management-S.30.0.html?&L=1Ageing model
Thermal model Electrical model
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Avo R MVKF25-vt17 Battery Pack Design 78
BMS control sequence
• Intelligent batteries due to base functions of a battery management system
Avo R 78
http://mocha-java.uccs.edu/ideate/courses.html
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Avo R MVKF25-vt17 Battery Pack Design 79
BMS basic functions
• Cell protection, charge control, demand management, SoC and SoH determination, cell balancing, authentication and identification, communication – are some objectives for BMS
Avo R 79
http://www.mdpi.com/1996-1073/4/11/1840/htm
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Avo R MVKF25-vt17 Battery Pack Design 80
BMS Scope and Failure Consequences
Avo R BTMS 80
http://www.mpoweruk.com/bms.htm
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Avo R MVKF25-vt17 Battery Pack Design 81
BMS architectures for xEVs
• Communication, reliability and accuracy• Practical attachment, number of components and connections• Few architectures with different features in connections and
communication
Avo R 81
http://www.electronicproducts.com/Power_Products/Batteries_and_Fuel_Cells/Battery_management_architectures_for_HEVs.aspx
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Avo R MVKF25-vt17 Battery Pack Design 82
Practical implementation
• Added intelligence, where and how? Sharing information, history and communication
Avo R 82
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Avo R MVKF25-vt17 Battery Pack Design 83
Multicell Battery Stack Monitor
• Component name LTC6802-1, Up to 12 cells, 13 ms measurement interval, up to 1000V, passive cell balancing
Avo R 83
http://www.linear.com/product/LTC6802-1
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Avo R MVKF25-vt17 Battery Pack Design 84
BMS sensor module
MM9Z1 638 4-Cell Lithium Battery BMS unit•battery stack monitor IC can measure a number of cell voltages and provide for the discharge of individual cells to bring them into balance with the rest of the stack
Avo R 84
http://www.nxp.com/products/automotive-products/energy-power-management/can-transceivers/reference-design-mm9z1-638-4-cell-
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Avo R MVKF25-vt17 Battery Pack Design 85
Some future trends by Bosch
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Avo R MVKF25-vt17 Battery Pack Design 86
Back to Battery modelling
• power_battery, power_pattery_temperature• State of the art model for concept development and
evaluation
Avo R 86
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Avo R MVKF25-vt17 Battery Pack Design 87
Physics coupled equivalent circuits
• Battery equivalent circuit models– Rint model Eo, Ro– First order (adds) R1, C1– Second order (adds) R2, C2
• Impedance model– Electrochemical impedance
spectroscopy (EIS)– Coupled to pfysics (?)
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Avo R MVKF25-vt17 Battery Pack Design 88Avo R 88
Testing batteries
• Electrochemical dynamic response
– Respons is related to ion-current/diffusion rate in the cell
– Slower response for weaker batteries
• Characterization– LF dubbed diffusion– MF charge transfer– HF migration
• Batteries with faded capacity suffer from low charge transfer and slow active Li-ion diffusion.
http://batteryuniversity.com/learn/article/testing_lithium_based_batteries
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Avo R MVKF25-vt17 Battery Pack Design 89
Useful links and Aknowledgement
• mpoweruk.com• Batteryuniversity.com• liionbms.com/php/cells.php
• Aknowledged authors and their results shown on the previous pages (with some links and references)