Week 10 - Simulating Combustion of Natural Gas.
Title :- Heat transfer analysis using ANSYS-FLUENT software for the cylindrical Lithium ion Battery with heat generation boundary condition
Objective :-
- Perform heat transfer analysis by enable the energy equation
- Apply heat generation boundary condition
- Create an enclosure
- Perform mesh independent study and find the most suitable mesh for going further
- Find out the average temp and heat transfer coefficient obtained by the battery
- Visualize the contour plot and analysis the result
Before going in details first we should know about, what is heat transfer analysis and why we do this :- The Heat transfer analysis/simulation type allows the calculation of the temperature distribution and heat flux in solids under thermal loads (for example, convection and radiation). Both steady-state and transient simulations are supported.
We have added some pictures of heat transfer analysis in graphics card(PCB)
Types of heat transfer :
- Radiation : Radiation is the transfer of heat energy through space by electromagnetic radiation.
- Conduction : Conduction is the transfer of heat energy from one substance to another or within a substance.
- Convection : Convection is the transfer of heat energy in a fluid. This type of heating is most commonly seen in the kitchen with a boiling liquid.
INTRODUCTION :-
Battery Thermal Management Systems(BTMS) : The Battery Thermal Management System (BTMS) is the device responsible for managing the heat generated during the electrochemical processes occurring in cells, allowing the battery to operate safely and efficiently. It safeguards both the user and the battery by ensuring that the cell operates within its safe operating parameters. BTMS plays a crucial role in battery pack life and on its overall performance.
Types of batteries used for Electric vehicle cars :
- Lead-acid batteries
- Nickel metal hydride (NiMH) batteries
- Lithium-ion (Li-ion)
In our case we will use Lithoum-ion battery pack in order to perform heat transfer analysis using ANSYS-FLUENT workbench.
Lithium-ion batteries have become widely used in energy storage systems. Since adverse operating temperatures can impact battery performance, efficiency/battery life and safety, achieving a battery thermal management system that can provide a suitable ambient temperature environment for working batteries is important.
Battery cooling : The battery cooling system in electric vehicles regulates the temperature of the battery pack. Many electric cars are capable of being charged at very fast rates with further increases planned for future models. This causes the battery to heat up significantly. High temperatures reduce the lifespan of lithium-ion batteries and very high temperatures increase the risk of thermal runaway.
- Cooling is therefore necessary to reduce the temperature during fast charging or when demand on the battery is high.
- Cooling during charging increases the efficiency of charge transfer and reduces degradation of the battery, allowing the battery to retain capacity over its lifetime so that maximum EV range can be maintained.
- Coolant with 40% ethylene glycol water solution is used to remove heat from the battery pack.
Types of cooling system used in most of the EVs and HEVs cars :
- Phase Change Material (PCM)
- Fin Cooling
- Air Cooling
- Liquid Cooling (both Direct and Indirect)
In our case air has used as the working fluid as coolant for Lithium-ion battery pack system.
Thermal Runaway : Thermal runaway is one of the primary risks related to lithium-ion batteries. Thermal runaway is the condition in which the lithium ion cell enetrs an uncontrollabe state and battery catches fire due to rapid heat propagation from one damaged cell to another cell. When its temperature rises at a rate greater than 20 degrees centigrade per minute, the cell has reached thermal runaway.
Modelling and solving approach
1. Start the anys fluent workbanch
2. First open spaceclaim in ANSYS ,create the circle by selecting the xy plane
3. Pull the one side of the circle and create cylindrical shaped battery
4. Then using 'Pattern' tool under 'Design' create (4*2)the battery pack and create the enclosure
5. Meshing - baseline and refinement (Add inflation layer )and named selection (Inlet ,outlet, fluid domain, batteries, convecton wall)
6. Steady state simulation using viscous K omega (SST) model
7. Creating material in Fluent database (Lithium) and put the value for specific heat, thermal conductivity, density
8. Cell zones condition (material for batteries = lithium)
9. Enable source terms for battery
10. Hybrid initialization
11. Run Fluent solver
12. Post-processign and animation plots
Pre-processing
1. Open spaceclaim `implies`select xy plane
2. Go to sketch and create the circle of 18 diameter then pull the one side of the circle upto 65 mm in order to create a cylindrical shaped battery
3. Go to 'design'`implies`'pattern' and create (4*2) battery pack by making distance as 2 mm between two batteries .
4. Now create the Enclosure and enable the share topology under prepare tool. Make sure to disable the 'preserve instances' under 'Structure' while using share topology.
Go to 'design'`implies`'pattern' and create (4*2) battery pack by making distance as 2 mm between two batteries .
Now create the Enclosure and enable the share topology under prepare tool.
Meshing
- Open the meshing console.
- Click on the mesh and select generate mesh option.
- Now a basic mesh pattern will be created.
- Now we will run a baseline mesh having default size . We go to mesh size and put the desired value>> click on generate mesh tab.
- Now on the next step we will refine the mesh size by decreasing the element size to get the more accurate result .
Setting up physics
Solver type - Pressure Based
Energy on as heat transfer analysis has been performrd here.
K -omega SST model is used here as it will give more accurate result in our case .
Solver - Steady state
K -omega Standard model is used here as it will give more accurate result in our case .
We have created the material ( Lithium ) and as it is not available in fluent databese we have added the value manually fot this.
Creating material (Lithium)
Density = 2700 kg/m^3
Specific heat= 900 J/kg K
Thermal conductivity = 7.14 W/mK
Aluminium has used in convection wall
Air as the working fluid through inlet
5 W/m^2K as Heat transfer coefficient in convection wall has used.
Enable source terms for battery
Case 1 (Default mesh , Inlet velocity - 5m/s, Distance between the batteries - 2mm)
Meshing
Element size = 8.481 mm
Number of total elements = 164415
Skewness :
Skewness is measured by quantifying the deviation from the ideal shaped. And acceptable range is 0 to 0.5.
In our case it is 0.239 in average .
Aspect ratio : We know that ratio between largest and smallest edge of an element is known as Aspect ratio.
In general Aspect ratio are maintained between 1 to 5 .
Named selection
inlet
outlet
convection wall
batteries
fluid domain
Reuslt
Residual plot
Temperature plot for batteries
Temperature contour on xy plane
Velocity contour on xy plane
Case 2 (Refine mesh , Inlet velocity - 5m/s, Distance between the batteries - 2mm)
Element size = 2.5 mm
Number of total elements = 358756
Skewness : 0.23 in average in our case. This is very good .
Element quality : In general for good mesh it is lying between 0 to 1.
In our case it is around 0.75 in average.
Inflation has used to make sure the transfer of heat smoothly between the batteries and the surfaces .
Residual plot
Temperature graph of batteries
Temperature contour on xy plane
Velocity contour on xy plane
Velocity vector
Animation of velocity vector and temp
Observation from this two cases :
Observation from this two cases :
1. In two cases the difference of the average temperature of batteries is very small around 3 K . And also if we look at the temperature contour, temperature distribution is good in compare to the default mesh .
2. So, we will go ahead with refine mesh with 2.5 mm mesh size for further cases and run the simulation by varying the velocity 3m/s , 5m/s and 10m/s with 2mm distance between the batteries.
Case 3 (Refine mesh , Inlet velocity - 3m/s, Distance between the batteries - 2mm)
Result
Temperature contour on xy plane
Temperature contour of batteries
Velocity contour
Velocity Vector
Case 4 (Refine mesh , Inlet velocity - 10m/s, Distance between the batteries - 2mm)
Result
Residual plot
Temperature plot
Temperature contour on xy plane
Temperature contour of batteries
Velocity contour
Velocity Vector
Observation from case 2, case 3 and case 4 : -
We know from the review of the literature that generally the acceptable temperature region for Lithium-ion battery is 253 K to 333 K. Very low temperature can produce a reduction in the energy capabilities of lithium-ion batteries. And also high ambient temperatures can contribute to a high internal temperature of the battery----which can also decrease the perfromance and power capabilities .
Conclusion : So, by considering all of the statement , battery temperature , contour plot we can go ahead with 10 m/s inlet velocity and 2 mm distance between the batteries as the average tempeature for the case 4 (323.68 K is lying between 253K - 333 K ranges ) is moderate. It will give good performance of the battery with power capabilities.
Case 5 (Refine mesh , Inlet velocity - 10m/s, Distance between the batteries - 4 mm)
Geometry
Residual plot
Temperature plot
Temperature contour
Temperatour con of batteries wall
Velocity contour
Velocity vector
Case 6 (Refine mesh , Inlet velocity - 10m/s, Distance between the batteries - 6 mm)
Geometry
Residual plot
Temperature plot
Temperature contour
Temperatour con of batteries wall
Velocity contour
Velocity vector
Observation from case 4, 5 and 6 :
Conclusion :-
- We can say from by observing the graph and contour plot that with increasing of the distance between the batteries the average temperature of batteries are decreasing by flowing the fluid through inlet with constant velocity.
- Velocity at the upper part of the battery pack from where we are flowing the fluid are highest and the temperature of the battery lowest due to the high velocity of the fluid.
- Also we can observe that for case 5 and case 6 the average temperature of the batteries are almost same. So, we can come to this conclusion that case 5 ( Distance of the battery = 4 mm and inlet velocity = 10 m/s ) is the ideal case.
- So. distance 4 between the batteres is the optimlal distance for the lithium ion battery pack.
Now we will run the same case in transient simulation to see the difference in result for steady and transient cases.
Case 7(Refine mesh , Inlet velocity - 10m/s, Distance between the batteries - 6 mm)
(Transient simulation)
Residual plot
Temperature plot
Temperature contour
Velocity contour
Velocity vector
Observation from case 6 and case 7 :
Observation :
- We are getting low temperature in transient simulation in compare to steady state simulation for same inlet velocity and distance between the batteries.
- So, in order to visualize the contour plot , velocity plot and to get the optimal result transient simulation is better compare to steady state simulation.
References : -
https://cfdflowengineering.com/battery-cooling-techniques-in-electric-vehicle/
https://cicenergigune.com/en/blog/battery-thermal-management-system-btms-electric-vehicle