Thermal Management of Battery Using Nano Fluid

$405.00 Student Discount

In this project, Thermal Management of Battery (using Nano Fluid) has been simulated and the results of this simulation have been investigated.

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The journal file in ANSYS Fluent is used to record and automate simulations for repeatability and batch processing.
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Geometry, Mesh, and CFD Simulation methodologygy explanation, result analysis and conclusion
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Description

Thermal Management of Battery (Using Nano Fluid), CFD Simulation Ansys Fluent Training

The present problem simulates the Thermal Management of Battery Using Nano Fluid (Two-Phase) by Ansys Fluent software.  This simulation is related to a Dual-Potential MSMD (multiscale multidomain) battery model. Generally, a battery can store electrical energy in chemical energy. If the current is requested from the battery, the chemical energy is converted into electrical energy, and when the battery is charged, the electrical energy is converted into chemical energy. Also, heat can be generated from multiple sources, including internal losses of joule heating and local electrode overpotentials, the entropy of the cell reaction, the heat of mixing, and side reactions.

Previously a modular, efficient battery simulation model (MSMD model) was introduced to aid the scale-up of Li-ion material & electrode designs to complete cell and pack designs, capturing electrochemical interplay with 3-D electronic current pathways and thermal response. The expandable and flexible architecture connects the physics of battery charge/discharge processes, thermal control, safety, and reliability computationally efficiently.

The present simulation is performed with Mixture multiphase model, and the effect of nanofluid flow in heat transfer enhancement of the battery is investigated. This work aims to investigate the effectiveness of phase change materials in the cooling process of the battery. The nanofluid material is water as base fluid and aluminum as nanoparticles, and the velocity of the nanofluid at the inlet face is equal to 0.1 m/s. The volume fraction of nanoparticles is 0.05.

GK empirical model is set for E–Chemistry. The Specified C-rate of 0.5 and numerical cell capacity of 14.6 are chosen as Electrical parameters.

Geometry & Mesh

 The Geometry of this model is designed in Design Modeler software three-dimensionally, and the scale of it is as follows:

Xmin: -0.007 m                                          Xmax: 0.007 m

Ymin: -0.008 m                                          Ymax: 0.0087 m

Zmin:  -0.0008325 m                                  Zmax: 0.002 m

Battery

We carry out the model’s meshing using ANSYS Meshing software. The mesh type is polyhedral, and the cell number is 362734. The following figure shows the mesh:

Battery Battery

Battery CFD Simulation

We consider several assumptions to simulate the present model:

  • Solver is pressure-based.
  • The simulation is transient.
  • The gravity effect is set at -9.81 in the Y direction.

The following table represents a summary of the defining steps of the problem and its solution:

General
Time Transient
Models
Viscous Laminar
Energy on
multiphase Mixture Model
Interface Modeling Dispersed
Formulation Implicit
Granular on
 

 

Particle Diameter

 

1e-5

 

 

 

Slip Velocity

 

On

 

Inlet Velocity Inlet
velocity magnitude 0.1 m.s-1
Volume Fraction 0.05
Temperature 298 k
Outlet Pressure Outlet
gauge pressure 0 pascal
Walls Wall
wall motion stationary wall
Battery Model on
Solution Method MSMD
E-Chemistry Model NTGK Empirical Model
Solution Options Specified C-Rate
C-Rate 0.5
Min. Stop Voltage 3
Max. Stop Voltage 4.3
Initial DoD 0.2
Methods
Pressure-Velocity Coupling SIMPLE
Pressure PRESTO!
momentum first-order upwind
Volume Fraction first-order upwind
Energy first-order upwind
Transient Formulation First Order Implicit
Wrapped-Face Gradient Correction on
Initialization
Initialization methods Standard
gauge pressure 0 pascal
x-velocity -0.1 m.s-1
y-velocity 0 m.s-1
z-velocity 0 m.s-1
Temperature 298 k
Phase-2 Granular Temperature 0.0001 m2/s2

Thermal Management of Battery Using Nano Fluid Results

We obtained two-dimensional and three-dimensional pressure and temperature contours, respectively, at the end of the solution process. We presented this chart in 500 Seconds. The results show that applying a Nanofluid flow to the battery body will cool and reduce the temperature growth rate.

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