Project 2 Thermal modeling of battery pack

# AIM

Model of 10 cell series lithium-ion battery and analyze their performance

# THEORY

Lithium-ion batteries

Lithium-ion batteries are secondary batteries that are widely used in electric vehicles (EVs), mobile phones, electric watches, and so forth. They stand out from other batteries due to their high energy density, low self-discharge, high output voltage, and good stability. They are available in various compositions (Table) and shapes like cylindrical prismatic, pouch, and coin. Cylindrical, prismatic, and pouch-type Li-ion cells are generally used in battery-powered EVs. The electrochemical reactions of a Li-ion cell during the charging/discharging of the battery as shown in Equation are due to the lithium intercalation reaction and are depicted in Figure.

compositions of lithium-ion batteries (Mented by a performance index on an increasing scale of 1 to 5)

# OBJECTIVE

For a 10-cell series lithium-ion battery model, simulate the thermal effects and compare life cycle performance at various temperatures, and charge & discharge rates using MATLAB.

# THEORY

# MODEL DESCRIPTION

Lithium-ion batteries are most famous for powering electric vehicles, which are set to account for up to 60 percent of new car sales by 2030.

Nowadays lithium-ion batteries are mostly used in electric vehicles we must know its charge and discharge rates to operate this battery in an efficient manner and without damage when this battery in operation this temperature of it must be kept in the limit we simulate the thermal effect of this cell, by knowing the how much temp rise take place we can provide efficient cooling to the battery so that the life cycle of the battery increases we will see a model on this issue below and explanation as follows

cells connected in series and one of the cell is faulty so what will be a thermal effect. This example shows how to simulate a battery pack consisting of multiple series-connected cells in an efficient manner. It also shows how a fault can be introduced into one of the cells to see the impact on battery performance and cell temperatures. For efficiency, identical series-connected cells are not just simply modeled by connecting cell models in series. Instead, a single cell is used, and the terminal voltage is scaled up by the number of cells. The fault is represented by changing the parameters for the Cell 10 Fault subsystem, reducing both capacity and open-circuit voltage, and increasing the resistance values.

This example shows how to simulate a battery pack consisting of multiple series-connected cells in an efficient manner.

• It shows how a fault can be introduced into one of the cells to see the impact on battery performance and cell temperatures.
• For efficiency, identical series-connected cells are not just simply modeled by connecting cell models in series. Instead, a single cell is used, and the terminal voltage is scaled up by the number of cells.
• The fault is represented by changing the parameters for the Cell 10 Fault subsystem, reducing both capacity and open-circuit voltage, and increasing the resistance values

• From the plot, we get SOC and temperature of the cells w.r.t. time for a given drive data. It can be seen from the first plot of temperature that cell 10 has a higher temperature than all other cells.
• The initial temperature of all cells is 293.1 K. With ongoing driving conditions for 22 minutes approximately, the faulty cell temperature rises to 333.8K and other cells to 339.6K.
• The rate of rising and fall in the temperature of the 10th cell is high which states that it is highly unstable. The higher temperature in any cell is not desired as it may increase the temperature on the surrounding cells.
• The SOC of the fault cell is less than the other cells. Starting from 40% the fault cell reduced to 35% in 22 minutes. All other cells from 45% state of charge, came down to 40%.
• This causes an imbalance between cells and results in reduced life of the battery and deteriorates the performance.

Now we edit the above Simulink model as per our requirement as shown below.

* Simulink Model:

Cell 01 to O4 Subsystem:

• Cell subsystem basically consists of a Thermal Model and Lithium Cell 1RC block which calculates the temperature and thermal effect for cells and overall for the battery pack.

• This block basically consists of a capacitance value in table which depends on an external physical signal inputs SOC and T.
• It is assumed that the capacitance value is slowly varying with time, and hence the equation i = C*dv/dt holds.
• The resistance value (R) table depends on an external physical signal inputs SOC and T.
• Voltage value (EM) which implements the cell's main branch voltage source, determines values for capacity (C) and state of charge (SOC). The defining equations depend on cell temperature, T.

For Faulty Cell 5

For Cell 06 to 10

• Output of one cell is connected with the SOC estimation whereas other output is connected with AC current source for cyclic charge/discharge profile.
• The peak amplitudes set to 50 A for cyclic charge and discharge. A basic parameter of AC current source is as

Temperature Source

• The Temperature Source block represents an ideal source of thermal energy that is powerful enough to maintain specified temperature at its outlet regardless of the heat flow consumed by the system.
• The source generates constant absolute temperature, defined by the Temperature parameter value.

Temperature Sensor

• The Temperature Sensor block represents an ideal temperature sensor, that is, a device that determines the temperature differential measured between two points without drawing any heat.
• Connections A and B are thermal conserving ports that connect to the two points where temperature is being monitored. Port T is a physical signal port that outputs the temperature differential value.
• The block positive direction is from port A to port B. The measured temperature is determined as T = TA – TB.

Ports

• A: Thermal conserving port associated with the sensor positive probe.
• B: Thermal conserving port associated with the sensor negative probe.
• T: Physical signal output port for temperature
  
  

Convective Heat Transfer:

• This block models heat transfer in a thermal network by convection due to fluid motion. The rate of heat transfer is proportional to the temperature difference, heat transfer coefficient, and surface area in contact with the fluid.

From and goto blocks

• The Goto block passes its input to its corresponding From blocks. The input can be a real- or complex-valued signal or vector of any data type. From and Goto blocks allow you to pass a signal from one block to another without actually connecting them.
• The From block accepts a signal from a corresponding Goto block, then passes it as output. The data type of the output is the same as that of the input from the Goto block. From and Goto blocks allow you to pass a signal from one block to another without actually connecting them.

State of charge estimation

• The Coulomb counting method measures the discharging current of a battery and integrates the discharging current over time in order to estimate SOC
• This subsystem takes current as input and gives the battery SOC % as output. A current sensor block is used and connected for soc estimation
• This ckt estimates the battery SOC % using the coulomb counting method. It takes current as the input and gives SOC% as output. The initial SOC of the battery is assumed to be 100% (1)
• Example shows how to simulate a battery pack consisting of multiple series-connected cells in an efficient manner. It also shows how a fault can be introduced into one of the cells to see the impact on battery performance and cell temperatures

# RESULTS

At 293.1K Temperature

At 300K Temperature

At 320K Temperature

• For a 10-cell series lithium-ion battery model, we simulated the thermal effects and compare life cycle performance at various temperatures, and charge & discharge rates using MATLAB.
• 1-4 cells are normal cells, 5th cell is faulty, 6-10 cell is a normal cell
• We are simulating thermal effect, we give Cyclic Charge/ Discharge Profile to the circuit
• From the above results all conditions it is the same but when ckt is run on this drive cycle profile as the 5th cell was faulty it will show a temperature rise high than any other cell and the life cycle of the cell gets reduced and cell even can get damage
• So as we give temperture at 293.15 the 1-4 and 6-10 cell temperature is near to 308k but 5th faulty cell temp goes to 320k and the drive cycle is shown which is Cyclic Charge/ Discharge drive cycle
• In condition two, we give a temperature 300 k the 1-4 and 6-10 cell temp is near to 316 k but 5th faulty cell temperature goes to 325kand the drive cycle is shown which is Cyclic Charge/ Discharge drive cycle
• In condition three we give a temperature of 320 k ie the 1-4 and 6-10 cell temperature is near to 336 k but 5th faulty cell temperature goes to 346k ie 80.85°C and the drive cycle is shown which is Cyclic Charge/ Discharge drive cycle

# CONCLUSION

we simulated the thermal effect and compared it at various temperatures, faulty cell temperature rise is more than the normal cell charge and the discharge cycle is given and due to temp rise, it can damage the cell and reduce the performance of the battery.