Week 7 State of charge estimation

1) Simulate the 3 test cases from harness dashboard and write a detailed report on the results.

Matlab model to simulate the 3 test conditions from harness dashboard and the explain how BMS implements algorithms.

LINK : https://in.mathworks.com/matlabcentral/fileexchange/72865-design-and-test-lithium-ion-battery-management-algorithms

The closed loop harness dashboard model.

To select one of the three conditions to be tested, it can be selected by the test sequence variant block which allows to select which test needs to be simulated.

The first variant was selected initially for the first simulation.

It states that at the start of the simulation the model will be in the driving condition after 3000 seconds it will be in balancing mode, after 1000 seconds it will be in charging and balancing mode and after 5000 seconds it will be post charging balancing mode. After simulating the model for 20000 seconds as shown.

We can see all the lights have turned green as there is no fault or errors in the model.

• In the plot it can be observed that the vehicle is initially in the driving state and charging was done till 90%. After the charging mode it reaches to the standby mode which can be seen from the BMS state plot.
• From the cell temperatures plot it is observed that the battery tamperature rises in driving and chgarging. The battery voltage was increased to 4.2V while driving.
• The current plot shows the current value supplied to the vehicle while driving. The SOC was observed to the decreased around 50% in driving conditions, which is increased while charging.

The second variant is simulated :

Initially it is the driving condition and after 10000 seconds there is charging condition.

• It was observed from the plot that the battery discharges completely at 8692 seconds and the vehicle does not go forward and the charging state is was not achieved at 10000 seconds. Hence the vehicle comes to standby condition and simulation stops midway.

The third variant is simulated :

Initially at the condition below for for third variant of the simulation. The continous charging condition from the start till end of 20000 seconds of simulation.

Looking at the plot if can be seen that the battery starts charging and the SOC starts increasing from beginning to around 2000 seconds and stays stable at 100% continously from 2000 seconds untill 20000 seconds. The peak current plot drops from 0 to 2000 seconds and stays constant as the charge is not used anywhere as the driving is not present.

From the above simulated 3 variants of the simulation carried out it was observed that,

• In the simulation all the three conditions were simulated such as driving charging and the stable state hence the charging and discharging were observed and in the end the constant 100% SOC was observed because of the standby state of the vehicle.
• In the second simulation it was discharging as the SOC dropped to 0% in the driving state within 8600 seconds and the charging state was not achieved at 10000 seconds.
• In the third simulation, only charging was observed for the 2000 seconds and the SOC remained at 100% constant for the next 18000 seconds.

2) What is coulomb counting? Refer to the above model and explain how BMS implements coulomb counting for SOC estimation.

• The coulomb counting method measures the discharging current of a battery and integrates the discharging current over time in order to estimate SOC.
• Coulomb counting method is done to estimate the SOC (t), which is estimated from the discharging current, I(t) and previously estimated SOC values, SOC(t-1).

SOC is calculated by the following equation.

SOC(t) = SOC(t-1) + `(I(t))/Q_n Deltat`

• but there are several factors that affect the accuracy of coulomb counting method including temperature, battery histor, discourage current and cycle life.

Modified coulomb counting method :

• To improve the coulomb counting method, a new technique called modified coulomb counting method is proposed. The modified coulomb counting method uses the corrected current to improve the accuracy of estimation.
• The corrected current is the function of discharging current. There is a quadratic relationship between the corrected current and discharging current of battery.

The corrected current is calculated by using.

`I_C(t) = k_2I(t)^2 + k_1I(t) + K_0`

Where, `k_1,k_2, and k_0` are constant values obtained from the practice experimental data. In modified coulomb counting method, SOC is calculated by the following equation.

`SOC(t) = SOC(t-1) + I_C/Q_n Deltat`

The experimental results show the accuracy of the modified coulomb method is superior to the conventional coulomb counting method. From the given model by mathworks, BMS closed loop model, when seen inside the BMS ECU.

The subsystem of BMS ECU :

The subsystem of SOC_Estimation

• The system carries out the estimation by coulomb counting equation mentioned earlier. The main advantage of coulomb counting is that of its simplicity and low computational cost. Temperature and current are taken as input from the battery.
• Current signal is given to the gain block and the temperature is given to capacity as it varies according to the temperature. These inputs are given to integration where current will be integrated with respect to the time. This output is given to another block where it is divided by capacity and hence the SOC is estimated.

REFERENCE :

• https://in.mathworks.com/matlabcentral/fileexchange/72865-design-and-test-lithium-ion-battery-management-algorithms
• https://www.mathworks.com/videos/series/how-to-develop-battery-management-systems-in-simulink.html

CONCLUSION :

• One of the main problems in coulomb counting us that it is necessary to calibrate the initial battery SOC. In several applications the initialization involves rest and the initial SOC is estimated based on the voltage.