Challenge

Week 7 State of charge estimation

AIM: To Study “Design and Test Lithium-Ion Battery Management Algorithms” MATLAB model.

OBJECTIVE:

1. To simulate the 3 test cases from the harness dashboard and study the results.

2. To study coulomb counting, and find how BMS implements coulomb counting for SOC estimation?

SIMULINK MODEL:

BODY:

Part-1

Case 1

From the above figure, we observed that driving is for 3000 seconds then followed by balancing for 1000 seconds followed by charging and balancing for 4000 seconds, then there is post charge balancing.

Case 2

The driving stage is for 0 to 10000 seconds. then the charging stage occurs.

Case 3

As there is only one stage that is the charging stage thus from 0 to 20000 seconds, only charging will take place.

RESULTS:

Case 1

1) From the plot, we can see the vehicle is initially in a driving state, and charging was done to 90%. After charging it reaches standby mode. It can be seen in the BMS state plot.

2) Battery temperature increases in driving and charging. Battery voltage was increased to 4.2V while charging.

3) The current plot shows the value of current supplied to the vehicle while driving.

4) SOC decreased up to 50% in driving conditions and it was increased while charging.

Case 2

1) The cell voltage fluctuates from 3.9 volts to 3.2 volts repeatedly as seen in the graph of cell voltages.

2) The battery pack current fluctuates from 0 to -60A and then rises to 10 A repeatedly as shown.

3) The cell temperature increases as there is a driving stage from 0 to 10000 seconds.

4) As the driving stage is there from 0 to 10000 seconds, thus BMS graph shows the BMS driving.

5) The SOC continues to reduce from 80% to 0%. the SOC does not increase because there is no charging and balancing stage.

6) The driving stage is till 10000 seconds as battery completely discharges at 9000 seconds (as SOC is 0% at 9000 seconds) thus vehicle runs till

9000 seconds only.

Case 3

1) Here we can see that the soc reached 100% in charging and remained in standby mode. Cell temperature also decreased when standby mode was achieved.

2) From the 3 cases we observe that only charging takes place thus SOC was 80% at first, then SOC increases to 100% in 2000 seconds then SOC remains constant at 100%.

Part-2

Coulomb counting

It is a method that measures the discharging current of a battery and integrates the discharging current over time in order to estimate SOC, which is estimated from the discharging current, and previously estimated SOC values.

SOC is calculated by the following equation:

But there are several factors that affect the accuracy of the Coulomb counting method including temperature, battery history, discharge current, and cycle life.

Modified Coulomb Counting Method

To improve the Coulomb counting method, a new technique called the 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 the battery. By the practice of experimental data, the corrected current is calculated by the following form:

where are constant values obtained from the practice experimental data, In the modified Coulomb counting method, SOC is calculated by the following equation:

The experimental results show that the accuracy of the modified Coulomb counting method is superior to the conventional Coulomb counting method. But there are several factors that affect the accuracy of the Coulomb counting method including temperature, battery history, discharge current, and cycle life.

In the model, the BMS implements coulomb counting for SOC estimation in the following way.

  • This system does the estimation by the coulomb counting equation mentioned above.
  • The advantage of the coulomb counting method is its simplicity and low computational cost.
  • Temperature and current from the battery are given as inputs. The current signal is given to a gain block and temperature is given to capacity since it varies according to temperature.
  • These inputs are given for integration where the current will be integrated with respect to time.
  • This out is given to another block where it is divided by the capacity, Hence the SOC is estimated.

SOURCE:

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

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