Week 7 State of charge estimation
(1). Stimulate 3 cases for harness dashboard:
>The battery model harness dashboard is represented below:
Case 1:
>Click on the test sequence varient block and select test case as 1.
>By clicking on the BMS Sequence block we get the chart.
>When simulation will start, the model will be in driving condition.
>After 3000 seconds it will be in standby mode and after 1000 seconds it will be in charging mode.
Results:
>Here all the indicators are green, so we can see no errors and we check the plot for this model and is shown above.
>From the plot we can see the vehicle is initially in driving stae and charging was done til 90%.
>After charging it reaches to standby mode, it can be seen in BMS state plot battery temprature increases in driving and charging.
>Battery voltage was increased to 4.2V while charging, SOC is decreased upto 50% in driving condition and it as increased while charging.
Case 2:
>Now change the test sequence varient to case 2.
>Now by clicking on the BMS state request block.
Result:
>From the above graph, a fault condition occured in second case.
>So even after charging was started the SOC did'nt increase, it continued to decrease.
Case 3:
>Now change the test sequence varient to case
>This condition has only one phase and that is charging.
>Thus, 0 to 20000 seconds simualtion runs.
Result:
>Here we can see that the SOC has reached 100% in charging and remained in standby mode.
>Cell temprature is also decreased when the standby mode was achieved.
Conclusion:
>From 3 cases we can obsereve 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%.
(2). Coloumb Counting & BMS impletations on columb counting for SOC estimation.
Coloumb Counting:
>THe coloumb counting method measures the discharging current of a battery and integrates the discharging current over time in order to estimate SOC.
The SOC is calculated by the following equation:
>But there are sevral factors that affect the accuracy of colomb counting method including teamprature, battery history, discharge current and cycle life.
Modified Coloumb Counting Method:
>To improve the coloumb counting method, a new technique called modified coloumb counting method is proposed.
>The modified coloumb 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.
By practice of experimental data, corrected current is calculated by the following form:
where k2,k1 and k0 are constant values obtained from the practice experimental data.
In modified coloumb counting method, SOC is calculated by the following equation:
>The experimental results show that the accuracy of the modified coloumb counting method is superior to the conventional coloumb counting method.
>But there are sevral factors that affect the accuracy of columb counting method including temprature, abttery history, discharge current and cycle life.
For example we can look into the project file we downloaded. A BMS system in the file represented below:
BMS algorithm models, protects, reports the measurement from battery pack.
By clicking on the BMS ECU we get the subsystem
By clicking on the SOC estimation block we get
From above figure we observe the columb counting block
A subsytem opens when we click on the coloumb counting
>This system does the estimation by coloumb counting equation mentioned above.
>Advantage of columb counting method is it's simplicity and low computation cost.
>Temprature and current from the battery is given as inputs.
>Current signal is given to a gain block and temprature is given to capacity since it varries according to the temprature.
>These inputs are given for integration where current will be integrated with respect to time.
>This output is given to another block where it is divided by capacity.
>Hence the SOC is estimated.