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Q:-1. Simulate the 3 test cases from harness dashboard and write a detailed report on the results. Ans:- Objective: A)To run three test cases from harness dashboard of closed loop BMS control. B)To explain coulomb counting for finding the SOC estimation in BMS. Downloading and open closed loop BMS harness dashboard…
Chandrakumar ADEPU
updated on 25 Nov 2022
Q:-1. Simulate the 3 test cases from harness dashboard and write a detailed report on the results.
Ans:-
Objective:
A)To run three test cases from harness dashboard of closed loop BMS control.
B)To explain coulomb counting for finding the SOC estimation in BMS.
Downloading and open closed loop BMS harness dashboard model:
In file exchange open the document of 'Design and Test Li-ion Battery Management Algorithm'.
Download the Zip file and extract to a folder. The folder consists of these files as shown below,
Firstly, Open Matlab software and open the Simulink model file of Battery Model in Plant---> Battery model and it open the plant battery model.
and it ask to Open Project and model or open model. Click on open project and model.
Battery model look like below
after that minimize the Battery model and click on " Battery_system.prj "
Next click on the project shortcut ---> open the 02 - BMS System
BMS System model will open
BMS_System
In this main block consist of two subsystems, BMS ECU and PLANT units.
The plant output from the plant unit is given as input to BMS ECU as the BMS_input feedback loop.The state request is given to BMS ECU unit.
The BMS Output commands are given as input to the plant unit as 'From_BMS'. Also, the state request is given to the Plant unit.
The final outputs from the closed-loop model are BMS_input, BMS_Output, and BMS_info.
In BMS ECU unit,the current power limit calculations are done used in State machine block,Soc Estimations,Cell balancing logics as shown below,
In Plant unit,the battery pack unit,Pre charge unit,charger/load units are created.
In battery packs there are two types of configurations as 1 module(6 cells) and 16 modules(96 cells).
Here we are choosing 1 module for lesser simulation running time.
Open Matlab software and open the Simulink model file of 'Closed loop BMS harness dashboard' in Tests-->System-->BMS_Closedloop_Harness_Dashboard model file.
The model file opens as,
Blocks in the model:
In the Dash board
Discussions:
A)To run three test cases from harness dashboard of closed-loop BMS control.
We have to test three cases for this model by selecting test sequence varient and select the cases one by one as fallows,
Test case 1:
Select 1 from test sequence varient dialog box and click apply as shown below.
Click on run button and check the results. This selection consists of selection changes in masked BMS_State request subsystem as,
This test case consist of the fallowing sequence operations as,
Here from the above test sequence editor figure it was set as,
Results:
Run the simulation and results are shown as,
The lamp indications are showing green for overall simulation period showing that there are no faults occurs during the sequences.
From the results we can understand that,
Cell Voltages and Pack Current-
For first 3000secs all 6 cells are in drive mode where discharging occurs majorly and in standby mode for lesser duration at approximately 1000 to 2000 secs.
The voltages varies from 3.1V(min) to 3.9V(max) in this range.
From 3000 secs to 4000secs cell balancing occurs and in this stage the module in standby mode and voltage is constant at nearly 3.7V.
After 4000secs charging occurs,voltage raised from 3.7V to 4V. At 4V to 4.2V at constant current as nearly 30 A and after 4.2 V as constant voltage,current reduces from 30A to 2.6A
at end of the charging and cell balancing occurs upto 9000Secs.
After 9000 secs post charge cell balancing starts. All cell voltages are balancing to a voltage with respect to cell 1 to 4.1 V as shown below,in this stage the pack is in stand by mode.
Cell temperatures:
Initially for 3000Secs the temperature range of cells increases gradually from ambient temperature 288K to 302K.
The temperature of cell 1 is lesser and cell 6 has higher temberature for all stages.
After 3000secs upto 4000secs the cell temperatures are reduced slightly as no current flows through cell in standby mode.
After 4000Secs temperature starts increases exponentially upto constant current region and start reduces as current flow reduces in constant voltage and cell balancing region upto 9000secs.
Cell 1 max temperature raised upto 302K and cell 6 temperature raised upto 317K.
After 9000secs the temperatures still reduces and remains stable at reaching ambient temperature.
BMS State:
For 3000 secs the battery module in drive mode(discharging).
From 3000 secs to 4000secs the battery module in balancing standby mode as shown from result plot.
After 4000 secs upto 9000secs the battery module in charging and balancing mode.
After 9000secs only post charge balancing mode operates upto end of simulation.
SOC:
Initially the state of charge of battery module is in 80%.
Here the yellow plot represents SOC estimation done by coulomb counting technique.
Blue plot represents SOC estimation using Unscented Kalman filter technique.
Red plot represents SOC estimation using Extended Kalman filter technique. Among three UKF and EKF techniques estimate accurately than coulomb counting technique.
Initially for 3000 secs SOC decreases to nearly 45% during drive mode.
After 3000secs upto 4000 secs the SOC is constant at 45% as cell balancing occurs in standby mode.
From 4000 secs to 9000secs module in charging mode.(4000 to 7000=CC mode,7000 to 9000=CV mode).
After 9000 secs the SOC becomes constant approximately 94% as seen from above plots.
Balanceing cells:
Initially upto 3000 secs balancing was not performing.
After 3000 secs cell balancing starts with on cell 6 and cell 2 as they rised to 1 as shown above since its voltage is higher than all other cell voltages.
After this stage charging and balancing,post charge balancing are occurs as Cell 6 and cell 2 remain in 1 state till end of simulation.
As cell 1(yellow) is in lesser voltage than other cells it remains in 0 state throughout the simulation.
At the end of the simulation all cell voltages try to balance equally as we seen earlier in single-cell voltages plot.
Test case 2:
Now select test case 2 and click apply in test sequence varient dialog box as shown below,
The case is altered to second as shown below,
This test case consist of drive mode for 10000secs and after that charging occurs till end of simulation.
Now run the model and results can be viewed.
Results:
The dashboard results are shown as without any faults occured.
The scope result plotted as,
Here in these plots only driving mode of battery module is plotted.
Cell Voltages and Pack Current-
The cell voltages varies from maximum 3.9V and reduces to 3.05V as cutoff voltage upto 9000 secs.Entire capacity drained at 9000 secs.
The pack current discharges upto maximum 70A and slight charging occurs during the overall drive.
Some stand by mode conditions are in between the drive modes.
Cell temperature:
Here cell 1 having lesser temperature variations from 288K to approximately 302.5K.
Cell 6 is having higher temperature variation from 288K to approximately 322.5K.
The cell temperatures are slightly reducing in between the drive modes as these durations are in stand by modes.
Battery module state:
Entire sequence is performing in drive mode as shown from the above plot.
Small duration of standby modes are not plotted in this plot as simulation upto 10000secs command is given as drive mode.
But in actual practical situation standby modes are not present present as battery current drains by other small auxilaries of EV's.
SOC of module:
Here the SOC reduces from 80% to 0% (as current drained for longer duration) in entire drive mode as shown in above plot.
At stand by modes inbetween them the SOC remains constant as shown.
Balancing:
Here balancing of cells are not performed as shown as balance states are in 0 for entire drive mode.
Test case 3:
Now select test case 3 and click apply in test sequence varient dialog box as shown below,
The test case is altered to third as shown below,
This test case consists of charging for the entire duration of time.
Run the model and results can be viewed.
Result:
The dashboard lamps indications are shown as,
All indications are in green indicates no fault conditions are occured.
The plots are shown as,
Cell voltages and pack current:
Initially cell 2 , voltages rises from 3.9V(approx) to maximum 4.2V and stabilised to 4.15V.
Cell 1 reises from 3.85V to 4.1V and stabilised to 4.08V.
The battery pack current raising from 0A to 30A and starts to reduce to 2.5 A gradually at end of full charging upto 2000 secs.
At 2000secs the pack is fully charged to 100%.
After full charge current flow will be cutoff as shown in result plot.
Cell temperatures:
The cell temperatures continue to increase heat upto full charge and after that the temperatures get started to reduces to ambient temperature.
As shown from result plot the temperatures start decreases after full charge(at 2000 secs).
BMS state:
Entire battery pack sequence is operating in charging mode as shown above.
SOC:
The pack SOC gets fully charged at 2000secs and remains at full charge for rest of the sequence as shown above.
The actual state of charge is around 93% shown as full charge shown by UKF and EKF techniques.
Cell Balancing:
Here from 0sec the cell 6 and 2 starts to balance with respect to cell 1 and all cells are try to balancing at end of simulation.
Conclusion:
Hence from above three test cases the performance of BMS on various factors are discussed and analysed.
B)To explain coulomb counting for finding the SOC estimation in BMS.
Coulomb counting:
SOC(State Of Charge) is defined as the rate of available capacity to its maximum capacity when a battery is fully charged and describes the remaining percentage of the battery
capacity.
To find this SOC % we are using coulomb counting method.
The coulomb counting method measures the discharging current of the battery and integrates the discharging current over time in order to estimate SOC.
Which can be estimated from discharrging current(I(t)),previously estimated SOC values(SOC(t-1)).The relation can be given as,
Modified Coulomd counting:
In this technidue discharge current is corrected with a function and corrected current is found out for accurate SOC estimation.
The function can be given as,
Where K0,K1,K2 are constant values obtained from the practice experimental data.
The SOC relation can be given as,
SOC estimation in BMS model:
To see the model of coulomb counting technique in BMS model click the subsystem of SOC_Estimation and click Coulomb counting.
It is developed as shown below,
Here the discharge current from battery given to gain with value as 1/3600 to convert current to Ahr.
The value is divided by capacity due to temperature change. Then integrated with a gain value of 1 with sample time -1 as we are using discrete integrator.
The saturation limits are from 0 to 1.
We will get the SOC values from 0 to 1 multiplied with 100 to get in percentage of SOC.
we Simulated the 3 test cases from harness dashboard and written a detailed report on the results also submited the results below.
and aslo stated What is coulomb counting Referd to the above model and explained how BMS implements coulomb counting for SOC estimation.
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