Week 7 State of charge estimation

                                                                                                                                EV BATCH - 17

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

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

1A) Downloading and harness dashboard model for Open and closed loop 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 consist of these file as shown below.

Open Matlab software and open the simulink model life file of closed loop BMS harness dashboard in Tests--->system--->BMS_Closedloop_Harness_Dashboard model file.

Then give open project and model in Pop-up dailog box to install all the model related library files in to the current folders and workspace.

The model file open as,

Blocks in model :

Dash board

. Test sequence varient (selector).

. Manual Varient (selector).

. BMS-Testsequence state requent (Subsystem) to priovide state request commands.

. Lamps to indicate Fault state,charging,High temperature,Over voltage,Over current,Charging,Voltage sensor operation ,inverter operation,low temperature, under voltage.If any fault in these red indication will intimate us and all in good conditions indicated by green condition.

. Rotating switch for manual varient changes while running simulation.

. In scope results the soc of module,module current,individual cell voltages, Individual cell temperature ,Battery state ,Cell balancing states are seen as outputs.

BMS_ Closed loop :

In this main block consist of two sub systems,BMS ECU and PLANT units.

This plant output from plant unit given as input to BMS ECU unit.

The final outputs from closed loop model are BMS_input,BMS_Output,BMS_info.

 

IN BMS ECU unit, the current power limit calculations are done used in state machine block,SOC Estimations,Cell balancing logic as shown below.

 

In plant Unit, the battery pack unit,Pre charge unit,Charge/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 runing time.

 

 

Discussions :

1. 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 the test sequences varient and select the cases one by one as follows,

Test -1 :

select 1 from test sequence varient dialog box and click apply as shown below.

This selection consist of selection changes in masked BMS_state  request subsystem as

This test case consist of the following sequence operation as ,

Here from the above test sequence editor figure it was set as

. Driving for first 3000 seconds.

. After 3000 seconds starts balancing operation occure for next 1000 seconds.

. Then charging and balancing occurs for next 5000 seconds.

. After that sequences post charge balancing operation occurs still end of the simulation period

 

Results :

Run the simulation and result are shown as,

The lamp indications are showning green for overall simulation period showing that there are no faults occuring during the sequences, 

from the result we can understand that,

Cell voltages and pack current :

For sirst 3000 seconds all 6 cells are in drive mode where discharging occurs mainly and in stand by mode for lesser duration at approximately 1000 to 2000 seconds.

The voltage varies from 3.1V(min) to 3.9(max) in this range

From 3000 seconds to 4000n seconds cell balancing occurs and in this stage the module in standby model and bvoltage is constanyt at nearly 3.7 volts.

After 4000 seconds charging occurs,voltage raised from 3.7v to4v at4v to 4.2v at constant current as nearly 30A and after 4.2V as constant voltage,surrent reces from30A to 2.6V.

After 9000 seconds post charge cell balancing starts .All cell voltages are balancing to a voltage with respect to cell 1 to 4.1V as shown below 

In this stage the pack is in stand by mode.

Cell temperatures :

Intially fro 3000 seconds the temperature range of cells increases gradually from ambient temperature 288k to 302k.

The temperature of cell1 is lesser and cell 6 has higher temperature for all stages.

After 3000seconds upto 4000seconds the cell temperatures are reduced slightly as no current flows through cell in standby mode.

After 4000seconds temperature starts increases exponentially upto constant current region and start reduces as current flow reduces in constant voltage and cell balancing region upto 9000seconds.

Cell 1 max temperature raised upto 302k and cell 6 temperature  raises up to 317k

After 9000 seconds the temperature still reduces and remian stable at reaching ambient temperature.

BMS State :

For 3000 seconds the battery module in drive model.

From 3000 seconds to 4000 seconds  the battery module in balancing standbymode as shown from result plot.

After 4000 seconds upto 9000 seconds the battery module in charging and balancing mode.

After 9000 seconds 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.

Balacing 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 remains in 1 state till end of simulation.

As cell 1(blue) is in lesser voltage than other cells it remains in 0 state through out 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 10000seconds 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 faluts occurred.

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.

As stand by modes in between 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 dailog box as shown below.

The test case is altered to third as shown below.

This test case consist of charging for entire duration of time .

Run the model and result can be viewed.

Result : The dashboard lamp indications are shown as 

All indications are green indicates no fault conditions are occured,these plots are shown as,

Cell Voltages and Pack Current  :

Intially cell2,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 OA 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 temperature continue to increases heat up to full charge and after that the temperatures get started to treduce to abient temperature.

As shown from result plot the temperatures start decreases after full charge (at 2000 sec).

BMS state :

Entire battery pack sequence is operatng in charging mode as shown above.

SOC :

The pack SOC gets fully charged at 2000 seconds 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 as UKF and EKF techniques.

Cell Balancing :

Here from 0sec the cell6 and 2 starts to balance with respect to cell1 and all cells are try to balancing at end of simulation.

Conclusion : 

Hece from above three test cases thr performance of BMS On Various factors are discussed and analysed.

1. 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(1(t)),previously

estimated SOC values (SOC (t-1)). The relation can be given as,

SOC (t)=SOC (t-1)+ I(t) /Q(n) △t.

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,

Ic(t) = k2I(t)^2+k1 I(t) + k0

Where K0,K1,K2 are constant values obtained from the practice experimental data.

The SOC relation can be given as,

SOC(t) = SOC(t-1)+Ic(t)/Qn △t.

Flowchart  of columb counting :

SOC estimation in BMS model :

To see the model of coulumb counting technique in BMS model click the subsystem ofSOC_Estimation and click coulumb counting.

It is developed as shown as below.

Here the discharge current from battery given to gain with value as 1/3600 to convert 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 the generator.

The saturation limits are from 0 to 1.

We will get the SOC values from 0 to 1 multiplied with 100 to get in percentsge of SOC.

CONCLUSIONS:

1)one of the main problems in coulomb counting is 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

2)Kalman filtering is an algorithm that provides estimates of some unknown variables given the measurements observed over time .