Week 7 State of charge estimation
EV Live Batch 21
1 Aim: Simulate the 3 test cases from harness dashboard and write a detailed report on the results
Ans: Here we have to create the 3 test cases from harness dashboard of closed loop BMS control model. & also explain the coulomb counting for finding the soc estimation in BMS.
Download and open the closed-loop BMS harness Dashboard model:
=> In the file, exchange open the document of Design and Test Li-ion Battery Management Algorithm.
Download the Zip file and extract it to a folder. The folder consists of these files as shown below,
Simulink Model:
From Dashboard:
=> Test Sequence Variant (Selector).
=> Manual Varient (Selector).
=> BMS_Testsequence state request(Subsystem) to provide state request commands.
=> Lamps to indicate Fault state, High temperature, Over voltage, Over current, charging, voltage sensor operation, inverter operation, low temperature, and Under voltage.If any fault in this red indication will intimate us and all in good conditions indicated by green indication.
=> Rotating switch for manual Varient changes while running simulation.
=> In scope results, the SOC of the module, Module current, Individual cell voltages, Individual cell temperature, Battery state, and Cell balancing states are seen as outputs.
BMS Closed Loop:
=> This main block consists 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 the 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 closed loop model are BMS_input,BMS_Output,BMs_info.
=> In the 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, and charger/load units are created.
In battery packs, there are two types of configurations 1 module (6 cells) and 16 modules (96 cells).
Here we are choosing 1 module for lesser simulation running time.
Explanation:
a). To run three test cases from the harness dashboard of closed-loop BMS control.
I have to test three cases for this model by selecting the test sequence variant and selecting the cases one by one fallows,
1st test case:
Select 1st from the test sequence variant dialog box and click apply as shown in below.
=> This selection consists of selection changes in the masked BMS_State request subsystem as,
=> This test case consists of the following sequence operation.
=> Here from the above test sequence editor figure, it was set as,
(i) Driving for the first 3000 secs.
(ii) After 3000sec starts balancing operations occur for the next 1000 Secs.
(iii) Then charging and balancing occurs for the next 5000 secs.
(iv) After that sequences post charge balancing operation occurs till the end of the simulation period.
Results:
=> The lamp indications are showing green for the overall simulation period showing that there are no faults occurring during the sequences.
=> From the results, I can understand that.
Cell Voltages and Pack Current:
=> For the first 3000secs, all 6 cells are in drive mode where discharging occurs majorly, and in standby mode for the lesser duration at approximately 1000 to 2000 secs.
=> The voltages vary 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 is in standby mode, and voltage is constant at nearly 3.7V.
=> After 4000secs charging occurs, the voltage is 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 up to 9000Secs.
=> After 9000 secs post charge cell balancing starts. All cell voltages are balanced 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 a higher temperature for all stages.
=> After 3000secs up to 4000secs, the cell temperatures are reduced slightly as no current flows through the cell in standby mode.
=> After 4000Secs temperature starts to increase exponentially up to the constant current region and starts to reduce as current flow reduces in constant voltage and cell balancing region up to 9000secs.
=> Cell 1 max temperature raised up to 302K and cell 6 temperature raised up to 317K.
=> After 9000secs the temperatures still reduce and remains stable at reaching ambient temperature.
BMS State:
=> For 3000 secs the battery module is in drive mode(discharging).
=> From 3000 secs to 4000secs the battery module is in balancing standby mode as shown from the resulting plot.
=> After 4000 secs up to 9000secs, the battery module is in charging and balancing mode.
=> After 9000secs only the post-charge balancing mode operates up to the end of the simulation.
SOC:
=> Initially, the state of charge of the battery module is 80%.
=> Here the yellow plot represents SOC estimation done by the coulomb counting technique.
=> The blue plot represents SOC estimation using the Unscented Kalman filter technique.
=> The red plot represents SOC estimation using the Extended Kalman filter technique. Among three UKF and EKF techniques estimate more accurately than the coulomb counting technique.
=> Initially, for 3000 secs, SOC decreases to nearly 45% during drive mode.
=> After 3000secs up to 4000secs, 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 the above plots.
Cell Balancing:
=> Initially, up to 3000secs, balancing was not performing.
=> After 3000 secs cell balancing starts with on cell 6 and cell 2 as they rose to 1 as shown above since its voltage is higher than all other cell voltages.
=> After this stage charging and balancing post, charge balancing occurs as Cell 6 and cell 2 remain in 1 state till the end of the simulation.
=> As cell 1(yellow) is in lesser voltage than other cells it remains in 0 states throughout the simulation.
=> At the end of the simulation, all cell voltages try to balance equally as I saw earlier in the plot of the single-cell voltage.
2nd test case:
=> Now select test case 2 and click apply in the test sequence variant dialog box as shown below,
=> The case is altered to 2nd as shown below.
=> This test case consists of drive Mode for 10000sec and after that charging occurs till the end of the simulation.
=> Now run the model and the results can be viewed.
Results:
=> The dashboard results are shown without any faults occurring.
Scope:
=> Here in these plots, only the driving mode of the battery module is plotted.
Cell Voltages and Pack Current:
=> The cell voltages vary from a maximum of 3.9V and reduce to 3.05V as cutoff voltage up to 9000 secs. the entire capacity drained at 9000 secs.
=> The pack current discharges up to a maximum of 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 has 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 reduced in between the drive modes as these durations are in standby modes.
Battery module state:
=> The 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 up to 10000secs command is given as drive mode.
=> But in an actual practical situation, standby modes are not present as battery current drains by other small auxiliaries of EVs.
SOC of the module:
=> Here the SOC reduces from 80% to 0% (as current is drained for a longer duration) in the entire drive mode as shown in the above plot.
At standby modes in between them, the SOC remains constant as shown.
Balancing:
=> Here balancing of cells is not performed as shown as balance states are in 0 for the entire drive mode.
3rd test case:
=> Now select test case 3 and click apply in the test sequence variant dialog box as shown below,
=> The test case is altered to 3rd as shown below,
=> This test case consists of charging for the entire duration of time.
=> Run the model and the results can be viewed.
Result:
=> The dashboard lamps indications are shown as,
=> All indications are in green indicating no fault conditions have occurred.
The plots are shown as,
Cell voltages and pack current:
=> Initially, in cell 2, voltages rise from 3.9V (approx) to a maximum of 4.2V and stabilised to 4.15V.
=> Cell 1 reises from 3.85V to 4.1V and stabilized to 4.08V.
=> The battery packs current raising from OA to 30A and starts to reduce to 2.5 A gradually at end of full charging up to 2000 secs.
=> At 2000secs the pack is fully charged to 100%.
After a full charge, the current flow will be cut off as shown in the resulting plot.
Cell temperatures:
=> The cell temperatures continue to increase heat up to full charge and after that, the temperatures get started to reduce to ambient temperature.
As shown from the resulting plot the temperatures start to decrease after full charge (at 2000 secs).
BMS state:
=> The 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 the 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 Osec cell 6 and 2 starts to balance with respect to cell and all cells try to balance at end of the simulation.
Conclusion:
=> Hence from the above three test cases, the performance of BMS on various factors is discussed and analyzed.
2 Aim:
What is coulomb counting? Refer to the above model and explain how BMS implements coulomb counting for SOC estimation ?
Ans:
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 the 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 discharging current(I(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 Coulomb 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.
SOC estimation in the BMS model:
=> To see the model of the coulomb counting technique in the BMS model click the subsystem of SOC_Estimation and click Coulomb counting.
=> It is developed as shown in below,
=> Here the discharge current from the battery is given to gain with a value of 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 by 100 to get in the percentage of SOC.
