Challenge

Week 7 State of charge estimation

NOTE: LIVE SESSION BATCH 16 by Alwin Augustine Sir

Q1) ANS

The bellow model is of the BMS_ClosedLoop_Harness_Dashboard for design and test lithium ion battery management algorithms.
model include charge discharge current limiter, state machine for decides BMS states, SOC estimation, Passive Cell balancing logic, Battery pack, Precharge circuit, Charger and Load.
Also it include some pack, inverter and charger test

1)coulomb counting,

2)Unscented Kalman Filter

3)Extended Kalman Filter.

There are three test sequence modes to simulate this model.

First Step:

Here in the first test sequence model, BMS drive for 3000 sec then foe 1000 sec BMS get standby after that for 5000 sec pack charge and remaining time again BMS get in standby position.

Second Step:

Third Step:

RESULTS OF TESTS:

For Test 1

In above result graph shows the various plots of battery pack and BMS parameters.
BMS status like Driving, Charging and Standby condition shown by BMS state plot
Due to the driving patterns of vehicles, current and voltage of the battery pack when BMS driving, they significantly fluctuate
We can see in BMS driving mode battery pack current is positive because of the regenerative braking and it is negative due to current drain from the battery pack for moving vehicle and cell temperature is increasing and SOC is slightly decreasing.
Pack voltage, current and SOC is stable and cell temperature is decreasing When BMS is in standby mode for 1000 sec
At time of start of standby mode cell balancing logic gives command for cell balancing as in this model passive cell balancing technique is used and we can not operate passive cell balancing during the discharging.
then we can see that at 4000 sec BMS starts charging the battery pack for 5000 sec.
if we can see current and voltage plot then we get the idea about battery pack charge with CCCV technique.
at initial state temperature starts increasing when constant current charging starts, and after that temperature starts decreasing when constant voltage charging starts.
If we see SOC graph SOC increases rapidly in constant current charge and SOC increases slowly when constant voltage charging starts.
All parameters get stable when full charge of the battery pack complete.

For Test 2:

In above test there is no cell balancing command as BMS operates only in driving mode for 10000 sec.
The result is same as Test 1 for starting 3000 sec
As per drive patterns of vehicles the Current and voltage fluctuates
as BMS operates only in driving mode during this test because of discharging or battery use the load cell temperature is increased and SOC decreased.

For Test 3:

BMS only charge the battery pack for the whole duration in this test
As we can operate a passive cell balancing technique during charging, cell balancing logic gives the cell balance command at the starting of the simulation
CCCV technique is used for battery pack charging .We can see in the temperature plot cell temperature is increased at constant current charging and temperature starts decreasing. as constant voltage charging starts,
Cell voltage starts stabilizing at maximum voltage, current reduces to zero and temperature starts reducing upto ambient temperature when full charge of the battery pack is done

Conclusion:

Unscented Kalman Filter, Extended Kalman Filter calculate the similar SOC but SOC estimate by using coulomb counting is slightly higher than the other two methods and
Its because In the case of Kalman filter it considers various effects and calculates practical SOC and coulomb counting calculates ideally or mathematically input or output goes charge from the battery.
passive cell balancing is not possible during the BMS driving mode or at time of discharging the battery pack,
temperature of the cell gradually reduces as same time charging current also gets reduced during the constant voltage charging

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Q2)ANS:

Coulomb counting is a technique used to track the State of Charge (SOC) of a battery pack.
It works by integrating the active flowing current (measured in amps) over time to derive the total sum of energy entering or leaving the battery pack.
In coulomb counting measuring the current (total charge in coulomb) flowing in and out of the battery. For this SOH is required. SOC accuracy also decreases if SOH is not accurate
Change in SOC = Charge pumped in or out of battery / (Total capacity * SOH)
SOC (new) = SOC (old) + Change in SOC
Charge (Q) = Current(I) * Time(t)

Algorithm of Coulomb Counting Flowchart

belowis subsystem of coulomb counting

Model above shows the coulomb counting subsystem and it works as discussed above .
For input Battery pack current and cell temperature signals are used and for output signal is SOC
For converting current into the charge with respect to time discrete time integrator is used
For the converting time in sec to hour Gain block is used
For predicting total capacity while considering cell temperature a 1-D lookup table is used.
Breakpoints are cell temperature and table data is battery capacity in 1-D lookup table

Ship work like this
in your own course.