Week 7 State of charge estimation

AIM :

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 ?

OBJECTIVE (1) - To Simulate the 3 test cases from harness dashboard and write a detailed report on the results

The Model :

It can be used to mimic diverse usage cycles and environmental conditions to evaluate assistance response to a potentially unsafe condition. For instance voltage current or temperature outside the recommended limits. Let's see this battery management system is a part of an EV powertrain and the initial SOC is 75% with the ambient temperature in being 15° C. The vehicle will run for a while and then stops to charge what is the vehicle and batteries are addressed and charging the self balancing cycle starts .

• How do we know that during the charging stage the battery pack will remain within recommended electrical and thermal limis. What is the temperature of the fact is 40° C instead of close to 15°. Will an aggressive drive cycle cause an under voltage situation when the SOC is running low.

• A models such as this allows the vehicle designer to test this type of situations.

BMS ECU : this represents the software and controls part of the model be showing how cell balancing is done, SOC is estimated in response to a different state using stateflow.

Plant :

This represents the hardware part of the model with the battery pack, precharge circuit and charger.

Test Harness Dashboard :

For testing different situations and scenarios.

TEST CASE 1 : click on test sequence variant block and select test case as 1

Now by clicking on the BMS system we get the chart

Battery is on driving mode for first 3000 seconds.

• The next 1000 seconds it is cell balancing as the battery management system has come to a standby. This will generally happens when the vehicle has come to a stop for a long time.

• Next 5000 seconds are for charging.

Battery management system(BMS) continues to be in standby for the remaining 11,000 seconds.

RESULTS :

• Fluctuations in cell voltages and that current until 3000s indicate that the vehicle was on driving mode.

• Tell voltages start of differently which means there was a SOC imbalancing from the beginning. However they do start converging after 3000s self balancing begins and by the end of 20,000 seconds all cells stabilised around 4.1V.

•Between 4000 seconds and 9000 seconds there is constant current (CC)and constant voltage(CV) charging happening from 4000 to 4600 seconds. It is cc and the remaining is CV. During the CC the SOC increase is much more quickly and then slows down during CV as a precaution mechanism to a much charging past the voltage limit.

• There is a moderate difference in the temperature of cell 1(297K0 and cell6(303k) when the vehicle comes to a stop at 3000 seconds. This is because of the way the battery pack is assembled.

• Cell 1 Open to the atmosphere while cell 6 who is thermally insulated on one side.

• The difference in the peak temperatures is 15°C and this happens during the initial charging stages.

• The SOC graph shows the estimation of SOC through different methods with yellow corresponding to coulomb counting, blue for unscented Kalman filter(UKF) and orange for extended Kalman filter(EKF) .

• Both Kalman filter methods are evidently more accurate than coulomb counting due to their ability to account for voltage information.

CASE 2 : Now we will change the test sequence variant in case 2

Now by clicking on the BM estate request Block

RESULTS :
From the above graph we can see that a faulty condition is observed in the second case .

So even after the charging was started the SOC did not increase, it continued to decrease.

CASE 3 : Now by changing the test sequence value to3 :

This condition has only one phase and that is charging. Thus 0 to 20,000s simulation runs.

RESULTS :

1. since the battery is only in charge in More the sudden influx of current from 0 to 30A is seen in first 5 seconds.
2. Due to the surge of electrons in to the cells this also explains the drastic rise in temperature in all cells.
3. EFK has outperformed UKF buy a little bit again while coulomb counting method more SOC approximation seems the most inaccurate. We can see this because of SOC is 100% highly unlikely and with coulomb counting it might be displaying 100% because it is only pre programmed to do so and at the end of CCCV charging.
4. EKF shows a SOC of 93% while UKF displays 94.5% which looks more realistic and accurate as well.

OBJECTIVE(2) - What is coulomb counting? Refer to the above model and explain how BMS implements coulomb counting for SOC estimation ?

Coulomb counting :

• SOC is a measure of how much charge is available for use in battery.

•For the application of rechargeable batteries in HEVs, SOC is a crucial parameter and thus needs to be measured accurately through electronic and electrical systems.

• It cannot be measured directly because it requires measuring the lithium content at both electrodes.

• Without accurate SOC measurement, the battery management system (BMS) would be unable to inform the user when the vehicle needs to be charged or what can be done to improve battery capacity.

A few indirect methods have been discovered to measure the SOC.

(1) Chemical method : It is applicable only to cells that give access to their electrolytes .

The SOC can be measured from specific gravity or the pH of the electrolyte.

((2) Voltage method : It measures the present voltage of the battery to find its SOC using the discharge characteristics of the voltage vs SOC. It is not preferred method because temp variations are not accounted for in this method which can cause the terminal voltage of a cell to vary from its OCV.

(3) Current integration method : It involves measuring the amount of current entering and leaving the battery, integrated over time. A device called a coulomb counter will measure the current supplied or removed over a period of time , and will compare it t the pre programmed capacity of the battery, hence determining the current SOC.

The figure below shows how SOC can be modelled . The amount of current entering /leaving the battery is integrated over time and the effect of temperature on capacity is also accounted for by using a 1-D lookup table.

where

Q = nominal cpacity of cell

n = present efficiency of cell

i(t) = current flowing in/out

• Although this is one of the most common ways of measuring SOC, it's still suffers from a lack of reference point.

• The SOC needs to be recalibrated regularly back to 100% every time a battery is fully charged and this is dependent on how accurately the sensor determines a fully charged cell.

• This method also does not consider the changing efficiency of the same which is dependent on how much is the charging and discharging current.

• Which is greater charge or discharge is the temperature of the cell increases which affects the efficiency.

• In addition over time the pre-declared capacity(Q) and efficiency of a cell reduces so reduction in cell cycle life also affects the SOC measurement.

For example we can look into the project file be downloaded. A BMS come in the file is represented below

BMS algorith models, protects , reports the measurement from battery pack.

By clicking on BMS ECU get the following subsystem

By clicking on the SOC t estimation Block we get,

From above figure we click coulumb counting block

A subsystem will open when we click on coulumb counting

• This system does the estimation by coulomb counting equation mentioned above.

• Advantage of coulomb ccounting method is it simplicity and low computational cost.

• Temperature in current from the battery is given as input.

• Current signal is given to again block and temperature is given to capacity since it carries according to temperature.

• 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.