Week 7 State of charge estimation

AIM:

To Simulate 3 cases from harness dashboard and compare the result plots.

To explain how BMS implements Coulomb counting to estimate SOC.

OBJECTIVE:

The objective of the assignment is to learn what coulomb counting is, how that is implemented in BMS and how it helps to estimate SOC.

MODEL SETUP:

The above model has the Battery Management System (BMS) ECU block which does the computations. The Plant block represents a battery pack.

This is the dashboard which represents the dashboard in the vehicle. It indicates the battery states - Balancing, Charging and Driving. There are LEDs to indicate any faults or errors and for other purposes.

PROCEDURE:

• There are 3 test cases or sequences. Each sequence is with a different algorithm.
• Test case 1 is Driving-Balancing-Charging-Balancing.

• Test case 2 is Driving-Charging.

• Test case 3 is Charging only.

• The simulation is done with each of the sequences and the results are analysed.

RESULTS:

Test case 1:     Driving-Balancing-Charging-Balancing

Graph 1 indicates the cell voltage of all the cells present within the battery pack. When the simulation begins, initially the vehicle is in a driving state and the SOC will decrease for this time period. We first observe that cell voltages are changing as the current is flowing in and out of the cell. At the beginning of the simulation, the voltages are slightly different because we initialize the model with a slight associate of imbalance; the voltages are deflecting and then there is a balance in the voltage. Then there is a sudden rise in cell voltages till they reach 4.2 V. This is because after a time period of 3000 seconds the next step is balancing mode and the vehicle is in standby condition. After another 1000 seconds, the vehicle is in the charging phase and the battery's SOC increases almost to 100%. At the end of the simulation, the values converge towards one another. This indicates that voltages are getting balanced but still at the end there is a small difference in their voltages and the voltage line flows between 4 to 4.2 V. 

Graph 2 shows charging state during the constant current phase current. Graph 3 shows the temperature traces showing the significant discrepancy between the hottest and coldest cell. The reason is mainly because of symmetry in the merger layer in terms of thermal behavior. The cell no 6 is significantly hotter than cell no 1 because it is thermally insulated on one side. Even if the maximum temperature reached during the simulation is not concerned in terms of safety, the temperature difference at cell no 6 at its higher temperature will eventually cost much faster degradation of cell 6 compared to cell 1. This leads to undesirable and unevenness in cell conditions. Therefore we need an active thermal management system to keep thermal differences within a few degree Celcius. Graph 5 shows the SOC of battery cells. The initial SOC is 75%, however, the simulation estimates need to initialize it to 80% to set their capability to recover. The other scopes indicate the bms state at each of the balance command signals respectively.

Test case 2:     Drive-charge, High-temperature fault

In graph 1, the initial state of the voltage of all the cells are deflecting in the same manner and dropping slightly. It has 4 fluctuation zones and in between each of these fluctuating zone, they are stable for a while. The cells are initially at 80% SOC and then they're falling at different time periods. to set their capability to recover. Other scopes indicate BMS state at each of the conditions.   

Test case 3:     Charging

From the above graphs all the cells are initiated with at different voltages the where the 6 the one having the higher voltage of 4.2 V and the 1st one having near about 4.1 v and remaining falling under this range BMS on charging state throughout the simulation. So the voltage graph moves along in a straight line because the voltage supply continues .There are some deflection of voltage lines of different cells but that is a very less amount of change in voltage. At the end of the simulation BMS tries to balance the voltage. The battery pack current is initiated with 20 A and then it falls to zero current till the end of simulation. Then there is constant current because the battery is put in charging.

Graph 3 shows the temperature of the cells. The cells initiate at 287-degree Celcius temperature and then all the cells gradually see a decrease in temperature. The temperature difference at cell no 6 at its higher temperature will eventually cost much faster degradation of cell 6 compared to cell 1 leading to undesirable and unevenness in cell condition. therefore need an active thermal management system to keep thermal differences within a few degree Celcius. The initial SOC of three different cells is at 80% as the. As the system is put on a charging state the SOC increases  to 100% The other scopes indicate the bms state at each of the balance command signals respectively. bms on charging state and battery command passing signal between 0 to 1.

Coulomb counting:

The Coulomb counting method is a method used to measure the discharging current of a battery. The method integrates the discharging current over time to estimate SOC. The Coulomb counting method is carried out to estimate the SOC at time t, which is estimated from the discharging current, I(t), and previously estimated SOC values, SOC(t-1). SOC is calculated by:

`SOC(t) = SOC(t-1) + (I(t))/Q_n Delta t`

There are several other factors affecting the accuracy of the Coulomb counting method including temperature, discharge current, battery history, and cycle life.

Limitations of coulomb counting: Coulomb Counting can be a very accurate technique, but it has its limitations:

• Leakage current within a cell does not go through the current sensor and is therefore not taken into account.

How BMS implements coulomb counting for SOC estimation:

• The system does the estimation by coulomb counting equation. The advantage of the coulomb counting method is its simplicity and low computational cost.
• Inside the BMS ECU block, we have the SOC estimation block.

• Withing the SOC estimation block, we have the Coulomb counting, which is a sub-system.

• Within the coulomb counting, the SOC estimation is done.
• Temperature and current from the battery is given as inputs for coulomb counting.

• Current signal is given to a gain block.
• 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.
• This way the SOC is estimated.

OBSERVATIONS:

Test case 1:

• During Charging the Battery pack voltage is increased up to 4.2V.
• The input cycle can be seen in the BMS_State plot in which the vehicle initially undergoes driving, then charging till SOC becomes 90% and then later in the standby state.
• The cell temperature increases during the driving and charging cycle and starts falling off in standby mode.
• The SOC drops to less than 50% after the driving cycle and then later put into charging until SOC Reaches 100%.
• The current supplied to the vehicle during the driving phase can be seen in the current plot.

Test case 2:

• After 10,000 sec when the driving cycle is over, the fault condition occurs and so the SOC does not increase even for the charging phase.
• Cell temperature increases during driving, and since it is higher than recommended, BMS stops the battery from charging, so we can see a gradual decrease in temperature

Test case 3:

• The SOC increases from 80 to 100% and then remains in standby mode.
• During charging SOC increases from 80 to 100%, temperature increases during charging and is reduced in the standby state of the BMS.

CONCLUSION:

Thus from the assignment we understood the coulomb counting and how this method is used to estimate the SOC of the battery.