Week 7 State of charge estimation

Objective -

For the model - Battery Systems

• To simulate the three test cases from harness dashboard and compare the results.
• What is coulomb counting?
• To explain how BMS implements coulomb counting for SOC estimation in above model.

Model of Harness Dashboard -

Blocks Used -

• Rotary Switch - The Rotary Switch changes the value of the connected block parameter to several specified values during simulation.
• State Request - It provides the required state needed for the simulation.
• Lamps - The Lamp block displays a color that indicates the value of the connected signal.

Subsystems - BMS_ClosedLoop

• Subsystem - BMS ECU
  • In this subsystem, the control of the battery is done.
  • Here, Current Power Limits is calculated.
  • SOC estimation is done.
  • State of Machine is determined.
  • Also the balancing techniques is controlled from this subsystem.

• Subsystem - PLANT
  • In this subsystem, Battery module is present.
  • The charging of the battery is controlled using pre charging circuit present in this subsystem.
  • The charging or discharging of the battery is controlled from Charge _Load subsystem.

Test Case - 1)

• Select test case 1 in Test Sequence Variant.

• And Run the simulation.
• The test sequence editor shown the below states
  • Driving for 3000 seconds
  • Balancing for 1000 seconds
  • Charging and Balancing for 5000 seconds

• After the simulation all lamps are lit up in green color which shows no faults occur during simulation.

• The simulation results are

• From these graph, we can conclude that
  • During driving state the battery voltage and current fluctuating according to requirement.
  • The SOC decreases in this state and cell tempreature increases.
  • In the Charging state, Cell voltage and current increases rapidly.
  • Also the cell tempreature increases at a faster rate.
  • During Standby state, the voltage level is almost constant after balancing is done.
  • The cell current becomes constant after decrease to some extent.
  • As the battery is in idle condition the temperature also decreases.

Test Case - 2)

• Select test case 2 in Test Sequence Variant.

• And Run the simulation.
• The test sequence editor shown the below states
  • Driving for 10000 seconds.

• After the simulation all lamps are lit up in green color which shows no faults occur during simulation.

• The simulation results are

• From these graph, we can conclude that
  • During driving state the battery voltage fluctuating according to requirement.
  • The cell current also fluctuates according to the voltage level.
  • The cell tempreature keeps on increasing as the battery is used in driving state only.
  • The SOC level decreases in almost linearly.
  • The cell balancing is not happen in this state.

Test Case - 3)

• Select test case 3 in Test Sequence Variant.

• And Run the simulation.
• The test sequence editor shown the below states
  • the only state in this test is Charging state.

• After the simulation all lamps are lit up in green color which shows no faults occur during simulation.

• The simulation results are

• From these graph, we can conclude that
  • As only charging of battery is done in this case.
  • When the cell voltage level reaches maximum cell voltage i.e. 4.2 V cell balancing is done.
  • After cell balancing the cell voltages becomes 4.1 V.
  • The cell current decreases during charging and becomes zero after cell balancing procees.
  • The cell temperature increases when the cell voltage level is increasing.
  • As the balancing starts cell temperature starts decreasing.

Coulomb Counting -

• The Coulomb counting method measures the discharging current of a battery and integrates the discharging current over time in order to estimate SOC.
• Coulomb counting method is done to estimate the SOC(t).
• It is estimated from the discharging current I(t) and previously estimated SOC values SOC(t-1).
• SOC is calculated by the following equation

`SOC(t) = SOC(t-1) + (intI(t)dt)/(Total Capacity)`

• There are several factors that affect the accuracy of Coulomb counting method such as
  • temperature
  • battery history
  • discharge current
  • cycle life

Modified Coulomb Counting -

• To improve the Coulomb counting method, a new technique called modified Coulomb counting method is proposed.
• The modified Coulomb counting method uses the corrected current to improve the accuracy of estimation.
• The corrected current is the function of discharging current.
• There is a quadratic relationship between the corrected current and discharging current of battery.
• By practice of experimental data, corrected current is calculated by the following form

`I_c(t) = k_2I(t)^2 + k_1I(t) + k_0`

• where, `k_2, k_1 and k_0` are constant values obtained from the practice experimental data.
• In modified Coulomb counting method, SOC is calculated by the following equation

`SOC(t) = SOC(t-1) + (intI_c(t)dt)/(Total Capacity)`

• The experimental results show that the accuracy of the modified Coulomb counting method is superior to the conventional Coulomb counting method.

Implementation of Coulomb Counting for SOC Estimation -

• The SOC Estimation is done by BMS ECU.

• The SOC Estimation subsystem is shown below

• The coulomb counting subsystem contains following blocks
  • Gain - The Gain block multiplies the input by a constant value.
  • 1-D Lookup Table - It evaluate a sampled representation of a function in N variables.
  • Product - It multiply and divide scalars and nonscalars or multiply and invert matrices.
  • Discrete Time Integrator - It perform discrete-time integration or accumulation of signal.

• Gain block is used to convert the current rate value from ampere per seconds to ampere per hour.
• The battery capacity values are provided from Lookup Tables.
• The ratio of Current and Capacity is integrated using time integrator.
• The output of integrator gives the SOC value.