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 ?

Solution

 BMS

A Battery Management System (BMS) monitors and regulates internal operational parameters, i.e. temperature, voltage and current during charging and discharging of the battery.

In technical terms, the BMS estimates the SoC(State of Charge) and SoH (State of Health) of the battery to improve safety and performance.

It avoids over-charging and over-discharging of the battery pack. This way, it maintains charge level within maximum and minimum allowed capacity to prevent sudden accidents [explosion].

Hence a BMS is a highly crucial device to ensure the safety of the battery and user.

There are many other benefits of using BMS; we will discuss them later in this article.

A BMS is an electronic board consisting of a variety of components and circuitry. After detecting a problem in operational parameters (voltage, temperature etc.) BMS triggers input to the alarm system followed by disconnecting the battery pack from the load or charger.

Benefits of BMS

• Ensure reliable battery operations
• Continuous battery health monitoring to avoid explosion
• Increases the life span of the battery
• Indicates battery level

Why Battery Management  is so important?

Utilising a battery management system is important because it helps you keep track of the performance of your battery pack and alerts you to any faults. But it also allows you to protect your batteries while they’re in use. 

A BMS is capable of tracking the voltage, temperature, and current range in which each cell can safely operate. If the batteries within your pack fall outside of this range, your BMS can detect and then control it. 

This is particularly important when dealing with lithium, as it’s a highly reactive substance. A BMS is a perfect way to monitor lithium performance and is a worthwhile investment. 

Simulink Model of BMS

This model consist of 

BMS ECU(Electronic Control Unit)

1. Charge estimation by  Extended Kalman Filter and uncedented Kalman Filter

There are 3 menthods of charge estimation in the BMS model

a. Coloumb Counting

b. Extended Kalman Filter

c. Unscedented Kalman Filter

Kalman Filter

In statistics and control theory, Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe.

The Kalman filter keeps track of the estimated state of the system and the variance or uncertainty of the estimate. The estimate is updated using a state transition  model and measurements.

Cell Balancing

Cell imbalance is a main significant factor in large battery packs which degrades the performance of the battery to be qualified by state of health (SOH) of battery.The weakest cell (lowest SOH of cell) in a set of seriesconnected cells dominated the overall string strength which causes safety issues and thermal runaway when discharging the battery pack below the limit. Classification of cell balancing into two methods such as passive cell balancing and active cell balancing which is explained in Figure  based on the battery SOC.

For explanation, considering the four cells connected in series in battery pack such as Cell 1, Cell 2 and Cell 3, and Cell 4. Before balancing, the SOC level of cells L1, L2, L3, and L4 were 40%, 60%, 80%, and 100%, respectively. The passive cell balancing technique equalizing the SOC of the cells by the dissipation of energy from higher SOC cells and formulate all the cells with similar SOC equivalent to the lowest level cell SOC specifically 40% of SOC level L1 in Cell 2 as shown in Figure.

Passive Cell Balancing

The high SoC cell is bled off (power is dissipated in the resistor) so that charging can continue until all cells are fully charged. 

Passive balancing allows all batteries to have the same SoC, but it does not improve the run-time of a battery-powered system. It provides a fairly low cost method for balancing the cells, but it wastes energy in the process due to the discharge resistor. Passive balancing can also correct for long-term mismatch in self discharge current from cell to cell.

Active balancing

In Passive cell balancing the excess charge was not made used of, hence it is deemed to be inefficient. Whereas in active balancing the excess charge form one cell is transferred to another cell of low charge to equalize them. This is achieved by utilizing charge storing elements like Capacitors and Inductors.

Cell Balancing Algorithm in Simulink

 Pre Charging And Contracter Arrangement

Pre charge in high voltage DC application limits the high inrush of current during powering mode.High voltage system with large capacitive load  is exposed to high electric current  during turn on time. This current can damage to the entire battery pack. Precharging is added in order to increase the lifespan of electronic components and increase the system reliablity of high voltage system.

Fault management

BMS provide necessary management and control to protect the cell  from going out of tolerance limit and operating condition. This management is precisely used in automotive application due to hash workig condition. The individual cell protection of every cell is very challenging taskthats why automotive industry must be designed to  respond to external fault condition by isolating the battery and resolving the issue caused by fault.

The faults system continously monotoring the voltage , current and temperature of the BMS. 

The current monitoring system measure the amount of current taken inside or given outside the battery.When the time duration of peak current increases  and is more than the fault generation than the system is said to be in fault state.

Charge and Discharge current limit.

Charging and discharging is part of fault calculation and protection is performed by the BMS as per the system is consisdered faulty. The voltage level of six cell is given as input and the  minimum voltage  is used to determine the maximum discharge current and maximum voltage is used find the maximum charging current.

Subsystem of charging and discharging circuit

The voltage is given to discharge current subsysyem and when there is difference between cut of voltage and minimum voltage of cell then maximum discharge current is calculated using resistance of the cell . The minimum discharge current is calculated with the help of cell instantaneous value of resistance , gtemperature and voltage of the cell.

Disccharge current subsystem

Charge current subsystem

Plant

It consist of three main subsystem

1.Battery pack

2.Cell Module

3. Charging and Discharging Load

1. Battery Pack

Cell Module

Six cell are connected in series with temperature sensor

Cell Balancing Circuit

Here passive cell balancing technique is used because it is less complex amd cheaper compare to other balancing technique. Resistors are connected in parallel in order to dissipate the extra charge contained in the cell.

Precharge circuit

The precharge circuit is used to prevent the current inrush  while charging and discharging the cell avoiding spark ignition.

The resistor connected here to limit the extra current flow and capacitor is connected to control the voltage ripple.

Charging and Discharging Load

Charging

If the input state of charging is one then battery is charged via controlled current source

Discharging

The charge given by battery is considered positive and charge given to battery is negative.

The state requirement is checked and and current profile of discharge is made repeating sequence from the mapped variable Battcarnt.

1. Test Sequence

Here simulation is run for 20000 sec. During first 3000 sec is discharging mode then next 1000 second is cell balancing mode or standby mode and then for 5000 second there is charging and balancing mode.

Select test variant as 1

Output harness block

Explanation

All the six cell connected in series and the first plot depicts the cell voltages. For the first 3000 seconds the cell voltage drops due to charging of battery and then go to stand by mode the voltages of the cell got stablizes because of cell balancing got activated and internal behaviour of the cell. Again as cell underwent charging mode voltage get increased and got stablised during standby mode.

The second graph displays about the battery pack current  drawn and given to the battery while charging and discharging of the cell.During charging the  current remains constant  and then it drops the charges during constant voltage mode.

The third  plot displays about the cell temperature of all the cell and got increased while charging and discharging.

Fourth graph shows the input state of the system and fith shows the state of charge of entire battery pack. the soc is calculated by three different  methods, namely coloumb counting, ukf,ekf.

The Soc  curve is decreasing while discharging and increasing while chaging.

The sixth plot show the cell balancing status. The voltage of firstcell is minimum and donot need balancing and other cell have magnitude of 1.

Test case2

Here first 10000 second is driving mode and after that charging mode of battery.

The cell voltage fluctuates from 3.9 v to 3.2v continously. The battery pack current goes to -60A and then rises to 10A.

In te fourth plot simulation runs only for discharging mode where SoC reaches to zeros and simulation stopped at 8962sec.

The soc is calculated by three methods coloumb counting,ukf,ekf.

Here cell balancing do not takes place as simulation runs only for driving mode.

Testcase3

In this case only charging takes place. The cell voltage remains constant throughout 20000sec.

At starting battery current increases to 30A And reduces to 0 at 2000 sec. THe soc was estimated 80% and icreases to 100%  and remains constant.

2. Coloumb  Counting

The coulomb counting method is expedient for state-of-charge (SOC) estimation of lithium-ion batteries with high charging and discharging efficiencies. The charging and discharging characteristics are investigated and reveal that the coulomb counting method is convenient and accurate for estimating the SOC of lithium-ion batteries. A smart estimation method based on coulomb counting is proposed to improve the estimation accuracy. The corrections are made by considering the charging and operating efficiencies. Furthermore, the state-of-health (SOH) is evaluated by the maximum releasable capacity. Through the experiments that emulate practical operations, the SOC estimation method is verified to demonstrate the effectiveness and accuracy.

To determine available capacity, coulomb counting relies on the integration of the current drawn from and supplied to a battery over time, τ∈tot, as given by

where I is the current and η is the efficiency during charge and discharge operations. Coulomb counting is advantageous in terms of a simple structure and its ease of implementation. However, some problems make it difficult to accurately estimate battery SOC by coulomb counting.

Because battery capacity and efficiency are significantly influenced by operating temperature and current direction, these factors should be considered to correct for battery SOC. Sensor accuracy is also important because accumulated errors can lead to a drift in the estimated battery SOC. Furthermore, one of the main problems in coulomb counting is that it is necessary to calibrate the initial battery SOC. In several applications, the initialization involves rest and the initial SOC is estimated based on the voltage inversion method.

2b.BMS implements coulomb counting for SOC estimation 

Implementation of coloumb counting for SOC estimation in BMS.

The discharge signal is converted to physical signal using gain block

The gain block is integrated by1/(30*3600) is applied to the integreter.The temperature data is divided by lookup table with the discharge current rate. the output is then integreted ny discrete time integrater with sample time of 0.1 second to calculate the soc of the batterypack.