Estimating a battery’s State of Charge is a challenging task, and many different types of algorithms have been used to try to achieve this with the lowest accuracy error. Some of the most common algorithms used today include: voltage correlation, voltage + IR correlation, and coulomb counting. By comparing these generic gauging algorithms to TI’s Impedance Track algorithm shows why Impedance Track has the highest accuracy battery gauging.

Voltage correlation is a very basic method for gauging batteries. This algorithm takes the OCV (Open Circuit Voltage) of the battery and references this value to a look-up table of voltages, where each voltage corresponds to a different SOC (State of Charge).

Figure 2-1 OCV Look-up Table and Graph

For example, Figure 2-1 shows what a voltage look-up table can look like for a lithium-ion battery. Using the voltage correlation method, if the OCV of the battery is 3.72 volts, then the gauge can predict that the SOC at that given time is 50%.

While voltage correlation is a very easy method to implement, the correlation does come with many drawbacks. Voltage correlation is only able to report the SOC, and is not be able to report other important data like SoH (State of Health), Remaining Capacity, and Remaining Run Time. Also, SOC is not adjusted for important factors like discharge rate, temperature, and the age of the battery.

Because of this factor, we recommend using voltage correlation for applications where the battery has long periods of rest where the OCV can be taken to accurately determine SOC and or the current is low enough where an OCV is still accurate.