This paper proposes a way to augment the existing machine learning algorithm applied to
state-of-charge estimation by introducing a form of pulse injection to the running battery
cells. It is believed that the information contained in the pulse responses can be interpreted
by a machine learning algorithm whereas other techniques are difficult to decode due to the
nonlinearity. The sensitivity analysis of the amplitude of the current pulse is given through
simulation, allowing the researchers to select the appropriate current level with respect to …

ACCURATE state-of-charge (SoC) estimation is necessary for optimal battery management
and safe and reliable utilization of battery powered devices, such as electric vehicles (EVs)
and grid level energy storage. For lithiumion batteries, in particular, SoC estimation is
difficult because the relationship between the SoC and the opencircuit voltage (OCV) is
nonlinear, as can be seen in Figure 1. In certain ranges of the SoC in Figure 1, the voltage is
completely flat with respect to the SoC due to phase changes occurring within the system; …