It isnt possible to process battery pulse sequence data with only half the SOC data since the "Battery.PulseSequence" object computes the charge and state of charge (SOC) data assuming that the experimental test ranges are 0% to 100% SOC: https://www.mathworks.com/help/autoblks/ref/battery.pulsesequence.html?s_tid=doc_ta#:~:text=using%20the%20assumption%20that%20the%20experimental%20test%20ranges%20is%200%25%20to%20100%25%20SOC.
Interpolating the SOC data to fit in the 0% to 100% range seems to be the only workaround for this issue.
Essentially you could interpolate the SOC data by finding the transfer function of the battery voltage response to the charging current pulse or use a machine learning algorithm to predict battery SOC using your SOC data.
To find the transfer function, you can check out the documentation for the System Identification Toolbox: https://www.mathworks.com/help/ident/transfer-function-models.html
If you plan to go down the machine learning route, you can refer to the following documentation for an example highlighting the use of Gaussian process regression to predict the state of charge of a battery: https://www.mathworks.com/help/stats/predict-battery-soc-using-machine-learning.html
If you have the license for Simscape, you can check out the estimators for battery SOC using the link to the following documentation: https://www.mathworks.com/help/simscape-battery/estimators.html
