Estimating the battery capacity using current power consumption and battery percentage
Firstly, a common chemical battery discharging from 95% to 35% in 1 second is undergoing a very deep discharge and its discharge profile will be very different from a slow steady discharge, e.g. 95% to 35% within 10 hours. Secondly, inferring from a very small snippet of the charge process (2% change) may work only if you know exactly which charge profile is being exhibited by the battery during that charge cycle, so that you can identify at which point of the charge cycle is the battery right now.

For most chemical batteries, the current consumption by the load determines the discharge profile and hence the capacity at a given point of time in the future. Since this is usually non-linear, and the slope varies at different points of the discharge profile, a linear regression would not be a good fit. I would recommend trying out a polynomial regression fit on the discharge profile. Multivariate adaptive regression splines should also work well. Similarly, the rate of charging determines the charge profile/characteristic curve.

You could fit multiple models, one each for each type of charge profile (e.g. deep discharge, slow discharge, etc.) and then select the appropriate model based on the current status of the battery, to predict the future state.

To understand this process for a lead acid battery, refer to these -


http://scubaengineer.com/documents/lead_acid_battery_charging_graphs.pdf and,
http://batteryuniversity.com/learn/article/how_to_measure_state_of_charge.