Battery system management through non-linear estimation of battery state of charge

This invention helps manage battery systems by observing their real-world charging and discharging behavior over time. It uses this actual performance data to create mathematical predictions of how the battery *should* perform across its full charge range. Based on these predictions, it provides instructions for operating the battery, and notably, it does this without needing to know the specific type of battery being used.

Why it matters: Filed before the widespread adoption of advanced AI/ML for predictive modeling. The claims cover battery management without specific battery type knowledge, which is now more robustly achievable with sophisticated machine learning models that can generalize from diverse performance data.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, non-linear estimation algorithms

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