A method and system dynamically predicting driving range of vehicles is disclosed. In some embodiments, the method includes dynamically determining real-time values corresponding to in-transit parameters associated with vehicle; and determining, via trained Machine Learning (ML) model, variance in in-transit parameters when compared with pre-defined parameters. Determining the variance includes identifying overlapping subset of parameters between in-transit parameters and pre-defined parameters; identifying non-overlapping subset of parameters between in-transit parameters and pre-defined parameters; determining difference in each of the real-time values determined for overlapping subset of parameters with corresponding optimal value; and computing variance based on non-overlapping subset of parameters and difference in real-time values determined for the overlapping subset of parameters. The method may include determining, via trained ML model, percentage deviation from absolute driving range associated with target vehicle based on determined variance; and predicting, via trained ML model, current driving range for vehicle based on identified percentage deviation.
METHOD AND SYSTEM FOR DYNAMICALLY PREDICTING DRIVING RANGE OF VEHICLES
2024-06-13
Patent
Electronic Resource
English
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