AI Engine for Vehicle Battery Performance Analysis

ChangeBridge: Patent Apps - Business Methods (G06Q)

Detected March 26th, 2026

Summary

The USPTO has published a new patent application detailing an AI engine designed to categorize vehicles and analyze battery performance. The application, filed by EATRON TECHNOLOGIES LIMITED, outlines methods for generating recommendations to enhance battery management strategies and determine power consumption.

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What changed

This document is a patent application (US20260087408A1) from the USPTO, assigned to EATRON TECHNOLOGIES LIMITED. It describes a computer-implemented method utilizing an AI decision engine to categorize vehicles based on factors like age, temperature, usage, and battery health. The engine analyzes battery performance metrics (charging habits, discharge rates, state of health, etc.) and generates recommendations for improving battery management and power consumption, accounting for the vehicle's current state.

As this is a patent application, it does not impose direct regulatory obligations or compliance deadlines on entities. However, it signals potential technological advancements in AI-driven battery management systems, which may be relevant for manufacturers in the automotive and technology sectors developing or utilizing such systems. Compliance officers should note this as a disclosure of novel technology rather than an actionable regulatory requirement.

Source document (simplified)

← USPTO Patent Applications

Systems and Methods for Using an Artificial Intelligence Decision Engine to Extend the Lifespan of Batteries

Application US20260087408A1 Kind: A1 Mar 26, 2026

Assignee

EATRON TECHNOLOGIES LIMITED

Inventors

MUHARREM UGUR YAVAS, CAN KURTULUS, ALI IBRAHIM OZKAN

Abstract

In one aspect, a computer-implemented method for executing an artificial intelligence (AI) engine, including executing a categorization model configured to categorize, into categories, vehicles based on factors comprising age, temperature conditions, usage patterns, battery health metrics, or some combination thereof, executing a behavior analysis model configured to analyze behavior of the vehicles in each of the categories to identify battery performance metrics including charging habits, discharge rates, charge rates, state of charge, state of health, state of power, or some combination thereof, executing a recommendation generation model configured to generate, based on the battery performance metrics, recommendations for enhancing battery management strategies, wherein the recommendation generation model accounts for a current state of a vehicle to suggest actions to improve battery health; and executing a battery model configured to determine power and energy consumption based on the recommendations generated by the recommendation generation model.