Battery failure prediction
A sensor-driven, machine learning-based system predicts battery failures in vehicles by analyzing driver behavior and battery conditions, enabling proactive maintenance and cost optimization.
Patent Information
- Authority / Receiving Office
- GB · GB
- Patent Type
- Patents
- Current Assignee / Owner
- AVATHON INC
- Filing Date
- 2021-08-05
- Publication Date
- 2026-07-08
AI Technical Summary
Existing technologies lack effective methods for predicting battery failure in vehicles, which can lead to unexpected breakdowns and inefficiencies, particularly in vehicles with battery packs that experience varying usage patterns due to different drivers.
A system utilizing sensors to collect data during discharging and recharging operations, coupled with machine learning models to analyze driver behavior and battery conditions, predicts battery failure timelines and identifies potential failure mechanisms, enabling proactive maintenance scheduling and resource allocation.
The system accurately forecasts battery failures, allowing for timely maintenance, reducing downtime, and optimizing maintenance and warranty costs based on driver-specific usage patterns, thereby enhancing vehicle reliability and operational efficiency.
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