Battery Management Controller Using Pattern-Based Prediction

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Solution Overview

Problem

Conventional electronic devices lack an effective method to predict battery charging needs based on battery consumption patterns, charging patterns, and user life patterns, leading to inefficient battery management and potential battery discharge.

Innovation Solution

An electronic device with a memory to store battery consumption and charging patterns, and a controller to collect situation information, including location and time, to predict battery use time and judge chargeability, using a judgment module to determine if battery charging is necessary.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional battery level indication methods are used, then the device can display battery status, but the device cannot predict charging needs or optimize battery management

Engineering Contradiction:

Improvebattery management effectivenessVSAvoidbattery consumption pattern information

Core Design Contradiction:

ReliabilityVSLoss of information

Solution Approach 1:

The system performs preliminary actions by collecting and analyzing battery consumption patterns, charging patterns, and user life patterns in advance. The judgment module predicts future battery status and charging needs before the battery actually depletes, enabling proactive rather than reactive battery management. This resolves the contradiction by transforming passive battery level indication into active prediction based on historical data analysis.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms by continuously monitoring battery consumption patterns and comparing them against stored patterns in memory. The controller receives feedback from the judgment module about predicted battery status and adjusts battery management strategies accordingly. This closed-loop feedback system enables the device to learn from past behavior and optimize future battery management, improving reliability while utilizing previously unused pattern information.

Inventive Principle:

Principle #23Feedback

2Measurement precision

If the device collects and analyzes multiple patterns (battery consumption, charging, user life patterns), then prediction accuracy improves, but system complexity increases

Engineering Contradiction:

Improvebattery use time prediction accuracyVSAvoiddata collection and processing complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system segments the complex analysis task into distinct pattern types: battery consumption patterns, charging patterns, and user life patterns. Each pattern is collected, stored, and analyzed separately by dedicated modules. The judgment module then integrates these segmented patterns to make comprehensive predictions. This segmentation reduces overall complexity by breaking down the monolithic analysis task into manageable, independent components that can be processed separately.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The judgment module serves as an intermediary between the multiple pattern data sources and the final prediction output. It receives processed pattern information from various collection modules, performs the actual prediction analysis, and delivers results to the controller. This intermediary structure simplifies the system architecture by providing a single integration point for multiple data streams, reducing the complexity of direct interactions between numerous components.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Loss of time

If the device uses pattern-based prediction, then battery charging timing is optimized, but more memory and processing resources are required

Engineering Contradiction:

Improvebattery discharge timeVSAvoidmemory storage capacity

Core Design Contradiction:

Loss of timeVSQuantity of substance

Solution Approach 1:

The system applies partial action by selecting and storing only the most relevant pattern information needed for prediction, rather than capturing every possible data point. The judgment module focuses on analyzing key patterns that have the greatest impact on battery behavior prediction. This selective approach extends battery discharge time by enabling accurate predictions without requiring exhaustive data collection and storage, thus optimizing the trade-off between prediction capability and memory resource consumption.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS9784797B2Method for controlling and an electronic device thereof

Publication Date: 2017.10.10 SAMSUNG ELECTRONICS CO LTD

AI summary

Various embodiments of this disclosure provide a power source management method and apparatus of an electronic device. The power source management apparatus of the electronic device includes a memory for storing a battery consumption pattern by situation and a battery charging pattern by situation. A controller is configured to collect at least one of situation information or information for life pattern judgment. The controller is also configured to predict a situation of the electronic device or a life pattern using the collection information and judge a chargeability of a battery. The situation is related with at least one or more of a location and a time.