Battery Expected Life Determination via Segmented Age Factor Modules
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Solution Overview
Problem
Current methods lack an effective way to determine the expected life of batteries, particularly in hybrid electric vehicles and plug-in hybrid electric vehicles, which is crucial for ensuring they meet performance criteria during both cycling and resting periods.
Innovation Solution
A system and method that calculate an expected life of a battery by generating age factor values based on user-input parameters such as cycle period, resting life, and operational life, using modules to determine when the battery will begin to fail to meet performance criteria, and displaying the expected life for user input and decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If battery life is extended through multiple propulsion systems, then the battery must satisfy performance criteria during both cycling and resting periods, but current methods lack an effective way to determine the expected life of the battery
Solution Approach 1:
The patent segments the battery life determination into three distinct age factor modules: first age factor module for cycling conditions, second age factor module for resting conditions, and third age factor module for combined conditions. Each module independently evaluates specific aspects of battery degradation, and their results are integrated to provide a comprehensive expected life determination.
2Duration of action of moving object
If the battery is required to meet performance criteria during continuous operation including both cycling and resting, then the operational life requirement increases, but determining when the battery will begin to fail becomes more complex
Solution Approach 1:
The system divides the complex life determination into separate modular components: first age factor module handling cycling parameters, second age factor module handling resting parameters, and third age factor module integrating both. This segmentation reduces complexity by allowing each module to focus on specific aspects rather than handling all parameters simultaneously.
Solution Approach 2:
The third age factor module serves multiple functions by integrating results from both the first and second age factor modules, and by accommodating different combinations of cycling and resting periods. This multi-functional module provides a unified expected life determination regardless of the specific operational profile.
Data Source
AI summary
A method includes: generating a first age factor value for a battery based on: a cycle period of the battery; a required operational life of the battery; and a cycle life of the battery. The method further includes generating a second age factor value for the battery based on: the required operational life; and a resting life of the battery. The method further includes generating a third age factor value for the battery based on: the required operational life; the first age factor value; the second age factor value; and at least one of an expected period of cycling of the battery during the required operational life and expected period of resting of the battery during the required operational life. The method further includes: generating an expected life of the battery based on the required operational life and the third age factor value; and displaying the expected life.