Battery Life Estimation Using Degradation Master Data
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Solution Overview
Problem
Existing methods for estimating the life of lithium ion secondary batteries are inadequate, as they primarily focus on single conditions such as cycle life or storage life, failing to accurately account for mixed states of use, leading to inaccurate degradation predictions.
Innovation Solution
A method and device that calculate battery degradation estimation values by using degradation master data, considering temperature and battery state conditions, allowing for accurate estimation of battery life even under varying conditions like charge cycles, preservation, and environmental temperatures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If single condition measurement (cycle life or preservation life only) is used for battery life estimation, then the measurement and evaluation process is simplified, but the estimation accuracy deteriorates because actual battery usage involves mixed states of both cycles and preservation
Solution Approach 1:
The patent segments battery degradation into two distinct components: cycle degradation (from charge-discharge cycles) and preservation degradation (from storage over time). By separating these degradation mechanisms, the system can independently measure and evaluate each component, then combine them to achieve accurate mixed-state life estimation without oversimplification
Solution Approach 2:
The patent introduces a state-of-health (SOH) parameter that evolves differently under cycle conditions versus preservation conditions. By tracking SOH changes under both conditions and using degradation rates specific to each state, the system accurately models mixed-state battery aging while maintaining practical measurement feasibility
2Device complexity
If existing degradation estimation methods are used, then the calculation process is simple, but the degradation prediction accuracy deteriorates under varying conditions such as temperature changes and mixed usage states
Solution Approach 1:
The patent employs dynamic degradation rate models that adapt to changing conditions. Instead of fixed degradation rates, the system calculates time-varying degradation rates based on actual temperature profiles, charge-discharge patterns, and state-of-health evolution, enabling accurate predictions under varying operational conditions while maintaining manageable calculation complexity through structured modeling approaches
Data Source
AI summary
A method of estimating a battery life includes: for a secondary battery having a degradation rate R when X days have elapsed after initial charge of the secondary battery, calculating a degradation estimation value (X+Y) days after the initial charge from degradation master data, the degradation master data being identified with use of conditions of temperature T provided for the calculation and a battery state S provided for the calculation; and deriving number of elapsed days Xcorr giving the degradation rate R based on the identified degradation master data, and calculating the degradation estimation value (Xcorr+Y) days after the initial charge from the identified degradation master data.