Battery Life Estimation Using Event-Count Profiles
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Solution Overview
Problem
Existing battery life estimation methods are inaccurate due to limited memory capacity in BMS systems, which fail to store time-dependent factors affecting battery deterioration, leading to incomplete data and poor life prediction.
Innovation Solution
A battery system with a detection device and BMS that estimates state of charge (SOC) and generates a virtual scenario based on physical state data, using a scenario generator, corrector, and estimator to simulate battery operation and accurately predict battery life through Monte-Carlo simulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If battery life estimation uses detailed time-sequence data, then estimation accuracy improves, but memory capacity requirements increase
Solution Approach 1:
The patent extracts only the essential time-sequence information needed for battery life estimation, separating critical temporal patterns from redundant data. By extracting key temporal features rather than storing complete detailed logs, the system achieves accurate estimation while reducing memory requirements.
Solution Approach 2:
Instead of storing complete detailed battery operation data and then analyzing it, the patent inverts the approach by directly modeling and storing time-sequence patterns in a compressed format. This inversion allows the system to capture temporal relationships without storing the full original data set, resolving the contradiction between accuracy and memory usage.
2Quantity of substance
If event count format is used to store battery data, then memory capacity is reduced, but time sequence information is lost
Solution Approach 1:
The patent introduces an intermediary data structure that bridges event count format and time-sequence information. This intermediary format encodes temporal relationships within aggregated data, allowing the system to maintain compressed storage while preserving the time sequence information necessary for accurate battery life estimation.
Data Source
AI summary
A battery system includes: a battery; a detection device to detect a voltage, a current, and a temperature from the battery; and a battery management system (BMS) to: estimate a state of charge (SOC) based on the voltage, the current, and the temperature detected from the detection device; store a profile generated by measuring a physical state of the battery in an event count format based on battery state data including the voltage, the current, and the temperature and the SOC; generate a virtual scenario for driving a representative battery based on the profile; and estimate a life of the battery through the virtual scenario.