Battery Management System Pattern Table for Accurate SOH Estimation
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Solution Overview
Problem
Current battery management systems struggle to accurately predict the pattern of use for charge and discharge cycles, leading to inaccurate State of Charge (SOC) estimation and reduced State of Health (SOH) maintenance, affecting the efficiency and reliability of battery performance in electric and hybrid vehicles.
Innovation Solution
A battery management system that employs a pattern table with multiple estimation ranges and counters to regularly update SOC estimation parameters, including Open Circuit Voltage (OCV), SOC, and current, to predict the pattern of use and estimate SOH more accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If simple counting method is used when certain SOC or OCV value is exceeded, then the management system is simple to operate, but the accuracy of charge and discharge cycle pattern detection deteriorates
Solution Approach 1:
The invention divides the charge and discharge cycle detection into multiple segments by creating a pattern table with multiple estimation ranges (e.g., 0-30%, 30-60%, 60-90%, 90-100% SOC ranges). Each range has specific detection criteria, allowing the system to accurately track cycles across different operating conditions while maintaining systematic simplicity.
Solution Approach 2:
The system performs preliminary action by pre-establishing a pattern table with multiple estimation ranges and detection criteria before actual battery operation. This pre-configured structure enables the system to automatically and accurately detect charge and discharge cycles without complex real-time calculations, resolving the contradiction between operational simplicity and detection accuracy.
2Device complexity
If accurate pattern of use for battery is not obtained, then the system structure remains simple, but the SOC estimation accuracy and battery reliability deteriorate
Solution Approach 1:
The pattern table segments battery operation into distinct charge and discharge cycles with specific SOC range criteria. By dividing the monitoring task into discrete, manageable segments rather than attempting continuous complex analysis, the system achieves accurate cycle detection and reliable SOC estimation without requiring overly complex system architecture.
Solution Approach 2:
The pattern table acts as an intermediary structure between the simple monitoring system and the complex task of accurate SOC estimation. This intermediate pattern-matching approach enables reliable battery management by translating simple detection operations into accurate cycle pattern recognition, improving reliability without proportionally increasing system complexity.
3Measurement precision
If regular and step-by-step counting of battery SOC is performed with pattern table updates, then the accuracy of SOH estimation is improved, but the device complexity increases
Solution Approach 1:
The pattern table is segmented into multiple estimation ranges with specific SOC thresholds and detection criteria. This segmentation transforms the complex task of continuous SOH monitoring into discrete, rule-based updates, improving measurement precision while keeping the implementation complexity manageable through systematic organization.
Solution Approach 2:
The system performs periodic updates of the pattern table at regular intervals during battery operation. This periodic action ensures accurate SOH estimation by continuously refreshing cycle pattern data without requiring constant complex processing, balancing precision improvement with acceptable device complexity through time-based periodic operation.
Data Source
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AI summary
The present invention relates to a battery management system and a battery management method. The battery management system for managing a battery including at least one cell comprises: an SOH (State of Charge) estimating unit for determining estimation parameters for estimating an SOC of the battery; and a controller for updating a pattern table for estimating a pattern of use on a charge and discharge cycle of the battery, based on the estimation parameters. The pattern table includes a plurality of pattern counters, and the plurality of pattern counters correspond to a plurality of estimation ranges, respectively. The controller determines to which estimation range from among the plurality of estimation ranges the estimation parameters correspond, and updates a value of a pattern counter corresponding to the determined estimation range from among the plurality of pattern counters. The battery management system and the battery management method according to the present invention may regularly update and record a pattern of use for charge and discharge cycles of the battery in order to estimate and analyze an accurate pattern of use for the battery, so as to effectively perform an estimation of the SOH of the battery and maintenance and repair.