SOC Estimation Device Using Dynamic OCV Curve Weighting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing SOC estimation methods for secondary batteries face inaccuracies due to hysteresis in the correlation curve between State of Charge (SOC) and Open Circuit Voltage (OCV), especially when the battery is stopped for a long period, leading to significant errors in SOC estimation upon resumption of use.
Innovation Solution
The SOC estimation device employs relational formulas that weight the correlation curves between SOC and OCV based on the magnitude of the actually measured OCV and the charge/discharge currents, adjusting weights according to the charging or discharging process to account for the stopped state and material characteristics of the battery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single correlation curve between SOC and OCV is used for estimation, then the device complexity is reduced, but measurement precision deteriorates due to hysteresis effects
Solution Approach 1:
The single correlation curve is segmented into multiple correlation curves corresponding to different SOC ranges. Each correlation curve is associated with specific weight coefficients that are applied based on the current SOC range, allowing the system to account for hysteresis effects while maintaining manageable complexity through range-based segmentation.
Solution Approach 2:
The estimation method dynamically selects and applies different weight coefficients based on the current SOC range and whether the battery is charging or discharging. This dynamic adaptation allows the system to switch between different correlation characteristics without requiring complex real-time curve fitting, resolving the contradiction between simplicity and accuracy.
2Ease of operation
If standard correlation curves are used without considering stopped state, then the ease of operation is maintained, but measurement precision deteriorates after long stopping periods
Solution Approach 1:
The system pre-calculates and stores multiple correlation curves and weight coefficients for different SOC ranges and states (charging/discharging). When the battery is stopped, the system can immediately apply the appropriate pre-prepared correlation characteristics without requiring complex real-time adjustments, thus maintaining ease of operation while improving accuracy after stopping.
Solution Approach 2:
The method changes the parameters (weight coefficients) of the correlation curves based on the battery state (stopped vs. operating) and SOC range. By adjusting these parameters rather than changing the entire estimation methodology, the system maintains operational simplicity while adapting to different states including stopped conditions.
3Measurement precision
If multiple correlation curves with different weights are used for each SOC range, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system uses dynamic selection of weight coefficients based on current SOC range and battery state (charging/discharging). This dynamic approach allows multiple correlation curves to be managed through a systematic rule-based selection process rather than requiring complex adaptive algorithms, thus improving precision while controlling complexity through structured dynamics.
Solution Approach 2:
Instead of changing the fundamental estimation methodology, the system changes the parameters (weight coefficients) of existing correlation curves based on SOC range and state. This parameter-based approach allows multiple curves to be utilized effectively without proportionally increasing system complexity, as the same basic estimation framework is reused with adjusted parameters.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for accurate SOC estimation both during use and after the battery has been stopped, reducing errors and ensuring safe charging/discharging practices by considering the battery's state and material properties.
Implementation Method 1
a hysteresis may occur in which a correlation curve indicating a relationship between the SOC and the OCV differs between a charging process and a discharging process
Data Source
AI summary
A State of Charge (SOC) estimation device is provided for a secondary battery in which a correlation curve indicating a relationship between an SOC and Open Circuit Voltage (OCV) differs between a charging process and discharging process. The SOC estimation device estimates the SOC based on a relational formula in which as measured OCV increases, weights are assigned to the correlation curve for the discharging process, and as the measured OCV decreases, weights are assigned to the correlation curve for the charging process. Thus, the SOC estimation device provides accurate SOC estimates regardless of whether the secondary battery is being used or not.