Battery State of Charge Prediction Using Open Circuit Voltage
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for predicting the State of Charge (SoC) of lithium-ion batteries are inaccurate due to aging effects and reliance on artificial parameters, failing to provide true SoC estimation and considering capacity fade and Open Circuit Voltage (OCV) changes.
Innovation Solution
A method and battery system that estimates SoC using an Open Circuit Voltage (OCV) model defined by internal parameters derived from battery voltage, load current, and initial SoC, accounting for aging effects, with a battery management controller predicting SoC based on OCV and displaying remaining battery life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing techniques use nonlinear adaptive filter along with single particle model to estimate SoC, then the estimation can be performed, but the filter introduces artificial parameter dependencies and physics that alter values of parameters, reducing reliability and accuracy
Solution Approach 1:
The patent extracts and removes the artificial nonlinear adaptive filter component from the SoC estimation system. By eliminating this filter that introduces artificial parameter dependencies, the invention directly measures and uses actual battery parameters (OCV, capacity, current) without alteration, thereby resolving the contradiction between operational capability and measurement precision.
Solution Approach 2:
The patent replaces the complex nonlinear adaptive filter mechanism with a simpler direct measurement and calculation approach. Instead of using a filter that processes and alters signals, the invention directly measures OCV and capacity fade, then calculates SoC using fundamental battery equations, substituting the artificial filtering mechanism with a physics-based direct calculation method.
2Ease of operation
If existing techniques estimate SoC for fresh cells without considering aging effects, then the estimation can be performed, but the OCV changes due to aging are not accounted for, reducing true SoC estimation accuracy
Solution Approach 1:
The patent implements a dynamic SoC estimation method that adapts to battery aging. By continuously measuring OCV and capacity fade during battery operation and updating the estimation model accordingly, the system maintains accuracy for both fresh and aged batteries. The dynamic adjustment of parameters based on actual aging effects resolves the contradiction between ease of operation and reliability for aged batteries.
Solution Approach 2:
The patent changes the estimation parameters to account for battery aging by incorporating OCV drift and capacity fade measurements. Instead of using fixed parameters for fresh cells, the invention dynamically adjusts parameters based on measured aging effects, allowing accurate SoC estimation across the entire battery lifecycle from fresh to aged states.
3Duration of action of stationary object
If battery capacity decreases due to repeated cycling and side reactions, then the battery operates longer, but the total capacity decreases requiring more frequent charging
Solution Approach 1:
The patent implements a feedback mechanism that continuously monitors battery capacity fade through OCV measurements and cycling data. By providing real-time feedback on actual capacity degradation, the system enables accurate SoC estimation that adapts to the reduced capacity, allowing users to understand the true remaining capacity and charge status despite the decreasing total capacity over time.
Data Source
AI summary
A method and apparatus for predicting a state of charge (SoC) of a battery includes estimating an open circuit voltage of the battery based on an open current voltage model, where the open current voltage model is defined by internal parameters that are derived from a battery voltage of the battery, a load current of the battery for a load, or a first SoC of the battery, or any combination thereof; and predicting a second SoC based on the estimated open current voltage.