AC Battery SoC Estimation Using Real-Time Impedance and EKF
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Solution Overview
Problem
Conventional methods for calculating the state-of-charge (SoC) of lithium-ion batteries in AC storage systems lack accuracy and require time-consuming calibration processes, involving expensive equipment and lengthy pretesting steps.
Innovation Solution
The proposed solution involves using real-time measurements of battery impedance, either DC or AC, to calculate resistance and capacitance values for an equivalent circuit model, which are then input to an Extended Kalman Filter (EKF) for accurate SoC estimation, eliminating the need for specific testing devices and time-consuming pretesting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional coulombic counting method is used for SoC determination, then the method is relatively easy to perform, but the accuracy is low (about 3% to about 5%) and frequent calibration is required
Solution Approach 1:
The patent combines the coulombic counting method with the extended Kalman filter (EKF) algorithm to create a hybrid SoC estimation approach. The EKF uses the battery's voltage, current, and impedance measurements to correct and refine the SoC estimates from coulombic counting, thereby improving accuracy while maintaining operational simplicity
Solution Approach 2:
The patent introduces an equivalent circuit model (ECM) as an intermediary between the battery and the EKF algorithm. The ECM represents the battery's electrical characteristics through resistors and capacitors, allowing the EKF to accurately estimate SoC by modeling the battery's dynamic behavior without requiring complex direct measurements
2Measurement precision
If extended kalman filter (EKF) method is used for SoC determination, then higher accuracy is provided (about 1% to about 3%), but device complexity and calibration requirements increase
Solution Approach 1:
The patent implements a self-calibrating EKF system that automatically adapts to battery aging and changing conditions. The algorithm continuously updates the equivalent circuit model parameters based on real-time impedance measurements and operational data, eliminating the need for manual recalibration and reducing system complexity over time
Solution Approach 2:
The patent dynamically adjusts the parameters of the equivalent circuit model based on real-time impedance measurements. By changing the resistance and capacitance values in the ECM to reflect current battery state, the system maintains high accuracy without requiring complex recalibration procedures or additional hardware
3Measurement precision
If conventional EKF method is used, then SoC estimation accuracy is improved, but time-consuming pretesting and database building (six months to one year) are required
Solution Approach 1:
The patent performs preliminary characterization of the battery's equivalent circuit parameters during normal operation rather than requiring separate pretesting. The system collects and processes operational data to build the ECM database in real-time, eliminating the need for lengthy offline testing and database construction
Solution Approach 2:
The patent replaces the mechanical/testing-based calibration approach with an algorithmic solution. Instead of physically testing the battery for six months to one year to build a database, the EKF algorithm computationally models battery behavior and learns parameters from normal operational data, dramatically reducing calibration time
4Measurement precision
If real-time impedance measurement method is used, then SoC estimation accuracy is maintained with online updates, but measurement and calculation complexity increases
Solution Approach 1:
The patent makes the power converter serve multiple functions: it not only performs power conversion but also measures battery impedance and provides data for EKF-based SoC estimation. By utilizing existing voltage and current measurements already taken for power control, the system obtains impedance data without requiring separate measurement equipment or procedures
Data Source
AI summary
A storage system configured for use with an energy management system is provided and includes an AC rechargeable battery and a power converter operably coupled to the AC rechargeable battery and configured to calculate an estimate of state-of-charge of the AC rechargeable battery based on at least one of DC impedance of the AC rechargeable battery or AC impedance of the AC rechargeable battery that are measured in real time operation is used to calculate resistance and capacitance values for an equivalent circuit model that in conjunction with previously measured voltage and current are input to an extended kalman filter (EKF). Time consuming testing of the equivalent circuit model in advance is therefore eliminated.