Battery Discharge Capability Estimation via Equivalent Circuit Model
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Solution Overview
Problem
Current methods fail to accurately determine the state of function (SOF) of a battery when starting up a load, which is crucial for ensuring the battery's discharge capability, especially as it relates to the stability of the load current, and require cumbersome impedance measurements over a wide frequency range, making real-time adjustments difficult.
Innovation Solution
A method using an equivalent circuit model to estimate the battery's discharge capability by setting a state vector with element parameters, measuring current and voltage, and applying these parameters to predict voltage under a specific current pattern, comparing it to a tolerance to determine discharge capability, while also incorporating impedance measurements and corrections based on current, temperature, and state of charge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If impedance measurement over a wide frequency range is performed to predetermine element parameters, then prediction accuracy of discharge capability is improved, but measurement time and calculation load increase significantly
Solution Approach 1:
The patent extracts only the necessary element parameters (R0, R1, C1) from the full impedance spectrum that are most critical for predicting discharge capability under load current patterns. By focusing on a reduced set of parameters rather than determining all parameters across the entire frequency range, the measurement time and calculation load are significantly reduced while maintaining adequate prediction accuracy for the specific application.
Solution Approach 2:
The patent applies partial action by performing impedance measurement only at selected frequency points rather than continuously across the entire frequency range. This partial measurement approach captures the essential battery characteristics needed for discharge capability prediction without the excessive time and computational resources required for complete wide-band impedance characterization.
2Measurement precision
If impedance measurement over a wide frequency range is performed to predetermine element parameters, then prediction accuracy of discharge capability is improved, but calculation load increases
Solution Approach 1:
The patent extracts only the essential element parameters (R0, R1, C1) from the full impedance model that are most influential for predicting voltage response under typical load current patterns. This parameter reduction dramatically decreases the calculation load for real-time discharge capability assessment while retaining the predictive accuracy needed for automotive applications.
Solution Approach 2:
The patent applies partial action by determining only a subset of impedance parameters at selected frequency points rather than performing complete impedance spectroscopy analysis. This partial determination approach reduces the computational complexity and processing requirements while maintaining sufficient accuracy for monitoring battery discharge capability under varying load conditions.
3Ease of manufacture
If element parameters are predetermin ed and memorized, then discharge capability can be evaluated, but the parameters require readjustment with battery aging making the system hard to maintain
Solution Approach 1:
The patent implements a dynamic parameter determination approach where the battery's equivalent circuit parameters (R0, R1, C1) are continuously or periodically updated based on real-time impedance measurements. This dynamic adaptation allows the system to automatically track parameter changes due to battery aging, eliminating the need for manual readjustment and maintaining accurate discharge capability evaluation throughout the battery's operational life.
Solution Approach 2:
The patent incorporates feedback mechanisms where measured impedance data and actual voltage responses under load are used to continuously refine and update the equivalent circuit parameters. This feedback loop ensures that the parameters remain accurate despite battery aging, degradation, or environmental changes, making the system self-correcting and easy to maintain without manual intervention.
4Device complexity
If a simple battery model with few element parameters is used, then calculation is simplified, but the model cannot accurately predict voltage under varying load current patterns
Solution Approach 1:
The patent applies local quality by tailoring the equivalent circuit model complexity to the specific requirements of discharge capability prediction under load current patterns. Instead of using a uniformly simple or complex model across all operating conditions, the patent selects an intermediate model complexity (with parameters R0, R1, C1) that provides sufficient accuracy for predicting voltage response under typical automotive load conditions while keeping the calculation manageable for real-time application.
Data Source
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AI summary
Regarding a method for determining battery discharge capability of the present invention, the optimum state vector X is estimated by extended Kalman filter operation. Using the estimated state vector X, element parameters of an equivalent circuit 21 are renewed to the optimum (step S7). Furthermore, based on the equivalent circuit 21 using the renewed element parameters, at the time of discharging with a predetermined current pattern from a battery 12, a voltage drop ΔV is estimated (step S8). Therefore the discharge capacity of the battery 12 is determined (step S9).