Battery State-of-Charge Estimation Using Time-Dependent Resistance
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Solution Overview
Problem
Existing methods for estimating the state of charge (SOC) of a battery are inaccurate due to the inability to directly measure SOC and the complex electrochemical nature of batteries, which are influenced by factors like temperature, current, and internal resistance, leading to inaccuracies in estimating the SOC.
Innovation Solution
A method and apparatus that consider the impact of temperature, current, and discharge duration on battery internal resistance by establishing a more accurate internal resistance model, using a refined correspondence between discharge duration and internal resistance types to estimate SOC with higher precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a Thevenin equivalent circuit model is used with pulse current excitation and least square method to obtain time constant, polarization resistance, and polarization capacitance, then the SOC estimation can be performed using extended Kalman filtering algorithm, but the accuracy is insufficient because the charge transfer resistance and diffusional impedance are not considered
Solution Approach 1:
The patent segments the internal resistance into three distinct components based on time scales: ohmic internal resistance (short time), polarization resistance (medium time), and charge transfer resistance and diffusional impedance (long time). This segmentation allows each resistance component to be measured and compensated separately, improving SOC estimation accuracy while maintaining manageable model complexity.
Solution Approach 2:
The patent adds a time dimension to the resistance measurement by conducting tests at multiple time points (short time, medium time, long time). This temporal dimensioning allows the separation and identification of different resistance components that manifest at different time scales, enabling more accurate SOC estimation.
2Productivity
If only ohmic internal resistance is measured at short time intervals, then the measurement process is simple and fast, but the SOC estimation accuracy deteriorates due to ignoring polarization effects and charge transfer resistance
Solution Approach 1:
The patent implements periodic measurement at three distinct time points during battery operation: short time (for ohmic resistance), medium time (for polarization resistance), and long time (for charge transfer resistance and diffusional impedance). This periodic multi-stage measurement approach ensures comprehensive resistance characterization while maintaining operational efficiency.
Solution Approach 2:
The patent performs preliminary characterization of the battery's resistance components at different time scales and stores this information for use during SOC estimation. By pre-establishing the relationship between time, current, voltage, and resistance components, the system prepares the necessary data structures and models in advance, enabling accurate real-time SOC calculation.
3Device complexity
If the internal resistance model does not account for discharge duration, then the model is simpler, but the SOC estimation accuracy decreases because the cumulative effect of charge transfer resistance and diffusional impedance is ignored
Solution Approach 1:
The patent makes the internal resistance model dynamic by incorporating discharge duration as a variable. The model automatically adjusts which resistance components are active based on the elapsed discharge time, transitioning from considering only ohmic resistance at short durations to including polarization, charge transfer, and diffusional impedance components at longer durations. This dynamic adaptation improves accuracy without requiring a permanently complex model structure.
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 improves the accuracy of SOC estimation by accounting for temperature, current, and discharge duration, resulting in a more precise determination of the battery's state of charge.
Implementation Method 1
the battery is a quite complex electrochemical system
Implementation Method 2
an ohmic internal resistance is obtained based on the segment C of the excitation response curve according to the Ohm's law
Data Source
Figure 1A~1B
Figure 1C
Figure 2
AI summary
This application discloses a method and apparatus for estimating a state of charge of a battery, configured to improve accuracy of an estimated value of a state of charge of a battery. The method in this application includes: obtaining, at a preconfigured time interval, a current-moment charge/discharge current, a current-moment temperature, a current-moment coulomb capacity, and a previous-moment state of charge value of a to-be-measured battery in real time; obtaining discharge duration of the to-be-measured battery; determining a current-moment internal resistance response type of the to-be-measured battery based on the discharge duration; determining current-moment internal resistance data of the to-be-measured battery based on the current-moment internal resistance response type, the current-moment temperature, the current-moment charge/discharge current, and the previous-moment state of charge value; determining a current-moment unusable capacity of the to-be-measured battery based on the current-moment internal resistance data, the current-moment charge/discharge current, and the current-moment temperature; and determining a current-moment state of charge value of the to-be-measured battery based on the current-moment coulomb capacity and the current-moment unusable capacity.