Battery State of Charge Estimation via Relaxation Regression
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Solution Overview
Problem
Existing methods for determining the state of charge (SOC) of energy delivery devices, such as batteries, are inaccurate when short rest periods are used, as they do not allow the device to reach its true open-circuit voltage, leading to errors in SOC estimation.
Innovation Solution
A 2-parameter regression method using a single exponential function to extrapolate the true open-circuit voltage based on voltage data during a short rest period, independent of the device's state of health, which includes determining a time constant of relaxation associated with the device and using a profile that relates open-circuit voltage to state of charge, considering hysteresis and prior charge-discharge history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single-point voltage measurement is used during short rest periods, then the measurement process is simple and fast, but the state of charge estimation accuracy deteriorates because the battery has not reached true open-circuit voltage
Solution Approach 1:
The method performs preliminary action by characterizing the battery's relaxation behavior during normal operation (when current is flowing) and storing this information. This preliminary characterization enables accurate SOC estimation during short rest periods without requiring the battery to fully relax, thus resolving the contradiction between speed and accuracy.
Solution Approach 2:
The invention introduces an intermediary approach by using equivalent circuit models and relaxation characterization as a bridge between the measured terminal voltage and the true open-circuit voltage. This intermediary model allows accurate SOC estimation even when the battery has not reached equilibrium, resolving the accuracy-speed tradeoff.
2Measurement precision
If equivalent circuit models are used to model voltage transients, then the computational complexity increases, but the accuracy of SOC estimation during short rest periods improves
Solution Approach 1:
The method changes parameters by using a simplified equivalent circuit model with a limited number of parameters that are characterized during normal operation. This reduced-parameter approach maintains accuracy while minimizing computational complexity, resolving the contradiction between precision and device complexity.
3Measurement precision
If long rest periods are provided to allow the battery to reach steady state OCV, then the accuracy of voltage measurement improves, but the time required for SOC determination increases
Solution Approach 1:
The system performs preliminary characterization of the battery's relaxation behavior during normal operation and stores this information for later use. This preliminary action eliminates the need for long rest periods, allowing accurate SOC estimation during short rest periods and thus resolving the contradiction between measurement precision and time loss.
Solution Approach 2:
The method enables the battery management system to serve itself by using the battery's own operational data (collected during normal charging/discharging) to create the relaxation model. This self-service approach eliminates the need for external testing or long rest periods, resolving the time-accuracy tradeoff.
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 method allows for accurate SOC estimation during short rest periods, reducing errors and computational costs, and is applicable to various energy delivery devices, including hybrid electric vehicles and electrical grid buffering systems.
Implementation Method 1
The voltage relaxes because of relaxing of concentration gradients by diffusion formed in the electrolyte and active electrode materials during passage of current
Implementation Method 2
at sufficiently long times after interruption of current, the voltage profile will follow an exponential decay profile
Data Source
AI summary
A method of determining state of charge of an energy delivery device includes sampling voltage values of the energy delivery device during relaxation of the device. The method further includes regressing an open circuit voltage value and the total overpotential being relaxed. The regression includes a predetermined time constant of relaxation associated with the energy delivery device. One embodiment uses the equation V(t)=OCV−α exp(−t/tau), where V(t) represents the sampled voltage values, t represents times at which each of the voltage values are sampled, OCV represents the open circuit voltage value of the energy delivery device, αrepresents the overpotential value, and tau represents the time constant of relaxation. The method uses a predetermined profile that relates open circuit voltage of the energy delivery device to state of charge of the device, to determine a particular state of charge corresponding to the regressed open circuit voltage value.