Battery Current Estimation Using Voltage Limit Feedback
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Solution Overview
Problem
Current methods for determining the state of power in energy storage cells, such as those in electric and hybrid vehicles, suffer from poor adaptability to rapid changes in power demand and rely heavily on accurate estimates of state of charge and open circuit voltage, leading to potential errors and violations of voltage or power constraints.
Innovation Solution
A system comprising sensors and a microprocessor-based control unit that monitors and controls charge and discharge currents of energy storage cells, using an equivalent circuit model to predict maximum charge and discharge currents within predetermined voltage limits, with a feedback control system to adjust current limits based on real-time voltage measurements and a time horizon, ensuring reliable power estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If concurrent estimation of state of power is performed together with state of charge and open circuit voltage parameters, then the battery management system can monitor multiple parameters simultaneously, but the reliability of power estimation deteriorates due to error propagation from dependent parameters
Solution Approach 1:
The patent separates the power estimation process into two distinct phases: an offline training phase where the neural network is trained using historical data, and an online estimation phase where only power is estimated using the trained model. This segmentation prevents error propagation from concurrent SoC and OCV estimation while maintaining monitoring efficiency through the trained network's ability to predict power directly from current measurements.
Solution Approach 2:
The patent performs preliminary training of the neural network offline using historical battery data before actual power estimation begins. This preliminary action prepares the model in advance, allowing it to accurately estimate power during online operation without relying on potentially erroneous concurrent estimates of dependent parameters like SoC and OCV.
2Adaptability or versatility
If prediction time horizon is extended to improve adaptability to rapid power demand changes, then the system can respond better to future power needs, but the accuracy of voltage constraint satisfaction deteriorates
Solution Approach 1:
The patent implements a dynamic adjustment mechanism where the prediction time horizon is not fixed but adapts based on the current operating conditions and battery state. When rapid power demand changes are detected, the system adjusts the time horizon to balance adaptability with voltage constraint accuracy, allowing flexible response while maintaining precision through condition-based optimization.
Data Source
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AI summary
The present invention relates to a method and a system for determining a maximum charge current (imax) or a maximum discharge current (i,in) of an energy storage cell (103) of an energy storage device (102). The method comprises providing a predetermined upper voltage limit (Vmax) or lower voltage limit (Vmin), and providing a time horizon (Δt) as a time difference from a present time (t) to a future time (t+Δt). With a repetition time period (ΔT) different from the time horizon, repeating measuring a present voltage level (V) of the energy storage cell; calculating a voltage difference (ΔV) between the present voltage level and the upper voltage limit (Vmax) or the lower voltage limit (Vmin); and determining the maximum charge current (imax) or maximum discharge current (imin) corresponding to the voltage difference and a model, such that the estimated voltage is within the voltage limits.