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In total, this simple battery model can be employed as a real-time model in electrified vehicle battery management systems.
The weights of the constructed dual neural network fusion battery model can be used to describe the characteristics of the corresponding parameters of electrochemical model for the battery.
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The model can be used for battery dynamic simulation and design in a satellite power system, an example of which is given.
The trained neural network model can be adaptively updated to account for the battery to battery variability, thus ensuring good SoC and SoH estimation accuracy.
With proposed parameter estimation method, the simplified ECT coupling model can be applied to similar battery systems.
The proposed model can be used to create self-powering systems, which are not limited to a finite battery energy.
This model can be quantified.
The model can be changed.
Advanced battery modeling and simulation can be realized with a unique computational fluid dynamics (CFD) approach that provides much detailed information that can greatly benefit battery research and development.
The same type of the models can be used to relate the variation of in vivo data to the variation of a battery of in vitro tests.
Models can be another issue.
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