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This paper describes an overall system for state-of-available-power (SoAP) prediction for a lithium-ion battery pack. The essential part of this method is based on an adaptive network architecture which utilizes both fuzzy model (FIS) and artificial neural network (ANN) into the framework of adaptive neuro-fuzzy inference system (ANFIS). While battery aging proceeds, the system is capable of delivering...
In this work a three dimensional impedance-based electric battery model is coupled with a thermal model. Both parts are verified by comparing measurement and simulation. Subsequently the model is used to simulate a locally limited internal short-circuit inside a cell and inside a battery pack. Based on the simulations, suggestions for improvements of passive safety are made.
Lithium-ion battery aging tests show that battery lifetime can be strongly influenced by the operating conditions, particularly by the state of charge and the cycle depth. Therefore a genetic optimization algorithm is applied to optimize the charging behavior of a plug-in hybrid electric vehicle (PHEV) connected to the grid with respect to maximizing energy trading profits in a vehicle-to-grid (V2G)...
Lithium-ion (Li-ion) batteries are nowadays the best tradeoff between performance, cost, and lifetime to store electric power and energy effectively. The reliable determination of the batteries’ instantaneous power capability and energy content is mandatory for many mobile high-energy and power-consuming applications. Herein, the battery impedance and state of charge () are the relevant...
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