In this work estimation methods are presented and optimized for the use in intelligent battery systems. These battery systems are characterized by sensors on cell level, a reconfigurable topology and the application of machine learning methods in the battery management system. The influence of switching operations on the system’s excitation and the estimation performance is investigated. Furthermore, a sensor data fusion method is presented to combine sensor data of cell current and voltage. The resulting benefits include but are not limited to an increased estimation accuracy.
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In this work estimation methods are presented and optimized for the use in intelligent battery systems. These battery systems are characterized by sensors on cell level, a reconfigurable topology and the application of machine learning methods in the battery management system. The influence of switching operations on the system’s excitation and the estimation performance is investigated. Furthermore, a sensor data fusion method is presented to combine sensor data of cell current and voltage. The...
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