This paper gives an overview on procedures and algorithms to determine the battery's states of function (SOF) with special respect to automotive applications. Detailed definition of battery parameters such as available charge (Q) and capacity (C) are given, which can be used by energy management systems to determine the SOF from the basic information on the actual battery conditions. As a result, well known battery performance parameters, such as state of charge (SOC), cranking capability (CC), charge acceptance (CA) and state of health (SOH) can be calculated from these basic parameters according to the requirements of the energy management system. The authors are providing a definition for these parameters in a way that clearly distinguishes battery condition on the one hand and state of function with regard to the application on the other hand. Conventional methods to determine the battery condition, such as charge balancing and resistance measurement, are reviewed and further developed to fulfill the requirements on reliability and sensitivity for automotive applications. Novel methods based on passive and active impedance measurements, expert systems and self-learning algorithms are introduced.
Battery monitoring for automotive batteries is not a miracle - some practicable algorithms to identify state-of-function parameters
Batterie-Überwachung bei Autobatterien ist kein Wunder - praktikable Algorithmen zur Feststellung der Zustandsparameter
2005
12 Seiten, 10 Bilder, 13 Quellen
Aufsatz (Konferenz)
Datenträger
Englisch
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