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000707282 0247_ $$2datacite_doi$$a10.18154/RWTH-2017-09156
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000707282 041__ $$aEnglish
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000707282 1001_ $$0P:(DE-588)1143879104$$aPilatowicz, Grzegorz$$b0$$urwth
000707282 245__ $$aFailure Detection and Battery Management Systems of Lead-Acid Batteries for Micro-Hybrid Vehicles$$cvorgelegt von Master of Science in Engineering Grzegorz Aleksander Pilatowicz$$honline
000707282 260__ $$aAachen$$c2017
000707282 300__ $$a1 Online-Ressource (212 Seiten) : Illustrationen, Diagramme
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000707282 4900_ $$aAachener Beiträge des ISEA$$v92
000707282 500__ $$aVeröffentlicht auf dem Publikationsserver der RWTH Aachen University
000707282 502__ $$aDissertation, RWTH Aachen University, 2017$$bDissertation$$cRWTH Aachen University$$d2017$$gFak06$$o2017-02-17
000707282 5203_ $$aIn dieser Arbeit wurden neuartige Algorithmen für die Batterie-Zustandserkennung von Blei-Säure Starterbatterien entwickelt. Das Hauptziel lag darin, die Genauigkeit, Zuverlässigkeit und Robustheit der herkömmlichen Lösungen, insbesondere die mit heuristischen Ansätzen, durch gewonnenes Verständnis der relevanten elektrochemischen Prozesse zu verbessern. Besonders für die Steigerung der Verfügbarkeit und Zuverlässigkeit der Blei-Säure Batterie und die sich daraus ergebenen Reduktion von CO2 Emissionen und Kraftstoffverbrauch der Mikro-Hybrid-Fahrzeuge sind diese Algorithmen nötig. Die Entwicklung, Vereinfachung und Implementierung dieser Algorithmen für den Einsatz in einer massentauglichen Hardware-Plattform, ist weitgehend schwierig, deshalb wurden diese Aspekte mit großer Priorität betrachtet.$$lger
000707282 520__ $$aMicro-hybrid vehicles (µH) are currently starting to dominate the European market and seize constantly growing share of other leading markets in the world. On the one hand, the additional functionality of µH reduces the CO2 emissions and improves the fuel economy, but, on the other hand, the additional stress imposed on the lead-acid battery reduces significantly its expected service life in comparison to conventional vehicles. Because of that µH require highly accurate battery diagnostics. It is necessary to ensure the vehicle reliability requirements, prolong service life, reduce warranty costs and maximize fuel savings. The latter refers to reducing number of premature engine restarts and missed stop-start opportunities.This thesis presents battery state detection algorithms of lead-acid batteries developed for operation in µH applications. Their novelty is defined by improved accuracy, reliability, robustness and applicability for different types and sizes comparing to the known solutions. It was possible thanks to conducted comprehensive experimental and analytic study, allowing a better understanding of the relevant electrochemical processes. Result of these studies were the foundation for each of the described methods and allowed finding optimal simplifications without significant loss of performance. Reduced complexity is of high importance for implementation of these algorithms into the low-cost hardware, which is responsible for real-time estimation of the battery state, current, voltage and temperature of the terminal as well as communicating these values to the body computer of the vehicle.$$leng
000707282 588__ $$aDataset connected to Lobid/HBZ
000707282 591__ $$aGermany
000707282 7001_ $$0P:(DE-82)IDM01459$$aSauer, Dirk Uwe$$b1$$eThesis advisor
000707282 7001_ $$aFerg, Ernst$$b2$$eThesis advisor
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000707282 9201_ $$0I:(DE-82)618310_20140620$$k618310$$lLehrstuhl für Elektrochemische Energiewandlung und Speichersystemtechnik$$x0
000707282 9201_ $$0I:(DE-82)614500_20201203$$k614500$$lInstitut für Stromrichtertechnik und Elektrische Antriebe$$x1
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