Entwicklung einer adaptiven Leistungsprognosefunktion für Starterbatterien mit Lithium-Titanat-Oxid-Anode als Grundlage zur sicheren Energieversorgung im Fahrzeug

Schröer, Philipp Antonius; Sauer, Dirk Uwe (Thesis advisor); Pischinger, Stefan (Thesis advisor)

Aachen : RWTH Aachen University (2021, 2022)
Book, Dissertation / PhD Thesis

In: Aachener Beiträge des ISEA 162
Page(s)/Article-Nr.: 1 Online-Ressource : Illustrationen, Diagramme

Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2021

Abstract

High-performance batteries play a major role for the reliability and safety of the energy supply in modern micro and mild hybrid vehicles. This dissertation presents a new algorithm for online power prediction of lithium-ion cells with lithium titanate oxide anode (LTO). It describes the steps from the definition of a battery model by means of an equivalent circuit diagram to implementation on the basis of polynomial characteristic maps. For the model parameterization, three different methods were presented that evaluate information from the frequency and/or time domain. In order to track changing battery behavior over the cell’s service life, an essential part of this work deals with an adaptive algorithm for adjusting the equivalent circuit diagram’s parameters. In continuous operation, the algorithm is able to trace the performance of a battery cell over its lifetime and to steadily predict the its behavior for a specific load profile. Furthermore, with a suitable stimulus, the cell’s state-of-available-power can be determined directly and independently of long-term monitoring. The algorithm is validated utilizing real driving profiles applied to aged batteries. Therefore, calendric and cyclic battery aging tests were carried out for about two years and up to 100,000 equivalent full cycles.