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- 2018 (24) (entfernen)
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- Deutsch (15)
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- Elektrotechnik und Informatik (ETI) (24) (entfernen)
Oxygen consumption of zinc-air batteries and theirperformance at low oxygen concentration levels
(2018)
Already existing primary Zinc-air batteries providea high energy density. Due to new secondary cells, its tech-nology can become an alternative for energy storage. Sincethese applications require a big amount of storable energy, theoxygen consumption has to be taken into account. This articledetermines the oxygen consumption of zinc-air batteries duringdischarging. Furthermore the performance of zinc-air batteries atlow oxygen concentrations is analyzed. Both aspects are validatedby practical experiments.
The main task of battery management systems is to keep the working area of the battery in a safe state. Estimation of the state of charge and the state of health is therefore essential. The traditional way uses the voltage level of a battery to determine those values. Modern metal air batteries provide a flat voltage characteristic which necessitates new approaches. One promising technique is the electrochemical impedance spectroscopy, which measures the AC resistance for a set of different frequencies. Previous approaches match the measured impedances with a nonlinear equivalent circuit, which needs a lot of time to solve a nonlinear least-squares problem. This paper combines the electrochemical impedance spectroscopy with neural networks to speed up the state estimation using the example of zinc air batteries. Moreover, these networks are trained with different subsets of the spectra as input data in order to determine the required number of frequencies.
Metal air batteries provide a high energy density as the ca-thodic reaction uses the surrounding air. Different metals can be usedbut zinc is very promising due to its disposability and nontoxic behav-ior. State estimation is quite complicated as the voltage characteristicof the battery is rather flat. Especially estimating the state of chargeis important as a secondary electrolysis process during overcharging canlead to an unsafe state. Another technique for state estimation is theelectrochemical impedance spectroscopy. Therefore, this paper describesthe process of setup and measuring a time series of impedance spectraat known states of charge. Then these spectra are used to derive anequivalent circuit. Finally the development of the circuit’s parameter areanalyzed to extract most important parameters.
Teaching People to program is a crucial requirement for our society to deal with the complexity of 21st-century challenges. In many teaching systems, the student is required to use a particular programming language or development environment. This paper presents an intelligent tutoring system to support blended learning scenarios, where the students can choose their programming language and development environment. For that, the system provides an interface where the students request test data and submit results to unit test their algorithms. The submitted results are analyzed by a machine learning system that detects common errors and provides adaptive feedback to the student. With this system, we are focusing on teaching algorithms rather than specific programming language semantics. The technical evaluation tested with the implementation of Mean and Median algorithm shows that the system can distinguish between error cases with an error rate under 20%. A first survey, with a small group of students, shows that the system helps them detect common errors and arrive at a correct/valid solution. We are in the process of testing the system with a larger group of students for gathering statistically reliable data.
State of Charge estimation of zinc air batteries using electrochemical impedance spectroscopy
(2018)
Elektrotechnik
(2018)