Untersuchung und Entwicklung von Netzwerkmodellen für belastete KFZ-Zündsysteme (English shop)

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n addition to established inductive ignition systems, alternative concepts such as laser ignition and high-frequency ignition are available for igniting gasoline-powered internal combustion engines. However, these technologies are still at such an early stage of development that research aimed at optimizing the combustion process continues to focus largely on widely used inductive ignition systems. Further developments concentrate, among other things, on improving ignition reliability, achieving high efficiency, and reducing pollutant emissions.

A significant contribution to these objectives was the introduction of decentralized ignition systems with individual ignition transformers, which enable, for example, cylinder-specific optimization of ignition timing and spark energy. Additional opportunities for optimization arise from the use of simulation tools to support development. However, this requires a reliable model of the entire ignition system. In addition to the ignition transformer, the electrical circuitry and spark plug must be taken into account during modeling. Initial approaches to electrical network models already exist and are optimized and extended within the scope of this dissertation.

Particular emphasis is placed on deriving a model for the ignition transformer, which also contributes significantly to a better understanding of the processes occurring within the transformer. Another essential element in developing a complete model is the ignition spark. To incorporate the spark into the simulation, however, detailed knowledge of its characteristics is indispensable. This, in turn, requires a highly accurate measurement system capable of determining the spark parameters of current and voltage.

Therefore, a measurement system is developed that is suitable for recording spark parameters under different external environmental conditions. The resulting dataset serves as the basis for developing an electrical network model of ignition sparks. Combined with the network models of the remaining ignition system components, this enables the simulation of complete ignition systems and can thus significantly support their optimization and further development.

Among other things, the dissertation demonstrates how the measured data can be evaluated to determine the energy distribution within the ignition transformer. This provides insight into the principal loss mechanisms within the ignition system and enables targeted optimization.