DEVELOPMENT AND IMPLEMENTATION OF A NEURAL KNOCK DETECTOR USING CONSTRUCTIVE LEARNING-METHODS

The world-wide demands for reasonable fuel consumption and reduced eng ine emissions force engine developers to improve the combustion proces s. Automobile makers are expecting to meet these demands by increasing the engine compression ratio. However, this improvement leads back to the problem of engine knock and appropriate engine control. Thus, the ability to detect engine knock with high precision will be mandatory for car makers. We propose a detection scheme that consists of two mai n blocks: multifeature extraction and neural classification. This pape r gives a short overview of the concept and presents a developed const ructive learning algorithm for the cycle-by-cycle detection task.