Engine Knock Estimation Using Neural Networks Based on a Real-World Database

In this paper we present an advanced knock detection approach. The detection concept consists of a two-level feature extraction step followed by neural network detector. A knock tendency index is estimated that takes into account the statistical behavior of the knock phenomena. The configuration of the neural network is based on a signal database that was acquired under almost ‘on-road’ conditions. The experimental set-up consisted of several measurement sessions in a special vehicle test cell. In order to achieve a most realistic knock database the test engine was mounted on an in-production car.