EXPERIMENTAL-DATA PROCESSING TECHNIQUES TO MAP THE PERFORMANCE OF A SPARK-IGNITION ENGINE

Mapping the performance of an internal combustion engine over a wide r ange of operating conditions is a common procedure during development. The generation and post-processing of the data are high-cost activiti es. Two approaches which offer advantages over parametric test plans h ave been investigated. A statistically designed matrix of tests has be en employed to map engine stability and combustion performance paramet ers. This approach minimizes the number of tests required and post-pro cessing techniques provide valuable insight to relationships which exi st between variables. This is particularly useful and efficient when q ualitative trends are of prime interest. When large data sets are nece ssarily acquired and quantitative relationships between variables are of particular concern, then data processing using neural networks is s hown to be an effective approach. The use of this technique is illustr ated by application to evaluate relationships between engine-out emiss ions and engine state variables.