Development of mean value engine model using ANN Soo-Youl Park (Mechanical Engineering)

Problem Definition Engine simulation model Physical model (Gas dynamics, Combustion, thermodynamics) Generally, More complex more accurate and more time consuming in calculation Need for fast running model guaranteeing high accuracy  hopefully, running at real time Minimizing the use of physical model by incorporating ANN  Mean value engine model

How to make it Build a fully physical based model Using DOE (Design of Experiment) with above model, generate training and test data. Replace some parts of physical model with ANN model

Training Neural Network Self Organizing Local Linear (Unsupervised Learning) RMS training error RMS testing error

Results & Conclusion With Core2 CPU of 2.4GHz, calculation time for acceleration cycle from zero to 80 km/h is 140s in case of fully physical model 21s in case of ANN supporting model  close to real time (real time is about 7.36s Accuracy ANN supporting vs. fully physical model Results for acceleration cycle