AI and Ml techniques are promising tools to handle the inherent nonlinearity and complexity of modern engine systems. AI and Data Driven Optimization Techniques for Internal Combustion Engines summarizes the recent developments in Artificial Intelligence (AI)/Machine Learning (ML) and data driven optimization and calibration techniques for internal combustion engines. The book covers AI/ML and data driven methods to optimize fuel formulations and engine combustion systems, predict cycle to cycle variations, optimize after-treatment systems and experimental engine calibration.

This book contains all the details of the latest optimization techniques along with their application to ICE and is for automotive engineers, mechanical engineers, OEMs, and R&D centers involved in engine design.