Artificial Intelligence and Data Driven Optimization of Internal
Combustion Engines summarizes 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, and optimize after-treatment systems and
experimental engine calibration. It contains all the details of the
latest optimization techniques along with their application to ICE,
making it ideal for automotive engineers, mechanical engineers,
OEMs and R&D centers involved in engine design.
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