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Automotive industry still investigate new techniques for control and optimization combustion engines. The main aim is to reduce fuel consumption, increase power and at the same time reduce exhaust emissions. Algorithms to control combustion engine are highly required in order to ensure stable work of the engine in a wide range of operating conditions. All restrictions and requirements determine implementation of additional systems and control algorithms. Existing algorithms like PID or H infinity are based on linear models of the controlled phenomena. CE characteristics are far from being linear. In order to solve nonlinear control problems new models should be applied. Artificial intelligence algorithms are technology widely accepted to tackle complex and nonlinear problems. They are able to handle noisy or incomplete data, and tackle nonlinear problems. When trained perform generalization and predictions at high speed. AI approach is used with success in research areas like robotics, medicine, pattern recognition, manufacturing and in Combustion Engines. The main aim of this paper is to outline how AI systems tackle problems related to control and optimize CE in order to define knowledge gaps in this area.