Executive Summary : | The project aims to improve the performance and reduce the emissions of a Reactivity Controlled Compression Ignition (RCCI) engine by implementing predictive control techniques using Artificial Intelligence (AI) algorithms. RCCI engines are a type of internal combustion engine that combines the benefits of both diesel and gasoline engines to achieve high efficiency and low emissions. The project involves collecting data on the engine's performance and emissions, which will be used to develop a predictive model using AI techniques such as machine learning and neural networks. This model will then be used to predict the engine's behavior and emissions under different operating conditions, which will allow for the implementation of a closed-loop control system that can optimize engine performance and reduce emissions in real-time. The project's ultimate goal is to develop a predictive control system that can be implemented in RCCI engines to improve their efficiency and reduce their environmental impact. This system could have significant implications for the automotive industry, as it could help to make RCCI engines a more viable alternative to traditional gasoline and diesel engines. |