Optimising Engine Performance and Emission Characteristics Through Advanced Simulation Techniques
Abstract
This article discusses the role of advanced simulation techniques, such as Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and Machine Learning (ML), in optimizing engine performance and reducing emissions. CFD enables in-depth analysis of fluid flow, heat transfer, and chemical reactions inside the engine, while FEA ensures the structural reliability of engine components under extreme conditions. ML and AI technologies provide predictive capabilities, enabling real-time optimization and predictive maintenance. Integrating these techniques yields significant synergies, such as real-time fuel injection timing optimization and automated engine component design. The study results show that simulation accelerates engine development and offers a cost-effective solution compared to conventional methods. However, challenges such as high computational resource requirements, model validation, and the complexity of multiphysics interactions remain to be overcome. In the future, adopting real-time simulation, cloud-based platforms, and integration with the Internet of Things (IoT) can accelerate the design cycle by up to 50% and improve efficiency and predictive accuracy. However, data security and technology synchronization are concerns that must be addressed.