International Journal of Science, Engineering and TechnologyAuthors: Budh Sen, Khemraj Beragi
Abstract: As environmental regulations grow increasingly stringent and fuel efficiency becomes a central concern for both manufacturers and consumers, the automotive industry is undergoing a technological shift toward intelligent engine management systems. Internal combustion (IC) engines, though mature, continue to dominate the global vehicle fleet, particularly in developing economies. However, traditional emission control and fuel optimization methods, which rely on fixed calibration maps and rule-based logic, struggle to adapt to real-time driving conditions and evolving operational complexities. This paper explores the transformative role of Artificial Intelligence (AI) in enhancing emission control and fuel efficiency in IC engines through a comprehensive secondary analysis of literature, case studies, and industrial applications from 2015 to 2025. AI techniques such as machine learning, deep learning, and reinforcement learning are capable of analyzing real-time engine data from multiple sensors, enabling dynamic adjustment of parameters like fuel injection, ignition timing, and air-fuel ratios. Case studies from companies such as Bosch, Toyota, and Mahindra demonstrate tangible improvements in emission reduction (up to 18%) and fuel savings (up to 10%) through AI-powered systems. The paper also discusses emerging trends including edge AI in ECUs, hybrid control systems, digital twin modeling, and AI integration in hybrid and biofuel engines. While the potential is vast, challenges such as data noise, computational constraints, legacy system integration, and regulatory compliance must be addressed. The study concludes that AI-driven engine control systems offer a promising path toward cleaner, more adaptive, and efficient automotive technologies.
DOI: http://doi.org/
