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• AI integration: Optimizes engine design and reduces manufacturing errors. • Enhanced efficiency: AI monitoring enhances the manufacturing process efficiency. • Testing advancement: AI is used in engine performance evaluation and analysis. • Control unit evolution: AI supplements traditional models in the engine control unit design. • Future potential: Promising scope for AI-based engine development research. The development of internal combustion (IC) engines has seen significant advancements, but understanding and modelling their complex dynamics pose challenges. Artificial intelligence (AI) techniques, notably artificial neural networks (ANN) and nature-inspired optimization algorithms like genetic algorithms (GA), offer potential solutions to enhance accuracy and tackle nonlinearities and uncertainties. Despite this potential, effectively leveraging AI in engine development remains a considerable research gap. This review examines the potential benefits of AI in addressing the challenges associated with dynamic systems like engine development, focusing on sustainability and environmental friendliness through methods such as biofuel adoption. Various IC engines, including compression ignition, direct injection, marine, and aircraft engines, along with other power-generating units, were analyzed. Processes such as manufacturing, design, testing, control, and fault detection were scrutinized to identify suitable domains for AI application. The review identifies opportunities for AI in enhancing sustainability and eco-friendliness in engine development, particularly through biofuel utilization. By exploring suitable domains for AI techniques, such as ANN and GA, this paper contributes to the advancement of environmentally conscious engines. Additionally, it offers recommendations for future research to tackle the persistent challenges in engine development, particularly concerning alternate fuels like biofuels.
Patnaik et al. (Fri,) studied this question.