Combination of Organic Rankine Cycle (ORC) with Diesel Engines for Emission Reduction and Enhanced Energy Efficiency: A Review

Growing concerns about emissions and fuel efficiency in diesel engines have driven the development of advanced waste heat recovery (WHR) systems. This research explored a novel approach integrating thermodynamic optimization, particle swarm optimization (PSO), genetic algorithms (GA), artificial neural networks (ANN) and response surface methodology (RSM) within an organic Rankine cycle (ORC) system to mitigate emissions. The use of organic fluids in the ORC proved effective for recovering low-grade waste heat across varying engine loads, leading to positive reductions in nitrogen oxide (NOx), particulate matter (PM) and greenhouse gas (GHG) emissions. Incorporating these optimization techniques further enhanced the system’s thermal efficiency and waste heat recovery capabilities, resulting in lower emissions from the diesel engine. The research findings demonstrate that model-based optimization effectively addresses operational challenges, improves engine performance, and reduces environmental impact, offering a promising pathway towards environmentally sustainable and efficient diesel engine operation—a goal of global importance given the need to reduce emissions and enhance energy system efficiency.