Experimental and predictive advancements in hydrogen enriched compressed natural gas spark ignition engines: a critical review
Muhammad Farhan, Hamza Ahmad Salam, Muhammad Ihsan Shahid, Tianhao Chen, Qiuhong Xiao, Long Jiang, Anas Rao, Xin Li, Fanhua Ma
Abstract
Hydrogen-enriched compressed natural gas (HCNG) has emerged as a compelling alternative fuel to conventional natural gas in spark-ignition (SI) engines, driven by its potential to improve combustion efficiency, reduce emissions, and extend lean-burn limits. This review critically synthesizes experimental, computational, and predictive advancements in HCNG fueled engine technologies across various operating conditions. The enrichment of CNG with hydrogen enhances laminar flame speed, combustion stability, and thermal efficiency, while simultaneously addressing challenges such as cyclic variability, lean-burn instability, and knock propensity. Integration strategies involving exhaust gas recirculation (EGR), advanced ignition timing, and elevated compression ratios are examined for their synergistic effects on emissions and performance. The review also highlights the utility of machine learning (e.g., SVM, ANN, IMPSO-BPNN) and quasi-dimensional combustion models for predictive simulation of engine behavior. Additionally, it provides a comprehensive comparison of laminar burning velocity and combustion characteristics of various HCNG blends, emphasizing the role of hydrogen fraction, equivalence ratio, and diluent gases in optimizing flame propagation and emission profiles. The study offers a robust framework for advancing clean fuel engine design and guides future research directions in HCNG combustion systems.