Comparison of the Predictive Capabilities of Chemical Kinetic Models for Hydrogen Combustion Applications

Recent legislation banning the sale of new petrol and diesel vehicles in Europe from 2035 has shifted the focus of internal combustion engine research towards alternative fuels with net zero tailpipe emissions such as hydrogen. Research regarding hydrogen as a fuel is particularly pertinent to the so-called ‘hard-to-electrify’ propulsion applications, requiring a combination of large range, fast refuelling times or high-load duty cycles. The virtual design, development, and optimisation of hydrogen internal combustion engines has resulted in the necessity for accurate predictive modelling of the hydrogen combustion and autoignition processes. Typically, the models for these processes rely respectively on laminar flame speed datasets to calculate the rate of fuel burn as well as ignition delay time datasets to estimate autoignition timing. These datasets are generated using chemical kinetic mechanisms available in the literature. However, these mechanisms have typically been developed with a focus on hydrocarbon oxidation – e.g., syngas, natural gas, biofuels, diesel, and gasoline - and their validation datasets feature a very limited number of hydrogen-specific targets. Therefore, this study explores the predictive capability of six commonly used chemical kinetic mechanisms over a large dataset consisting of hydrogen-specific ignition delay time and laminar flame speed targets compiled using data available in the literature. Additionally, a sensitivity analysis was conducted to identify reactions that strongly affect the ignition delay time of hydrogen-air mixtures in the intermediate-temperature regime, where large ignition delay time deviations are observed compared to experimental results. The sensitivity analysis was followed by an exploratory study in ad-hoc mechanism adjustment.