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In order to meet increasingly stringent emissions standards and lower the fuel consumption of heavy-duty (HD) vehicles, significant efforts have been made to develop high efficiency and clean diesel engines and aftertreatment systems. However, a trade-off between the actual engine efficiency and nitrogen oxides (NOx) emission remains to minimize the operational costs. In addition, the conversion efficiency of the diesel aftertreatment system decreases rapidly with lower exhaust gas temperatures (EGT), which occurs at low load operations. Thus, it is necessary to investigate the optimum combustion and engine control strategies that can lower the vehicle’s running costs by maintaining low engine-out NOx emissions while increasing the conversion efficiency of the NOx aftertreament system through higher EGTs.

This paper deals with the experimental and numerical investigation of a 2.0 litre single cylinder Heavy Duty Diesel Engine fuelled by natural gas and diesel oil in Dual Fuel mode. Due to the gaseous nature of the main fuel and to the high compression ratio of the diesel engine, reduced emissions can be obtained. An experimental study has been carried out at three different load level (25%, 50% and 75% of full engine load). Basing on experimental data, the authors recreated a 45° mesh sector of the engine cylinder and performed CFD simulations for the cases at 50% and 75% load levels. Numerical simulations were carried out on the 3D code Ansys FORTE. The aim of this work is to study combustion phenomena and, in particular, the interaction between natural gas and diesel oil, respectively represented by methane and n-dodecane. A reduced kinetic scheme for methane auto-ignition was implemented while for n-dodecane two set of reactions were utilised.

The absence of combustion information continues to be one of the key obstacles to the intelligent development of engines. Currently, the cost of integrating cylinder pressure sensors remains too high, prompting attention to methods for extracting combustion information from existing sensing data. Mean-value combustion models for engines are unable to capture changes of combustion parameters. Furthermore, the methods of reconstructing combustion information using sensor signals mainly depend on the working state of the sensors, and the reliability of reconstructed values is directly influenced by sensor malfunctions. Due to the concentration of operating conditions of hybrid vehicles, the reliability of priori calibration map has increased. Therefore, a combustion information reconstruction method based on priori calibration information and the fused feature deviations of existing sensing signals is proposed and named the "Deviation-based Centroid Displacement Method" (DCDM).