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Dual-fuel engines powered by renewable fuels provide a potential solution for reducing the carbon footprint and emissions of transportation, contributing to the goal of achieving sustainable mobility. The investigation presented in the following uses a dual-fuel engine concept running on biogas (referred to as CNG in this paper) and the e-fuel polyoxymethylene dimethyl ether (OME). The current study focuses on the effects of exhaust gas rebreathing and external exhaust gas recirculation (EGR) on emissions and brake thermal efficiency (BTE). A four-cylinder heavy-duty engine converted to dual-fuel operation was used to conduct the engine tests at a load point of 1600 min-1 and 9.8 bar brake mean effective pressure (BMEP). The respective shares of high reactivity fuel (HRF, here: OME) and low reactivity fuel (LRF, here: CNG) were varied, as were the external and internal EGR rates and their combinations.

With the rising popularity of dual-fuel combustion, liquefied petroleum gas (LPG) can be utilized in high-compression diesel engines. Through production from biomass (biomass to liquid, BtL), biopropane as a direct substitute for LPG can contribute to a reduction in greenhouse gas emissions caused by combustion engines. In a conventional dual-fuel engine, the low reactivity fuel (LRF) propane is premixed with the intake air to form a homogeneous mixture. This air-fuel mixture is then ignited by the high reactivity fuel (HRF) in the form of a diesel pilot injection inside the cylinder. In the presented work, this premixed charge operation (PCO) is compared to a method where propane and diesel are blended directly upstream of the high-pressure pump (premixed fuel operation, PFO) in variable mixing ratios for different engine loads and speeds. Furthermore, the effects of internal and external exhaust gas recirculation are investigated for each operating mode.

In recent years, the automotive industry has shifted from purely combustion engine-driven vehicles towards hybridization due to the introduction of CO2 emission legislation. Hybrid powertrains also represent an important pillar and starting point in the journey towards zero-emission and full electrification. Fulfilling the most recent emission standards requires efficient control strategies for the engine, capable of real-time operation. Model accuracy is one of the main parameters which directly influence the performance of such control strategies. Specific methodologies developed in the past, such as physically- or phenomenologically-based approaches, have already facilitated the modeling of the combustion engine. Even though these models can accurately predict emissions in steady state conditions, their performance during transient engine operation is time-consuming and still not sufficiently reliable.

In recent years, the utilization of dual-fuel combustion has gained popularity in order to improve engine efficiency and emissions. With its high knock resistance, methane allows operation in high compression diesel engines with lower risk of knocking. With the use of diesel fuel as an ignition source, it is possible to exploit the advantages of lean combustion without facing problems to provide the high amount of ignition energy necessary to burn methane under such operating conditions. Another advantage is the variety of sources from which the primary fuel can be obtained. In addition to fossil sources, methane can also be produced from biomass or electrical energy. As the rate of substitution of diesel by methane increases, the trade-off between nitrogen oxide and soot is mitigated. However, emissions of carbon monoxide and unburned methane increase.

The aim of current research on internal combustion engines is to further reduce exhaust gas pollutant emissions while simultaneously lowering carbon dioxide emissions in order to limit the greenhouse effect. Due to the restricted potential for reducing CO2 (carbon dioxide) emissions when using fossil fuels, an extensive defossilisation of the transport sector is necessary. Investigations of future propulsion systems should therefore not focus solely on further development of the prime mover, but also on the energy carrier which is used. In this context, fuels from renewable energy sources are of particular interest, e.g. paraffinic diesel fuels such as hydrogenated vegetable oil (HVO) or potentially entirely synthetic fuels like POMDME (polyoxymethylene dimethyl ether, short: OME) as well as blends of such fuels.

Homogeneous Charge Compression Ignition (HCCI) offers a significant potential to reduce CO2 as well as NOx and particulate emissions. However ensuring stable and efficient HCCI combustion in practical use is a challenge and requires sophisticated control concepts. In the present paper a closed loop control concept is investigated for this purpose. In order to optimize the closed loop control, adaptations with neural networks are introduced. Different sensor concepts for HCCI combustion control are presented and the benefit of the analysis of crankshaft movements is analyzed.