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A reduced kinetic reaction mechanism for the autoignition of dimethyl ether is presented in this paper. Dimethyl ether has proven to be one of the most attractive alternatives to traditional fossil fuels for compression ignition engines. It can either be produced from biomass or from fossil oil. For dimethyl ether, Fischer et al. (Int. J.Chem. Kinet. 32 ( 12 ) (2000) 713-740) proposed a detailed reaction mechanism consisting of 79 species and 351 elementary reactions. In the present work, this detailed mechanism is systematically reduced to 31 species and 49 reactions. The reduced mechanism is discussed in detail with special emphasis on the high temperature thermal decomposition of dimethyl ether and on the fuel specific depleting reactions, which produce the methoxymethyl radical. In addition, a reaction pathway analysis for low temperature combustion is applied, where hydroperoxy-methylformate is found to be the dominating parameter for the low temperature regime.

In order to comply with demanding Greenhous Gas (GHG) standards, future automotive engines employ advanced engine technologies including waste heat recovery (WHR) systems. A waste heat recovery system converts part of engine wasted exergies to useful work which can be fed back to the engine. Utilizing this additional output power leads to lower specific fuel consumption and CO2 emission when the total output power equals the original engine output power. Engine calibration strategies for reductions in specific fuel consumption typically results in a natural increase of NOx emissions. The utilization of waste heat recovery systems provides a pathway which gives both reduction in emissions and reduction in specific fuel consumption. According to DOE (Department of Energy), US heavy-duty truck engines’ technology need to be upgraded towards higher brake thermal efficiencies (BTE). DOE target is BTE>55% for Class-8 heavy-duty vehicles in the United States.

In order to reduce engine out CO2 emissions it is a main subject to find new alternative fuels out of renewable sources. For this paper, several fuels were selected which can be produced out of biomass or with hydrogen which is generated directly via electrolysis with electricity from renewable sources. All fuels are compared to conventional diesel fuel and two diesel surrogates. It is well known that there can be a large effect of fuel properties on mixture formation and combustion, which may result in a completely different engine performance compared to the operation with conventional diesel fuels. Mixture formation and ignition behavior can also largely affect the pollutant formation. The knowledge of the combustion behavior is also important to design new engine geometries or implement new calibrations for an existing engine. The fuel properties of the investigated fuels comprise a large range, for example in case of the derived cetane number, from below 30 up to 100.

Especially for internal combustion engine simulations, various combustion models rely on the laminar burning velocity. With respect to computational time needed for CFD, the calculation of laminar burning velocities using a detailed chemical mechanism can be replaced by incorporation of approximation formulas, based on rate-ratio asymptotics. This study revisits an existing analytical approximation formula [1]. It investigates applicable temperature, pressure, and equivalence ratio ranges with special focus on engine combustion conditions. The fuel chosen here is methane and mixtures are composed of methane and air. The model performance to calculate the laminar burning velocity are compared with calculated laminar burning velocities using existing state of the art detailed chemical mechanisms, the GRI Mech 3.0 [2], the ITV RWTH [3], and the Aramco mechanism [4].

For compliance with legislative regulations as well as restricted resources of fossil fuel, it is essential to further reduce engine-out emissions and increase engine efficiency. As a result of lower peak temperatures and increased homogeneity, premixed Low-Temperature Combustion (LTC) has the potential to simultaneously reduce nitrogen oxides (BSNOx) and soot. However, LTC can lead to higher emissions of unburnt total hydrocarbons (BSTHC) and carbon monoxide (BSCO). Furthermore, losses in efficiency are often observed, due to early combustion phasing (CA50) before top dead center (bTDC). Various studies have shown possibilities to counteract these drawbacks, such as split-injection strategies or different nozzle geometries. In this work, the combination of both is investigated. Three different nozzle geometries with included spray angles of 100°, 120°, and 148° and four injection strategies are applied to investigate the engine performance.

The possibility to vary compression ratio offers a new degree of freedom that may enable so far not exploited benefits for the combustion process especially for highly boosted spark ignited engines. Numerous approaches to enable a variable compression ratio (VCR) have been tried and tested in the past. Nevertheless, none of these systems reached series production because of several reasons, ranging from too much complexity and moveable parts to deep modification required on existing engine architectures and manufacturing lines. Instead, the approach of a variable length conrod (VCR conrod) could be the solution for integration in almost any type of engine with minor modifications. It is then considered by several OEMs as a promising candidate for midterm series production. This paper shows, firstly, a discussion of the benefits of a variable compression ratio system.

With the implementation of the “Worldwide harmonized Light duty Test Procedure” (WLTP) and the highly dynamic “Real Driving Emissions” (RDE) tests in Europe, different engineering methodologies from virtual calibration approaches to Engine-in-the-loop (EiL) methods have to be considered to define and calibrate efficient exhaust gas aftertreatment technologies without the availability of prototype vehicles in early project phases. Since different types of testing facilities can be used, the effects of test benches as well as real and virtual vehicle operators have to be determined. Moreover, in order to effectively reduce harmful emissions, the reproducibility of test cycles is essential for an accurate and efficient application of exhaust gas aftertreatment systems and the calibration of internal combustion engines.

Nowadays, collision avoidance systems (CAS) are an intensive research topic since the majority of all traffic accidents are collisions that are caused due to inattention or unadjusted driving behavior of the driver. Up to date prototypic CAS are based on on-board environmental sensors, such as camera or radar systems, that scan the vehicle's surrounding environment in order to assess the situation's hazardousness. The functionality of the used sensors under varying environmental conditions and the limited sensor covering area require an enormous effort to ensure a reliable detection of obstacles, and thus limit the application of the systems. In order to expand the operating field of such systems, a Galileo-based CAS will be developed within the project ‘Galileo above’ (application centre for ground based traffic).

If fuels that are more resistant to auto-ignition are injected near TDC in compression ignition engines, they ignite much later than diesel fuel and combustion occurs when the fuel and air have had more chance to mix. This helps to reduce NOX and smoke emissions at much lower injection pressures compared to a diesel fuel. However, PPCI (Partially Premixed Compression Ignition) operation also leads to higher CO and HC at low loads and higher heat release rates at high loads. These problems can be significantly alleviated by managing the mixing through injector design (e.g. nozzle size and centreline spray angle) and changing CR (Compression Ratio). This work describes results of running a single-cylinder diesel engine on fuel blends by using three different nozzle design (nozzle size: 0.13 mm and 0.17 mm, centreline spray angle: 153° and 120°) and two different CRs (15.9:1 and 18:1).

Downsizing in combination with turbocharging currently represents the main technology trend for meeting CO2 emissions with gasoline engines. Besides the well-known advantages of downsizing the compression ratio has to be reduced in order to mitigate knock at higher engine loads along with increased turbocharging demand to compensate for the reduction in power. Another disadvantage occurs at part load with increasing boost pressure levels causing the part load efficiencies to deteriorate. The application of a variable compression ratio (VCR) system can help to mitigate these disadvantages. The 2-stage VCR system with variable kinetic lengths entails variable powertrain components which can be used instead of the conventional components and thus only require minor modifications for existing engine architectures. The presented variable length connecting rod system has been continuously developed over the past years.

A regular flex-fuel engine can operate on any blend of fuel between pure gasoline and E85. Flex-fuel engines have relatively low efficiency on E85 because the hardware is optimized for gasoline. If instead the engine is optimized for neat ethanol, the efficiency may be much higher, as demonstrated in this paper. The studied two-liter engine was modified with a much higher compression ratio than suitable for gasoline, two-stage turbocharging and direct injection with piezo-actuated outwards-opening injectors, a stratified combustion system and custom in-house control system. The research engine exhibited a wide-open throttle performance similar to that of a naturally aspirated v8, while offering a part-load efficiency comparable to a state-of-the-art two-liter naturally aspirated engine. NOx will be handled by a lean NOx trap. Combustion characteristics were compared between gasoline and neat ethanol.

The reduction of harmful emissions is a key challenge in fighting climate change and global warming. Besides battery electric vehicles (BEVs), improved engine efficiency and alternate fuels, such as e-fuels or biofuels, can improve the emission budget of the transportation sector. Pred ictive simulations can be utilized as these avoid relying on slow manufacturing processes and expensive experiments. As the properties of alternative fuels can change drastically compared to classical fuels, even engine parameters, such as the mass flow rate, need to be reevaluated and optimized. However, simulation frameworks often rely on mass flow rates as input quantity, and hence, a prediction is impossible. This paper gives accurate pressure-based boundary conditions for multiphase systems and focuses on equations of state (EOS) employed in homogeneous equilibrium models (HEMs). Additionally, a dual-density approach is introduced to correct modeling errors that are intrinsic to a particular EOS.

Premixed charged compression ignition (PCCI) is an advanced combustion strategy, which has the potential to achieve ultra-low nitrogen oxide and soot emissions at high thermal efficiencies. PCCI combustion is characterized by a complex nonlinear chemical-physical process, which indicates that a physical description involves significant development times and also high computation cost. This paper presents a method to use cylinder pressure data and engine operations parameters for prediction of PCCI engine emissions by unsupervised learning and nonlinear identification techniques. The proposed method first uses principal component analysis (PCA) to reduce the dimension of the cylinder-pressure data. Based on the PCA analysis, a multi-input multi-out model was developed for nitrogen oxide and soot emission prediction by multi-layer perceptron (MLP) neural network.

This paper describes an approach to reduce development costs and time by frontloading of engineering tasks and even starting calibration tasks already in the early component conception phases of a vehicle development program. To realize this, the application of a consistent and parallel virtual development and calibration methodology is required. The interaction between vehicle subcomponents physically available and those only virtually available at that time, is achieved with the introduction of highly accurate real-time models on closed-loop co-simulation platforms (HiL-simulators) which provide the appropriate response of the hardware components. This paper presents results of a heterogeneous testing scenario containing a real internal combustion engine on a test facility and a purely virtual vehicle using two different automatic transmission calibration and hardware setups.

The laminar burning velocity is an important parameter in various combustion models for engine simulations. With respect to computational time for computational fluid dynamics (CFD) and full system engine simulations, the calculation of laminar burning velocities using a detailed chemical mechanism can be replaced by incorporation of approximation formulas, based on rate-ratio asymptotics. In the present study, a work flow is developed to analyze the engine efficiency performance of spark ignition engines with respect to the laminar burning velocity as a fundamental fuel property. Firstly, methane is used as a fuel to assess practicability of the approach. The procedure is subsequently adopted for market type gasoline surrogates, RON95 and RON100. Detailed chemistry calculations are carried out for the three target fuels using existing state of the art mechanisms, the Aramco [Zhou et al., Proc. Combust. Inst., pp. 403-411, 2017] and the ITV RWTH mechanism [Cai et al., Combust.

Knock control is one of the most vital functions for safe and fuel-efficient operation of gasoline engines. However, all knock control strategies rely on accurate knock detection to operate the engine close to the optimal set point. Knock detection is usually calibrated on the engine test bench, requiring the engine to run with knocking combustion in a time-consuming multi-stage campaign. Model-based calibration significantly reduces calibration loops on the test bench. However, this method requires a large effort in building and validating the model, which is often limited by the lack of function documentation, available measurements or hardware representation. As the software models are often not available, function structures vary between manufacturers and sub model functions are often documented as black boxes. Hence, using the model-based approach is not always possible.

Ethanol currently remains the leading biofuel in the transportation sector, with special focus on spark ignition engines, as a pure as well as a blend component. In order to provide reliable numerical simulations of gasoline combustion processes under the influence of ethanol for modern engine research, it is mandatory to develop well validated detailed kinetic combustion models. One key parameter for the numerical simulation is the laminar burning velocity. Under the aspect of minimizing the general simulation effort for burning velocities, well-validated models have to be reduced. As a base kinetic mechanism for the reduction and optimisation process with respect to burning velocity calculations, a detailed model presented by Zhao et al. (Int. J. Chem. Kin. 40 (1) (2007) 1-18) is chosen. The model has been extensively validated against shock tube, rapid compression machine and burning velocity data. The detailed model consists of 55 species and 290 reactions.

In order to reduce engine out CO2 emissions it is a main subject to find new alternative fuels out of renewable sources. For this reason in this paper a blend out of 1-octanol and di-n-butylether and pure di-n-butylether are investigated in comparison to n-heptane as diesel-like fuel. The alternative fuels have a different combustion behavior particularly concerning important combustion parameters like ignition delay and mixture formation. Especially the formation of pollutants like nitrogen oxides in the combustion of alternative fuels is of global interest. The knowledge of the combustion behavior is important to design new engine geometries or implement a new calibration of the engine. In previous measurements in a single cylinder engine it was found out that both alternative fuels form nearly no soot emissions. For this reason now NOx is investigated optically to avoid the traditional soot NOx trade-off in diesel combustion.

Targeted fuel blending is a known method to improve the performance of an automotive engine. Two candidates for a biofuel blend are the linear C8H18O isomers 1-octanol and di-n-butyl ether (DNBE). Both fuels feature an increased amount of oxygen that reduces soot emissions. However, physical properties of both fuels differ significantly and thus, a different type of spray mixing and combustion is expected: The low reactivity of 1-octanol causes a long ignition delay enabling a better mixture homogenization, but also causes HC and CO emissions. DNBE in contrary is highly volatile, has a short ignition time and thus can act as an ignition booster for 1-octanol without losing positive effects concerning emissions. In this work a spray study is performed for blends of 1-octanol and DNBE. Measurements are conducted under diesel-like engine conditions with an 8-hole piezo injector. High-speed Schlieren and Mie scattering techniques are used for spray visualizations.

In order to reduce pollutant and CO2 emissions and fulfill future legislative requirements, powertrain electrification is one of the key technologies. In this context, especially 48V technologies offer an attractive cost to CO2 reduction ratio. 48V mild hybrid powertrains greatly benefit from additional electric intake air compression (E-Charging) and direct torque assist by an electric machine (E-Boosting). Both systems significantly improve the transient engine behavior while reducing the low end torque drawbacks of extreme downsizing and downspeeding. Since E-Charging and E-Boosting have different characteristics concerning transient torque response and energy efficiency, application of model predictive control (MPC) is a particularly suitable method to improve the operating strategy of these functions. MPC requires fast running real-time capable models that are challenging to develop for systems with pronounced nonlinearities.