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Multiple-injection strategies are widely used in DI diesel engines. However, the interaction of the injection pulses is not yet fully understood. In this work, a split injection into a combustion vessel is studied by multiple optical imaging diagnostics. The vessel provides quiescent high-temperature, high-pressure ambient conditions. A common-rail injector which is equipped with a three-hole nozzle is used. The spray is visualized by Mie scattering. First and second stage of ignition are probed by formaldehyde laser-induced fluorescence (LIF) and OH* chemiluminescence imaging, respectively. In addition formation of soot is characterized by both laser-induced incandescence (LII) and natural luminosity imaging, showing that low-sooting conditions are established. These qualitative diagnostics yield ensemble-averaged, two-dimensional, time-resolved distributions of the corresponding quantities.

The most challenging part of the engine combustion development is the reduction of pollutants (e.g. CO, THC, NOx, soot, etc.) and CO2 emissions. In order to achieve this goal, new combustion techniques are required, which enable a clean and efficient combustion. For compression ignition engines, combustion rate shaping, which manipulates the injected fuel mass to control the in-cylinder pressure trace and the combustion rate itself, turned out to be a promising opportunity. One possibility to enable this technology is the usage of specially developed rate shaping injectors, which can control the injection rate continuously. A feasible solution with series injectors is the usage of multiple injections to control the injection rate and, therefore, the combustion rate. For the control of the combustion profile, a detailed injector model is required for predicting the amount of injected fuel. Simplified 0D models can easily predict single injection rates with low deviation.

In this article, the development challenges of a fuel cell system are explained using the example of the BREEZE! fuel cell range extender (FC-REX) applied in an FEV Liiona. The FEV Liiona is a battery electric vehicle based on a Fiat 500 developed by FEV. The BREEZE! system is the first applied 30 kW low temperature polymer electrolyte membrane (LT PEM) fuel cell system in the subcompact vehicle class. Due to the highly integrated system approach and dry cathode operation, a compact design of the range extender module with a system power density of 0.45 kW/l can be achieved so that the vehicle interior including trunk remains completely usable. System development for fuel cells significantly influences performance, efficiency, package, durability, and required maintenance effort of a fuel cell electric powertrain. In order to ensure safe and reliable operation, the fuel cell system has to be supplied with sufficient amounts of air, hydrogen, and coolant flows.

In order to reduce development cost and time, frontloading is an established methodology for automotive development programs. With this approach, particular development tasks are shifted to earlier program phases. One prerequisite for this approach is the application of Hardware-in-the-Loop test setups. Hardware-in-the-Loop methodologies have already successfully been applied to conventional as well as electrified powertrains considering various driving scenarios. Regarding driving performance and energy demand, electrified powertrains are highly dependent on the dc-link voltage. However, there is a particular shortage of studies focusing on the verification of variable dc-link voltage controls by Hardware-in-the-Loop setups. This article is intended to be a first step towards closing this gap. Thereto, a Hardware-in-the-Loop setup of a battery electric vehicle is developed.

Regulated emissions, CO2-values, comfort, good driveability, high reliability and costs, this is the main frame for all future powertrain developments. In this frame, the diesel powertrain, not only for passenger cars, but also for commercial vehicle applications, faces some challenges in order to fulfil the future European and current US emission legislations while keeping the fuel consumption benefit, good driveability and an acceptable cost frame. One of these challenges is the varying fuel qualities of diesel fuel in different countries including different cetane number, volatility, sulphur content and different molecular composition. In addition to that in the future, more and more alternative fuels with various fuel qualities and properties will be launched into the market for economical and environmental reasons. At present, the control algorithms of the injection system applied in most diesel engines is open loop control.

This paper analyzes different concepts for storage and recuperation of kinetic energy during braking operation in a forklift truck application. The reduction of fuel consumption is one of the challenges for on and off-road vehicles. Starting from a conventional hydrostatic transmission, secondary hydraulic control and a hybrid solution are investigated. Wasting kinetic energy during braking operation of mobile working machines in cyclic applications and converting it into heat energy instead of reusable energy is a very inefficient principle still used in industry. Rising energy costs, enhanced government guidelines and increased environmental awareness require more efficient drive concepts for the next decades. Recuperation of kinetic energy during braking operation provides the opportunity of increasing the efficiency of mobile working machines. Efficient recuperation of kinetic energy requires a proper application and a low-loss system design.

Due to the complex powertrain layout in hybrid vehicles, different configurations concerning internal combustion engine, electric motor and transmission can be combined - as is demonstrated by currently produced hybrid vehicles ([1], [2]). At the Institute for Combustion Engines (VKA) at RWTH Aachen University a combination of simulation, Design of Experiments (DoE) and numerical optimization methods was used to optimize the combustion engine, the powertrain configuration and the operation strategy in hybrid powertrains. A parametric description allows a variation of the main hybrid parameters. Parallel as well as power-split hybrid powertrain configurations were optimized with regard to minimum fuel consumption in the New European Driving Cycle (NEDC). Besides the definition of the optimum configuration for engine, powertrain and operation strategy this approach offers the possibility to predict the fuel consumption for any modifications of the hybrid powertrains.

The droplet velocity is an important parameter for breakup, evaporation, and combustion of Diesel sprays, but it is very difficult to measure it by widely used laser diagnostic techniques like PDA, PIV and LCV under realistic high-pressure and high-temperature conditions. This is basically caused by laser beam steering and multiple scattering of light due to very high droplet densities, in particular close to the nozzle. It was demonstrated recently, that these problems can be greatly reduced by the laser flow tagging (LFT) technique. For this purpose, the model fuel is doped with a phosphorescent tracer. A number of droplet groups within the spray are tagged by illuminating them with focused beams of a pulsed laser, and their velocities are measured by recording the phosphorescence twice after each laser pulse using a double-frame ICCD.

During the past years, there has been an increasing tendency to seriously question and break up old and ingrained structures in combustion engine testing. The reason for this is the continuously increasing number of engine and vehicle variants and a variety of applications resulting from it, which significantly push up development costs and times when carrying out the classical testing patterns. The following article by FEV Motorentechnik GmbH introduces a comprehensive test methodology for purposeful endurance testing of modern drive units (in particular from the fields of passenger cars and commercial vehicles). The procedure and the testing philosophy are explained in detail, illustrated by a concrete development example.

The technology used in hybrid vehicle concepts is significantly different from conventional vehicle technology with consequences also for the noise and vibration behavior. In conventional vehicles, certain noise phenomena are masked by the engine noise. In situations where the combustion engine is turned off in hybrid vehicle concepts, these noise components can become dominant and annoying. In hybrid concepts, the driving condition is often decoupled from the operation state of the combustion engine, which leads to unusual and unexpected acoustical behavior. New acoustic phenomena such as magnetic noise due to recuperation occur, caused by new components and driving conditions. The analysis of this recuperation noise by means of interior noise simulation shows, that it is not only induced by the powertrain radiation but also by the noise path via the powertrain mounts. The additional degrees of freedom of the hybrid drive train can also be used to improve the vibrational behavior.

The modern engine development process is characterized by shorter development cycles and a reduced number of prototypes. However, simultaneously exhaust after-treatment and emission testing is becoming increasingly more sophisticated. It is expected that predictive simulation tools that encompass the entire powertrain can potentially improve the efficiency of the calibration process. The testing of an ECU using a HiL system requires a real-time model. Additionally, if the initial parameters of the ECU are to be defined and tested, the model has to be more accurate than is typical for ECU functional testing. It is possible to enhance the generalization capability of the simulation, with neuronal network sub-models embedded into the architecture of a physical model, while still maintaining real-time execution. This paper emphasizes the experimental investigation and physical modeling of the port fuel injected SI engine.

The modern engine design process is characterized by shorter development cycles and a reduced number of prototypes. However, simultaneously exhaust after-treatment and emission testing is becoming increasingly more sophisticated. The introduction of predictive real-time simulation tools that represent the entire powertrain can likely contribute to improving the efficiency of the calibration process. Engine models, which are purely based on physical first principles, are usually not capable of real-time applications, especially if the simulation is focused on cold start and warm-up behavior. However, the initial data definition for the ECU using a Hardware-in-the-Loop (HiL)-Simulator requires a model with both real-time capability and sufficient accuracy. The use of artificial intelligence systems becomes necessary, e.g. neural networks. Methods, structures and the realization of a hybrid real-time model are presented in this paper, which combines physical and neural network models.

Environmental concern demands that emissions and fuel consumption of vehicles have to improve considerably in the next 10 years. New technologies for gasoline engines, downsizing with high boosting, direct injection and fully variable valve train systems, are being developed. For Diesel engines, improved components including piezobased injectors and particle filters are expected. In the drive train new starter-generator systems as well as automated manual transmissions are being developed. In parallel alternative fuels are investigated and the use of hybrid drives and fuel cells are developed. This paper reports the progress made in the recent years and gives a comparative assessment on the different technologies with a prediction of the introduction dates and volumes into the market.

Today, automated vehicles mostly rely on ego vehicle sensors such as cameras, radar or LiDAR sensors that are limited in their sensing capability and range. Vehicle-to-everything (V2X) communication has the potential to appropriately complement these sensors and even allow for a cooperative, proactive interaction of vehicles. As such, V2X communication might play a vital role on the way to smart and efficient traffic solutions. In the public funded research project UK Autodrive, we are currently investigating and experimentally evaluating V2X-based applications based on dedicated short range communication (DSRC). Moreover, the novel application intersection priority management (IPM) is part of the research project. IPM aims at automating intersections in such a way that vehicles can pass safely and even more efficiently without the use of traffic lights or signs.

A main focus of development in modern SI engine technology is variable valve timing, which implies a high potential of improvement regarding fuel consumption and emissions. Variable opening, period and lift of inlet and outlet valves enable numerous possibilities to alter gas exchange and combustion. However, this additional variability generates special demands on the calibration process of specific engine control devices, particularly under cold start and warm-up conditions. This paper presents procedures, based on Hardware-in-the-Loop (HiL) simulation, to support the classical calibration task efficiently. An existing approach is extended, such that a virtual combustion engine is available including additional valve timing variability. Engine models based purely on physical first principles are often not capable of real time execution. However, the definition of initial parameters for the ECU requires a model with both real time capability and sufficient accuracy.

Current simulation tools for the investigation of the dynamic system response as well as for the component stresses on the basis of multi-body and finite-element techniques are integral part of today's powertrain development efforts. These tools are typical used for the analysis and optimization of shafts, clutches, chain/belt drives, bearings, levers, brackets, housings and many other components. An exception is made by gears which today are still frequently investigated by the help of semi-empirical methods based on DIN, ISO, AGMA and the specific knowledge base of well experienced developers. The main difficulty is that the gears are rolling off via large contact surfaces with complex nonlinear mechanical contact properties. Within the scope of research work FEV developed a new method for the analysis and optimization of gear drives based on comercial multi-body and finite-element software platforms.

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.

Due to the future application of combustion engines in small and hybrid vehicles, the demand for high efficiency with low mass and compact engine design is of prime importance. The diesel engine, with its outstanding thermal efficiency, is a well suited candidate for such applications. In order to realize these targets, future diesel engines will need to have increasingly higher specific output combined with increased power to weight ratios. This is therefore driving the need for new designs of 3 and/or 4 cylinder, small bore engines of low displacement, sub 1.5l. Recent work on combustion development, has shown that combustion systems, ports, valves and injector sizes are available for bore sizes down to 65 mm.

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.

In order to reduce engine out CO2 emissions, it is a main subject to find new alternative fuels from renewable sources. For identifying the specification of an optimized fuel for engine combustion, it is essential to understand the details of combustion and pollutant formation. For obtaining a better understanding of the flame behavior, dynamic structure large eddy simulations are a method of choice. In the investigation presented in this paper, an n-heptane spray flame is simulated under engine relevant conditions starting at a pressure of 50 bar and a temperature of 800 K. Measurements are conducted at a high-pressure vessel with the same conditions. Liquid penetration length is measured with Mie-Scatterlight, gaseous penetration length with Shadowgraphy and lift-off length as well as ignition delay with OH*-Radiation. In addition to these global high-speed measurement techniques, detailed spectroscopic laser measurements are conducted at the n-heptane flame.