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As part of a system model, a PEM fuel cell stack model is presented for functional tests and pre-calibration of control units on hardware-in-the-loop (HiL) test benches. From the basic idea to couple a 1-D membrane model with a spatially distributed abstraction of the gas channel, a real-time capable 1-D+1-D PEM FC stack model is constructed. Fundament for the HiL usage is an explicit formulation of the commonly implicit model equations. With that, not only calculation time can be reduced, but also model accuracy is preserved. A validation using test bench data emphasizes the accuracy of the model. Finally, a runtime and eigenvalue analysis of the stack model proves the real-time capability.

The introduction of real driving emissions cycles and increasingly restrictive emissions regulations force the automotive industry to develop new and more efficient solutions for emission reductions. In particular, the cold start and catalyst heating conditions are crucial for modern cars because is when most of the emissions are produced. One interesting strategy to reduce the time required for catalyst heating is post-oxidation. It consists in operating the engine with a rich in-cylinder mixture and completing the oxidation of fuel inside the exhaust manifold. The result is an increase in temperature and enthalpy of the gases in the exhaust, therefore heating the three-way-catalyst. The following investigation focuses on the implementation of post-oxidation by means of scavenging in a four-cylinder, turbocharged, direct injection spark ignition engine. The investigation is based on detailed measurements that are carried out at the test-bench.

This paper presents a new method to derive the tire forces for simultaneous braking and cornering, by combining empirical models for pure braking and cornering using brush-model tire mechanics. The method is aimed at simulation of vehicle handling, and is of intermediate complexity such that it may be implemented and calibrated by the end user. The brush model states that the contact patch between the tire and the road is divided into an adhesion region where the rubber is gripping the road and a sliding region where the rubber slides on the road surface. The total force generated by the tire is then composed of components from these two regions. In the proposed method the adhesion and the sliding forces are extracted from an empirical pure-slip tire model and then scaled to account for the combined-slip condition. The combined-slip self-aligning torque is described likewise.

Today, mechanical systems such as the piston groups of internal combustion engines are simulated using Multiple Body-System (MBS) - approaches. However, the use of these models is restricted to a few problems as their adaptability is limited. The simulation of mechanical systems only by means of finite elements shows great promise for the future. In order to consider lubrication effects between two touching bodies of a mechanical system, a hydrodynamic contact algorithm (HCA) for finite element (FE) applications was developed. This paper discusses the technical background and first results for the simulation of a piston group using this new approach.

In order to achieve high customer satisfaction and to avoid high warranty costs caused by component failures of the power-train of hybrid electric vehicles (HEV), car manufacturers have to optimize the dimensioning of these elements. Hence, it is obligatory for them to gain knowledge about the different types of vehicle usage being predominant all over the world. Therefore, in this paper we present a Data Mining system that employs a Random Forest (RF) based dissimilarity measure in the dimensionality reduction technique t-Distributed Stochastic Neighbor Embedding (t-SNE) to automatically identify and visualize different types of vehicle usage by applying these methods to aggregated logged on-board data, i.e., load spectrum data. This kind of data is calculated and recorded directly on the control units of the vehicles and consists of aggregated numerical data, like the histogram of the velocity signal or the traveled distance of a vehicle.

Homogeneous Charge Compression Ignition (HCCI) combustion is a process dominated by chemical kinetics of the fuel-air mixture. The hottest part of the mixture ignites first, and compresses the rest of the charge, which then ignites after a short time lag. Crevices and boundary layers generally remain too cold to react, and result in substantial hydrocarbon and carbon monoxide emissions. Turbulence has little effect on HCCI combustion, and may be most important as a factor in determining temperature gradients and boundary layer thickness inside the cylinder. The importance of thermal gradients inside the cylinder makes it necessary to use an integrated fluid mechanics-chemical kinetics code for accurate predictions of HCCI combustion. However, the use of a fluid mechanics code with detailed chemical kinetics is too computationally intensive for today's computers.

The paper describes a novel method for calculating the residual gas fraction and the trapping efficiency in a 2 stroke engine. Assuming one dimensional compressible flow through the inlet and exhaust ports, the method estimates the instantaneous mass flowing in and out from the combustion chamber; later the residual gas fraction and trapping efficiency are estimated combining together the perfect displacement and perfect mixing scavenging models. It is assumed that when the intake port opens, the fresh mixture is pushing out the burned charge without any mixing and after a multiple of the time needed for the largest eddy to perform one rotation, the two gasses are instantly mixed up together and expelled. The result is a very simple algorithm that does not require much computational time and is able to estimate with high level of precision the trapping efficiency and the residual gas fraction in 2 stroke engines.

Intensified emission regulations as well as consumption demands lead to an increasing significance of carbon monoxide (CO) emissions for diesel engines. On the one hand, the quantity of CO raw emissions is important for emission predictions as well as for the exhaust gas after treatment. On the other hand, CO emissions are also important for predicting combustion efficiency and thus fuel consumption, since a part of unreleased chemical energy of the fuel is still bound in the CO molecules. Due to these reasons, a simulation model for predicting CO raw emissions was developed for diesel engines based on a phenomenological two-zone model. The CO model takes three main sources of CO emissions of diesel engines into account: Firstly, it contains a sub model that describes CO from local understoichiometric areas. Secondly, CO emissions from overmixed regions are considered.

This paper presents a phenomenological single-zone combustion model which meets the particular requirements of high speed DI diesel engines with common rail injection. Therefore the model takes into account the freely selectable pilot and main injection and is strongly focusing on result parameters like combustion noise or NO-emission which are affected by this split injection. The premixed combustion, the mixing-controlled combustion and the ignition delay are key parts of the model. The model was developed and tested on more than 200 samples from three different engine types of DaimlerChrysler passenger car engines equipped with common rail injection. A user-friendly parameterization and a short computing time was achieved thanks to the simple structure of the model.

As a consequence of reduced fuel consumption, direct injection gasoline engines have already prevailed against port fuel injection. However, in-cylinder fuel homogenization strongly depends on charge motion and injection strategies and can be challenging due to the reduced available time for mixture formation. An insufficient homogenization has generally a negative impact on the combustion and therefore also on efficiency and emissions. In order to reach the targets of the intensified CO2 emission reduction, further increase in efficiency of SI engines is essential. In this connection, 0D/1D simulation is a fundamental tool due to its application area in an early stage of development and its relatively low computational costs. Certainly, inhomogeneities are still not considered in quasi dimensional combustion models because the prediction of mixture formation is not included in the state of the art 0D/1D simulation.

Intensified emission regulations as well as consumption demands lead to an increasing significance of unburned hydrocarbon (UHC) emissions for diesel engines. On the one hand, the quantity of hydrocarbon (HC) raw emissions is important for emission predictions as well as for the exhaust after treatment. On the other hand, HC emissions are also important for predicting combustion efficiency and thus fuel consumption, since a part of unreleased chemical energy of the fuel is still bound in the HC molecules. Due to these reasons, a simulation model for predicting HC raw emissions was developed for diesel engines based on a phenomenological two-zone model. The HC model takes three main sources of HC emissions of diesel engines into account: Firstly, it contains a sub-model that describes the fuel dribble out of the injector after the end of injection. Secondly, HC emissions from cold peripheral zones near cylinder walls are determined in another sub-model.

In this paper a fast NOx model is presented which can be used for engine optimization, aftertreatment control or virtual mapping. A cylinder pressure trace is required as input data. High calculation speed is obtained by using table interpolation to calculate equilibrium temperatures and species concentrations. Test data from a single-cylinder engine and from a complete six-cylinder engine have been used for calibration and validation of the model. The model produces results of good agreement with emission measurements using approximately 50 combustion product zones and a calculation time of one second per engine cycle. Different compression ratios, EGR rates, injection timing, inlet pressures etc. were used in the validation tests.

Modern diesel engine injection systems are largely computer controlled. This opens the door for tailoring the fuel rate. Rate shaping in combination with increased injection pressure and nozzle design will play an important role in the efforts to maintain the superiority of the diesel engine in terms of fuel economy while meeting future demands on emissions. This approach to studying the potential of rate shaping in order to reduce NO formation is based on three sub-models. The first model calculates the fuel rate by using standard expressions for calculating the areas of the dimensioning flow paths in the nozzle and the corresponding discharge coefficients. In the second sub-model the heat release rate is described as a function of available fuel energy, i.e. fuel mass, in the cylinder. The third submodel is the multizone combustion model that calculates NO for a given heat release rate under assumed air /fuel ratios.

The automotive industry uses supercharging in combination with various EGR strategies to meet the increasing demand for Diesel engines with high efficiency and low engine emissions. The charge air is heated by the EGR and the compression in the turbocharger to such an extent that high NOx emissions and a reduction in engine performance occurs. For this reason, the charge air cooler cools down the charge air before it enters the air intake manifold. In case of low pressure EGR, the charge air possesses a high moisture content and under certain operating conditions an accumulation of condensate takes place within the charge air cooler. During demanding engine loads, the condensate is entrained from the charge air cooler into the combustion chamber, resulting in misfiring or severe engine damage.

A method for automatic reduction of detailed kinetic to skeletal mechanisms for complex fuels is proposed. The method is based on the simultaneous use of sensitivity and reaction-flow analysis. The resulting skeletal mechanism is valid for the parameter range of initial and boundary values, the analysis have been performed for. The gas-phase chemistry is analyzed in the end gas of an SI-engine, using a two-zone model. Species, not relevant for the occurrence of autoignition in the end gas, are defined as redundant. They are identified and eliminated for different pre-set levels of minimum reaction flow and sensitivity. The error in the mechanism increases monotony with increasing pre-set level of minimum reaction flow.

An experimental study of a glow plug engine combustion process has been performed by applying chemiluminescence imaging. The major intent was to understand what kind of combustion is present in a glow plug engine and how the combustion process behaves in a small volume and at high engine speed. To achieve this, images of natural emitted light were taken and filters were applied for isolating the formaldehyde and hydroxyl species. Images were taken in a model airplane engine, 4.11 cm3, modified for optical access. The pictures were acquired using a high speed camera capable of taking one photo every second or fourth crank angle degree, and consequently visualizing the progress of the combustion process. The images were taken with the same operating condition at two different engine speeds: 9600 and 13400 rpm. A mixture of 65% methanol, 20% nitromethane and 15% lubricant was used as fuel.

An experimental study of the Homogeneous Charge Compression Ignition (HCCI) combustion process has been conducted by using chemiluminescence imaging. The major intent was to characterize the flame structure and its transient behavior. To achieve this, time resolved images of the naturally emitted light were taken. Emitted light was studied by recording its spectral content and applying different filters to isolate species like OH and CH. Imaging was enabled by a truck-sized engine modified for optical access. An intensified digital camera was used for the imaging. Some imaging was done using a streak-camera, capable of taking eight arbitrarily spaced pictures during a single cycle, thus visualizing the progress of the combustion process. All imaging was done with similar operating conditions and a mixture of n-heptane and iso-octane was used as fuel. Some 20 crank angles before Top Dead Center (TDC), cool flames were found to exist.

In this paper, a theoretical study is presented where fuel rate shaping is analyzed in combination with EGR as a method for reducing NOx formation. The analytical tools used include an empirically based model to convert fuel rate to heat release rate, and a zero dimensional multizone combustion model to calculate combustion products, local flame temperatures and NOx emissions at a given heat release rate. The multizone model, which has been presented earlier, includes flame radiation and convective heat losses. Several geometrical shapes of the fuel rate are tested for different combustion timings and EGR rates. It is found that the fuel rate giving the lowest NOx formation varies with the injection timing. In order to lower the NOx emissions at normal and advanced injection timings, the fuel rate should have a rather long duration, and start at its maximum level followed by a slow decay.

Test of autonomous systems is mostly brute force and ad-hoc thus being neither efficient nor transparent. Though requirements invite for a situational transparency, a framework is missing to judge quality of requirements and derived test-cases. Practical challenges are state explosion, difficulty to derive corner cases, no systematic safety of the intended functionality as specified, lack of accepted KPI, etc. Maintaining a valid safety case is hardly possible with such adaptive systems and continuous software updates. To achieve trusted autonomous vehicles, test cases must be generated automatically while at same time providing coverage (e.g., indicating progress with KPI), efficiency (e.g., limiting the amount of regression testing) and transparency (e.g., showing how specific corner cases are tested in case of accidents). This paper provides a method for automatically generating test cases for AI-based autonomous systems and compares it with existing testing methods.

Introducing a new fuel alternative to gasoline is a very complex task. According to their short to mid term economical feasibility selected processes are modeled. Selected emissions and the primary energy demand of the production and the utilization of hydrogen and methanol as fuels for fuel cell powered buses are compared to conventional diesel powered buses. Different production routes for the alternative fuels are considered. Ecological and economical numbers are given and interpreted.