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A conventional coil ignition system and two breakdown ignition systems with different electrode configurations were compared in M.I.T.'s transparent square piston engine. The purpose was to gain a deeper understanding of how the breakdown and glow discharge phases affect flame development and engine performance. The engine was operated with a standard intake valve and with a shrouded intake valve to vary the characteristic burning rate of the engine. Cylinder pressure data were used to characterize the ignition-system performance. A newly developed schlieren system which provides two orthogonal views of the developing flame was used to define the initial flame growth process. The study shows that ignition systems with higher breakdown energy achieve a faster flame growth during the first 0.5 ms after spark onset for all conditions studied.

In this paper different compressor/expander concepts including mechanical superchargers, turbochargers and two-stage charging concepts are analysed with regard to their suitability for fuel cell applications. Special attention is focused on system designs which use the energy of the tail gases for driving the compressor. The net efficiencies of different system concepts at full load were calculated with a simulation model, based on Matlab/Simulink‘ and show, that with a single stage turbocharger in combination with a tail gas burner good efficiencies and high power densities can be obtained at a pressure level of more than 2.5 bar.

An improved plasma reactor has been designed, built and evaluated. It is characterized by a reduced power per area ratio, relative to previous designs, and includes several improvements to run the whole system safely in a car. The new reactor design includes a concentric inner high voltage electrode, a grounded outer electrode, a shielded high-voltage and high temperature resistant electrical connection. A generator controller has been developed for better control of operating conditions as required during the engine cold start phase. The new generator/reactor system was installed in the exhaust pipe of a gasoline direct injection engine. HC emissions could be reduced up to 30 % in the first 40 seconds of a cold start test. In addition to HC treatment the dielectric barrier discharge has also been investigated as a method for regenerating a diesel particulate trap.

Due to experimental challenges, combustion of diesel-like jets has rarely been characterized by laser-based quantitative multiscalar measurements. In this work, recently developed laser diagnostics for combustion temperature and the concentrations of CO, O2, and NO are applied to a diesel-like jet, using a highly oxygenated fuel. The diagnostic is based on spontaneous Raman scattering (SRS) and laser-induced fluorescence (LIF) methods. Line imaging yields multiscalar profiles across the jet cross section. Measurements turn out to be particularly accurate, because near-stoichiometric combustion occurs in the central region of the jet. Thereby, experimental cross-influences by light attenuation and interfering emissions are greatly reduced compared to the combustion of conventional, sooting diesel fuel jets. This is achieved by fuel oxygenation and enhanced premixing.

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.

The efficient operation of powertrain test benches in research and development is strongly influenced by the state of “health” of the functional test object. Hence, the use of Early Damage Detection Systems (EDDS) with Unit Under Test (UUT) monitoring is becoming increasingly popular. An EDDS should primarily avoid total loss of the test object and ensure that damaged parts are not completely destroyed, and can still be inspected. Therefore, any abnormality from the standard test object behavior, such as an exceeding of predefined limits, must be recognized at an early testing time, and must lead to a shutdown of the test bench operation. With sensors mounted on the test object, it is possible to isolate the damage cause in the event of its detection. Advanced EDDS configurations also optimize the predefined limits by learning new shutdown values according to the test object behavior within a very short time.

In order to lower friction losses and hence ensure low fuel consumption of internal combustion engines, borderline design of hydrodynamic cranktrain bearings is often unavoidable. To realize this without the risk of failures, detailed modelling of hydrodynamic effects is gaining more and more relevance. In this publication, an approach using flow simulation to couple hydrodynamic bearings with each other, will be introduced. This allows the state variables of the fluid in the supply bore of the crankshaft to be calculated transiently. One important aspect of this concerns the solubility of gas in oil. This paper demonstrates that the gas fractions in the supply bore of the crankshaft influence the pressures at the hydrodynamic bearings. Additionally, simulation results will be shown and also validated with measurement data.

To achieve global market and brand specific drivability characteristics as unique selling proposition for the increasing number of passenger car derivatives, an objectified evaluation approach for the drivability capabilities of the various cars is required. Thereto, it is necessary to evaluate the influence of different engine concepts in various complex and interlinked powertrain topologies during engine load change maneuvers based on physical criteria. Such an objectification approach enables frontloading of drivability related engineering tasks by the execution of drivability development and calibration work within vehicle subcomponent-specific closed-loop real-time co-simulation environments in early phases of a vehicle development program. So far, drivability functionalities could be developed and calibrated only towards the end of a vehicle development program, when test vehicles with a sufficient level of product maturity became available.

Engine processes are subject to cyclic fluctuations, which a have direct effect on the operating and emission behavior of the engine. The fluctuations in direct injection gasoline engines are induced and superimposed by the flow and the injection. In stratified operation they can cause serious operating problems, such as misfiring. The current state of knowledge on the formation and causes of cyclic fluctuations is rather limited, which can be attributed to the complex nature of flow instabilities. The current investigation analyzes the cyclic fluctuations of the in-cylinder charge motion and the mixture formation in a direct injection gasoline engine using laser-optical diagnostics and numerical 3D-calculation. Optical measurement techniques and pressure indication are used to measure flow, mixture formation, and combustion processes of the individual cycles.

Dielectric barrier discharge (DBD) offers the advantage to excite and dissociate molecules in the exhaust gas stream. Those dissociated and excited species are oxidizing or reducing harmful exhaust gas components. The advantage of a plasma chemical system in comparison to a catalytic measure for exhaust gas treatment is the instantaneous activity at ambient temperature from the starting of the engine. The investigations reviewed in this paper are dealing with the plasma chemical oxidation of hydrocarbons in the exhaust gas stream during cold start conditions. The article concerns the design and development of a plasma-system in order to decrease the hydrocarbon emissions from engine start till catalyst light off. Vehicle results in the New European Driving Cycle show a hydrocarbon conversion of more than 42% in the first 11 seconds from engine start. In this period nearly all types of hydrocarbon were reduced.

Powertrain electrification is becoming increasingly common in the transportation sector to address the challenges of global warming and deteriorating air quality. This paper introduces a novel “Build Your Hybrid” approach to experience and test various hybrid powertrain concepts. This approach is applied to the light commercial vehicles (LCV) segment due to the attractive combination of a Diesel engine and a partly electrified powertrain. For this purpose, a demonstrator vehicle has been set up with a flexible P02 hybrid topology and a prototype Hybrid Control Unit (HCU). Based on user input, the HCU software modifies the control functions and simulation models to emulate different sub-topologies and levels of hybridization in the demonstrator vehicle. Three powertrain concepts are considered for LCVs: HV P2, 48V P2 and 48V P0 hybrid. Dedicated hybrid control strategies are developed to take full advantage of the synergies of the electrical system and reduce CO2 and NOx emissions.

This paper focusses on the supply conditions of a connecting rod bearing. Thereto, a novel simulation approach is presented, which is based on a transient 3D-CFD multiphase flow simulation including the ability of gas dissolution and diffusive mass transfer. The model determines the pressure behavior and the gas bubble development in the oil supply system of a connecting rod bearing. It allows to visualize the flow behavior and the existence of gas bubbles in order to get a detailed impression of the physical occurrences. The experimental results from Maaßen [5], where a big gas bubble is formed in the supply bore by gas cavitation, are confirmed and used for validation. Further the flow behavior of free air ratios is investigated. The paper concludes that the supply conditions of a connecting rod bearing are strongly influenced by the gas bubble in terms of the fluid composition and the volume flow rate at the connecting rod bearing inlet.

Modeling thermal systems in Battery Electric Vehicles (BEVs) is crucial for enhancing energy efficiency through predictive control strategies, thereby extending vehicle range. A major obstacle in this modeling is the often limited availability of detailed system information. This research introduces a methodology using neural networks for system identification, a powerful technique capable of approximating the physical behavior of thermal systems with minimal data requirements. By employing black-box models, this approach supports the creation of optimization-based operational strategies, such as Model Predictive Control (MPC) and Reinforcement Learning-based Control (RL). The system identification process is executed using MATLAB Simulink, with virtual training data produced by validated Simulink models to establish the method's feasibility. The neural networks utilized for system identification are implemented in MATLAB code.

The calibration of Engine Control Units (ECUs) for road vehicles is challenged by stringent legal and environmental regulations, coupled with short development cycles. The growing number of vehicle variants, although sharing similar engines and control algorithms, requires different calibrations. Additionally, modern engines feature increasingly number of adjustment variables, along with complex parallel and nested conditions within the software, demanding a significant amount of measurement data during development. The current state-of-the-art (White Box) model-based ECU calibration proves effective but involves considerable effort for model construction and validation. This is often hindered by limited function documentation, available measurements, and hardware representation capabilities. This article introduces a model-based calibration approach using Neural Networks (Black Box) for two distinct ECU functional structures with minimal software documentation.