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Hybrid and electric vehicles present a promising trade-off between the necessary reductions in emissions and fuel consumption, the improvement in driving pleasure and performance of today's and tomorrow's vehicles. These hybrid vehicles rely primarily on electronics for the control and the coordination of the different sub-systems or components. The number and complexity of the functions distributed over many control units is increasing in these vehicles. Functional safety, defined as absence of unacceptable risk due to the hazards caused by mal-function in the electric or electronic systems is becoming a key factor in the development of modern vehicles such as electric and hybrid vehicles. This important increase in functional safety-related issues has raised the need for the automotive industry to develop its own functional safety standard, ISO 26262.

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.

For on- and off-highway applications in 2012/2014 new legislative emissions requirements will be applied for both European (EURO 6/stage 4) and US (US 2010/Tier4 final) standards. Specifically the NOX-emission limit will be lowered down to 0.46 g/kWh (net power ≻ 56 kW (EU)/130 kW (US) - 560 kW). While for the previous emissions legislation various ways could be used to stay within the emissions limits (engine internal and aftertreatment measures), DeNOX-aftertreatment systems will be mandatory to reach future limits. In these kinds of applications fuel consumption of the engines is a very decisive selling argument for customers. Total cost of ownership needs to be as low as possible. The trade-off between fuel consumption and NOX emissions forces manufacturers to find an optimal solution, especially with regard to increasing fuel prices. In state-of-the-art calibration processes the aftertreatment system is considered separately from the calibration of the thermodynamics.

Homogeneous charge compression ignition (HCCI) is a part load, low-temperature combustion process which operates at lean mixtures and produces ultra-low NOX emissions. As opposed to SI engines that use a spark to control combustion timing, HCCI combustion is enabled by compression induced autoignition which is characterized by rapid global and spatial combustion yielding fuel efficiency benefits. This process is highly dependent on the in-cylinder state, including pressure, temperature and trapped mass. The absence of a direct combustion control proves to be a major challenge and results in unstable engine operation especially at the limits of the narrow operation range. In recent studies, direct water injection is used in HCCI combustion to stabilize combustion and increase the operation range. This paper outlines the thermodynamic influence and evaluation of the potential of water injection for HCCI combustion.

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 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.

Depending on a vehicles drive cycle, an improvement of the overall drivetrain efficiency does not necessarily have to go along with an improvement of its mileage. In here the ratio of energy to overcome rolling resistance, aerodynamic drag, acceleration and energy wasted directly in wheel brakes is responsible for potentially differing trends. A detailed knowledge of energy flows, sources and sinks makes up a substantial step into optimizing any drive train. Most fuel energy leaves the drivetrain via exhaust pipes. Next to usable mechanical energy, a big amount is spent to heat up the system directly or to overcome drive train friction, which is converted into heat to warm up the system additionally. An in depth quantification of the most important energy flows for an upper middle-sized class gasoline powered drive train is given as results of warm-up cycle simulations.

The accuracy of soot estimation is - besides thermal management – one of the key requirements for successful DPF applications. With the implementation of more stringent emissions regulations and requirements for fuel efficiency the importance of high quality soot mass estimation becomes even more relevant. The durability targets for T2B5 and Euro 6 require accurate soot load detection under all driving profiles and customer specific environments – from low speed delivery cycles to high speed extra urban driving profiles. The most fuel and CO2 efficient regeneration strategy relies on knowledge of the current soot mass in the DPF. This paper describes several options of soot mass estimation: From an empirical engine out emissions model, combined with a physical soot oxidation model to a physical model in which the pressure drop signal combined with other parameters is used to determine the filter load.

Due to increasingly strict emission regulations, the demand for internal combustion engine performance has enhanced. Combustion stability is one of the main research focuses due to its impacts on the emission level. Moreover, the combustion instability becomes more significant under the lean combustion concept, which is an essential direction of internal combustion engine development. The combustion instability is represented as the cycle-to-cycle variation. This paper presents a quasi-dimensional model system for predicting the cycle-to-cycle variation in 0D/1D simulation. The modeling is based on the cause-and-effect chain of cycle-to-cycle variation of spark ignition engines, which is established through the flow field analysis of large eddy simulation results [1]. In the model system, varying parameters are turbulent kinetic energy, the distribution of air-to-fuel equivalence ratio, and the in-cylinder velocity field.

The increasingly stringent limits on pollutant emissions from internal combustion engine-powered vehicles require the optimization of advanced combustion systems by means of virtual development and simulation tools. Among the gaseous emissions from spark-ignition engines, the unburned hydrocarbon (HC) emissions are the most challenging species to simulate because of the complexity of the multiple physical and chemical mechanisms that contribute to their emission. These mechanisms are mainly three-dimensional (3D) resulting from multi-phase physics - e.g., fuel injection, oil-film layer, etc. - and are difficult to predict even in complex 3D computational fluid-dynamic (CFD) simulations. Phenomenological models describing the relationships between the physical-chemical phenomena are of great interest for the modeling and simplification of such complex mechanisms.

In this paper, boosting strategies are investigated for part load operation of typical fuel-cell-systems. The optimal strategy can mainly be obtained by simulation. The boosting strategy is one of the most essential parameters for design and operation of a fuel-cell-system. High pressure ratios enable high power densities, low size and weight. Simultaneously, the demands in humidification and water recovery for today's systems are reduced. But power consumption and design effort of the system increases strongly with the pressure level. Therefore, the main focus must be on the system efficiencies at part load. In addition, certain boundary conditions like the inlet temperature of the fuel-cell stack must be maintained. With high pressure levels the humidification of the intake air before, within or after the compressor is not sufficient to dissipate enough heat. Vaporization during the compression process shows efficiency advantages while the needs in heat dissipation decreases.

Model-based control strategies along with an adapted calibration process become more important in the overall vehicle development process. The main drivers for this development trend are increasing numbers of vehicle variants and more complex engine hardware, which is required to fulfill the more and more stringent emission legislation and fuel consumption norms. Upcoming fundamental changes in the homologation process with EU 6c, covering an extended range of different operational and ambient conditions, are suspected to intensify this trend. One main reason for the increased calibration effort is the use of various complex aftertreatment technologies amongst different vehicle applications, requiring numerous combustion modes. The different combustion modes range from heating strategies for active Diesel Particulate Filter (DPF) regeneration or early SCR light-off and rich combustion modes to purge the NOx storage catalyst (NSC) up to partially premixed combustion modes.

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.

One of the challenges faced when using Li-ion batteries in electric vehicles is to keep the cell temperatures below a given threshold. Mathematical modeling would indeed be an efficient tool to test virtually this requirement and accelerate the battery product lifecycle. Moreover, temperature predicting models could potentially be used on-board to decrease the limitations associated with sensor based temperature feedbacks. Accordingly, we present a complete modeling procedure which was used to calculate the cell temperatures during a given electric vehicle trip. The procedure includes a simple vehicle dynamics model, an equivalent circuit battery model, and a 3D finite element thermal model. Model parameters were identified from measurements taken during constant current and pulse current discharge tests. The cell temperatures corresponding to an actual electric vehicle trip were calculated and compared with measured values.

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.

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.

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.

This paper describes an alternative catalyst aging process using a hot gas test stand for thermal aging. The solution presented is characterized by a burner technology that is combined with a combustion enhancement, which allows stoichiometric and rich operating conditions to simulate engine exhaust gases. The resulting efficiency was increased and the operation limits were broadened, compared to combustion engines that are typically used for catalyst aging. The primary modification that enabled this achievement was the recirculation of exhaust gas downstream from catalyst back to the burner. The burner allows the running simplified dynamic durability cycles, which are the standard bench cycle that is defined by the legislation as alternative aging procedure and the fuel shut-off simulation cycle ZDAKW. The hot gas test stand approach has been compared to the conventional engine test bench method.

This paper introduces different modeling approaches of crankshafts, compares the refinement levels and discusses the difference between the results of the crankshaft durability calculation methodologies. A V6 crankshaft is considered for the comparison of the refinement levels depending on the deviation between the signals such as main bearing forces and deflection angle. Although a good correlation is observed between the results in low speed range, the deviation is evident through the mid to high speed ranges. The deviation amplitude differs depending on the signal being observed and model being used. An inline 4 crankshaft is considered for the comparison of the durability results. The analysis results show that the durability potential is underestimated with a classical crankshaft calculation approach which leads to a limitation of maximum speed of 5500 rpm.

Combustion and pollutant formation in a new recently introduced Common-Rail DI Diesel engine concept with roof-shaped combustion chamber and tumble charge motion are numerically investigated using the Representative Interactive Flamelet concept (RIF). A reference case with a cup shaped piston bowl for full load operating conditions is considered in detail. In addition to the reference case, three more cases are investigated with a variation of start of injection (SOI). A surrogate fuel consisting of n-decane (70% liquid volume fraction) and α-methylnaphthalene (30% liquid volume fraction) is used in the simulation. The underlying complete reaction mechanism comprises 506 elementary reactions and 118 chemical species. Special emphasis is put on pollutant formation, in particular on the formation of NOx, where a new technique based on a three-dimensional transport equation within the flamelet framework is applied.