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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.

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.

Exhaust aftertreatment systems must function sufficiently over the full useful life of a vehicle. In Europe this is currently defined as 160.000 km. With the introduction of Euro 7 it is expected that the required mileage will be extended to 240.000 km. This will then be consistent with the US legislation. In order to quantify the emission impact of exhaust system degradation, an Euro 7 exhaust aftertreatment system is aged by different accelerated approaches: application of the Standard Bench Cycle, the ZDAKW cycle, a novel ash loading method and borderline aging. The results depict the impact of oil ash on the oxygen storage capacity. For tailpipe emissions, the maximum peak temperatures are the dominant aging factor. The cold start performance is effected by both, thermal degradation and ash accumulation. An evaluation of this emission increase requires appropriate benchmarks.

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.

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.

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.

To reduce hydrocarbon and particle emissions as well as irregular combustion phenomena, the identification and quantification of possible oil sources in the combustion chamber of the direct injection gasoline engine are of main interest. The aim of this research activity is to fundamentally investigate the formation of locally increased lubricating oil concentration in the combustion chamber. For this purpose, the oil sources are considered separately from each other and divided into two groups - piston/compression ring and lubricating film on the liner. The associated oil emissions and their influence on the engine combustion process are the core of the investigations.

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 demand for lower CO2 emissions requires not just the optimization of every single component but the complete system. For a transmission system, it is important to optimize the transmission hardware as we well as the interaction of powertrain components. For automatic transmission with wide ratio spreads, the main losses are caused by the actuation system, which can be reduced with use of ondemand actuation systems. In this paper, a new on-demand electromechanical actuation system with validation results on a clutch test bench is presented. The electro-mechanical actuator shows an increase in the efficiency of 4.1 % compared to the conventional hydraulic actuation in a simulated NEDC (New European Driving Cycle) cycle. This increase is based on the powerless end positions of the actuator (engaged and disengaged clutch). The thermal tension and wear are compensated with a disk spring. This allows a stable control over service life.

Maintaining low NOx emissions over the operating range of diesel engines continues to be a major issue. However, optical measurements of nitric oxide (NO) are lacking particularly in the core of diesel jets, i.e. in the region of premixed combustion close to the spray axis. This is basically caused by severe attenuation of both the laser light and fluorescent emission in laser-induced fluorescence (LIF) applications. Light extinction is reduced by keeping absorption path lengths relatively short in this work, by investigating diesel jets in a combustion vessel instead of an engine. Furthermore, the NO-detection threshold is improved by conducting 1-d line measurements instead of 2-d imaging. The NO-LIF data are corrected for light attenuation by combined LIF and spontaneous Raman scattering. The quantified maximum light attenuation is significantly lower than in comparable previous works, and its wavelength dependence is surprisingly weak.

Pilot injection (PI) during the negative-valve-overlap (NVO) period is one method to improve control of combustion in gasoline controlled auto-ignition engines. This is generally attributed to both chemical and thermal effects. However, there are little experimental data on active species formed by the combusting PI and their effect on main combustion in real engines. Thus, it is the objective of the current study to apply and assess optical in-cylinder diagnostics for these species. Firstly, the occurrence and nature of combustion during the NVO period is investigated by spectrally-resolved multi-species flame luminescence measurements. OH*, CH*, HCO*, CO-continuum chemiluminescence, and soot luminosity are recorded. Secondly, spectrally-, spatially-, and cycle-resolved laser-induced fluorescence measurements of formaldehyde are conducted. It is attempted to find a cycle-resolved measure of the chemical effect of PI.

PlugIn Hybrid Electric Vehicles (PHEV) offer the opportunity to experience electric driving without the risk of vehicle break-down due to a low battery charge state. Thus, PHEV's represent an attractive means of meeting future CO2-legislation. PHEV batteries must fulfill a divergent list of requirements: on the one hand, the battery must supply sufficient energy to ensure it can be driven an appropriate distance in EV-mode. On the other hand, even with a low state-of-charge (SOC), the battery must supply sufficient power to assist the engine in vehicle acceleration or to recuperate on deceleration. This leads to a compromise in terms of cell selection. Fundamentally, high energy cells cannot provide high charge and discharge rates and high power cells cannot provide sufficient energy.

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.

The performance of high voltage batteries is the key factor for further success of electric vehicles. The primary areas for battery development include high voltage (HV) and functional safety, maximum power and usable energy, battery life, packaging and weight reduction. This paper explains the development of the HV battery and the battery management system for the FEV Liona fleet, a retrofit of a pure electric powertrain into a FIAT 500. The multi-disciplinary process used to develop this program includes electrical, mechanical and functional aspects. The layout of the electrical system includes cell selection, layout of modules and the interconnection of twelve modules to a battery pack. The mechanical design of mounting the battery under the floor addresses the housing issues regarding robustness and sealing, the packaging into the vehicle as well as the positioning of the HV components inside the battery.

High levels of exhaust temperature or rich mixtures are necessary for the regeneration of today's diesel particulate filters or NOx catalysts. Therefore, late main injection or post injection is an effective strategy but leads to the well-known problem of lubricating oil dilution depending on the geometry, rail pressure and injection strategy. In this paper a method is developed to simulate fuel entrainment into the lubricating oil wall film in the diesel combustion chamber to predict oil dilution in an early design stage prior to hardware availability for durability testing. The simulation method integrates a newly developed droplet-film interaction model and is compared to results of an optical single-cylinder diesel engine and a similar thermodynamic single-cylinder test engine. Phenomena of diesel post injection like igniting early post injection or split post injections with short energizing times are considered in this paper.

Partly competing objectives, as low fuel consumption, low friction, long oil maintenance rate, and at the same time lowest exhaust emissions have to be fulfilled. Diminishing resources, continuously reduced development periods, and shortened product cycles yield detailed knowledge about oil consumption mechanisms in combustion engines to be essential. There are different ways for the lubricating oil to enter the combustion chamber: for example as blow-by gas, leakage past valve stem seals, piston rings (reverse blow-by) and evaporation from the cylinder liner wall and the combustion chamber. For a further reduction of oil consumption the investigation of these mechanisms has become more and more important. In this paper the influence of the mixture formation and the resulting fuel content in the cylinder liner wall film on the lubricant oil emission was examined.

The presented paper deals with the set-up and performance of a newly developed control system as well as with achieved engine results. This control system is able to control the entire cylinder pressure trace by using a flexible rate shaping injector and iterative learning control (ILC). Standard thermodynamic cycles, like isobaric and Seiliger cycles, and a newly suggested class of cycles are generated and analyzed on a single cylinder engine. With this control system an extremely flexible tool for optimization of combustion processes is available to exploit the full potential of injection rate- shaping on diesel engines.

Within a public founded project test cell investigations were undertaken to identify parameters which predominantly influence the development of critical deposits in injection nozzles. A medium-duty diesel engine was operated in two different coking cycles with a zinc-free lubricant. One of the cycles is dominated by rated power, while the second includes a wide area of the operation range. During the experiments the temperatures at the nozzle tip, the geometries of the nozzle orifice and fuel properties were varied. For a detailed analysis of the deposits methods of electron microscopy were deployed. In the course of the project optical access to all areas in the nozzle was achieved. The experiments were evaluated by means of the monitoring of power output and fuel flow at rated power. The usage of a SEM (scanning electron microscope) and a TEM (transmission electron microscope) revealed images of the deposits with a magnification of up to 160 000.

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.