Due to the change in mobility to lower CO2 emissions, there is a turnaround in the automotive industry. The share of classic combustion engines with petrol or diesel fuel will continue to decline. As a result, the development capacities for ICEs will also decrease. Therefore, development process becomes an even greater challenge. The IFS has been researching in the application of artificial intelligence in the development process since 2019. Various successes have already been achieved here, e.g. in virtualizing the combustion chamber or the stack of a fuel cell with the help of neural networks. Since the majority of all AI projects fail, the application of current research projects has to be carried out at an early stage. In the course of the paper, first the combustion chamber of a hydrogen engine is modelled with neural networks. In contrast to the petrol engines used in the previous papers, the combustion speed of hydrogen combustion is much higher. Despite that, very good predictions can be made with the neural networks. The connection of the networks to the 0D-/1D-simulation software, GT-Suite, is shown as an example. Here, two different possibilities are examined via the FMU interface. In the first variant, an FMU of the neural networks is generated and then integrated into the software. This makes it possible to generate a user-friendly variant that can also be sent to a calculation cluster. This was used to do a benchmark with regard to the computing speed and prediction quality. The computing time could be accelerated by a factor of 4. In the second variant, an FMU is made from the simulation and coupled with the networks in Python. Since this also allows direct coupling with Python, an OpenAI Gym environment is set up for coupling with an RL agent. Following this, an RL agent for throttle control was trained.

The update of the Mercedes-Benz strategy from “Electric first” to “Electric only” is accelerating the transformation towards an emission-free future and placing the focus on fully electric drives (Mercedes-Benz, www.daimler.com/konzern/strategie/mercedes-benz-strategy-update-electric-drive.html , last accessed 2021/06/22.). In addition to radial flux motors, which have been very common to date, axial flux motors offer new possibilities for drive topologies due to their comparatively small axial installation space and serve as enabler for compact dual drive units, for example. The special potential of axial flux motors lies in their combination of an extraordinary power-to-size and power-to-weight ratio with the highest level of efficiency. (Yasa Limited, www.yasa.com/technology/ , last accessed 2021/12/2;3. The Yokeless And Segmented Armature Machine Developed For The LIFECar, University of Oxford, Hilary;). Taking the general requirements for the electric motor as a basis, the aim is to derive the mechanical requirements and determine the properties of the component parts. The standards for laminated sheet packages of radial flux motors that specify the electromagnetic and mechanical properties have been defined. So far, laminated sheet packages in the form of laminated back iron for rotors of axial flux motors have been specified in terms of their electromagnetic properties exclusively. The relevant standards therefore do not take into account any requirements relating to the axial strength and stiffness of laminated back iron. In this paper the author focuses on simulation and experimental validation of these mechanical properties of axial flux rotor back iron.

Due to increasing climate awareness and the introduction of much stricter exhaust emission legislation the internal combustion engine technology faces major challenges. Although the development and state of technology of internal combustion engines generally reached a very high level over the last years those need to be improved even more. Combining water injection with a diesel engine, therefore, seems to be the next logical step in developing a highly efficient drive train for future mobility. To investigate these potentials, a comprehensive evaluation of water injection on the diesel engine was carried out. This study covers >560 individual operating points on the test bench. The tests were carried out on a single-cylinder derived from a Euro 6d four-cylinder passenger car with the port water injection. Furthermore, a detailed pressure trace analysis (PTA) was performed to evaluate various aspects regarding combustion, emission, etc. The results show no significant effects of water injection on the combustion process, but great potential for NO x reduction. It has been shown that with the use of water injection at water-to-fuel rates of 25%, 50%, and 100%, NO x reduction without deterioration of soot levels can be achieved in 62%, 40%, and 20% of the experiments, respectively. Furthermore, water injection in combination with EGR offers additional reduction in NO x emissions.

State-of-the-art spark-ignition engines mainly rely on the quasi-hemispherical flame propagation combustion method. Despite significant development efforts to obtain high energy conversion efficiencies while avoiding knock phenomena, achieved indicated efficiencies remain around 35 - 40 %. Further optimizations are enabled by significant excess air dilution or increased combustion speed. However, flammability limits and decreasing flame speeds with increasing air dilution prevent substantial improvements. Pre-Chamber (PC) initiated jet ignition combustion systems improve flame stability and shift flammability limits towards higher dilution levels due to increased turbulence and a larger flame area in the early Main-Chamber (MC) combustion stages. Simultaneously, the much-increased combustion speed reduces knock tendency, allowing the implementation of an innovative combustion method: PC-initiated jet ignition coupled with Spark-Assisted Compression Ignition (SACI). The jets penetrating the MC establish a flame propagation combustion that – with appropriate boundary conditions – triggers a controlled volume reaction in the remaining charge. The resulting ultra-fast combustion process converges to the ideal thermodynamic constant-volume cycle leading to indicated efficiencies of >45%. However, implementing this combustion method requires precisely adjusted boundary conditions and a suitable geometrical design (e.g., compression ratio). This paper addresses the development of a fast-running quasi-dimensional burn rate model for PC-initiated SACI combustion to conduct robust design studies and complement existing testing methodologies (3D-CFD, experimental). The modeling approach considers two thermodynamic systems (PC and MC) connected through orifices. Both systems use the two-zone entrainment model for flame propagation combustion. Furthermore, the eventual MC volume reaction is modeled by a multi-pseudo-zone approach based on a distributed auto-ignition integral. The models are integrated into the so-called cylinder module developed at the Institute of Automotive Engineering Stuttgart and validated using measurement data of two single-cylinder research engines using different fuels (E100, RON95E10), loads (IMEP = 6 − 15 bar), excess air dilutions (λ = 1 − 2.8) and compression ratios (12.6 – 16.4), showing a satisfactory prediction of the burn rates and pressure curves.

The proportion of new registrations with battery-electric and hybrid powertrains is rising steadily. This shows the strong trend in the automotive industry away from conventional powertrains with internal combustion engines. The aim is to reduce the transport sector's contribution to CO2 emissions. However, it should be noted that this only applies when renewable energy is used. Studies show the relevance of the system boundaries under consideration, which makes the application of Life Cycle Assessment indispensable. According to these studies, the various types of powertrains differ only slightly in their greenhouse gas impact. Rather, the energy supply chain plays a significant role. Moreover, a ban on combustion engines would lead to an additional increase in cumulative CO2 emissions. An important aspect on the way to sustainable mobility solutions is addressing the existing fleet. The approximately 1.25 billion vehicles predominantly powered by internal combustion engines can make a significant contribution to reduce greenhouse gas emissions by using renewable fuels. Synthetic manufacturing pathways can improve the fuel composition and properties to also minimize pollutant emissions in addition to CO2. This can specifically benefit vehicles without particulate filters, reducing local emissions. The large number of different production paths of renewable fuels leads to a high diversification of components and properties. Methods are needed to optimize these for internal combustion engine operations. Since the change of the used fuel has far-reaching effects, a holistic approach is required. In the current work, different methods are presented to evaluate and optimize the effects on the sub-processes of gasoline engine combustion. As a results, requirements for renewable fuels can be defined which play an important role for the further development of process engineering and manufacturing for renewable fuels.

Nach Definition gelten Motoren die mit zwei unterschiedlichen Kraftstoffen betrieben werden können, als bivalentBetriebbivalenter. Dies bedeutet, dass die beiden Kraftstoffe gemeinsam im Fahrzeug mitgeführt werden und eine Umschaltung der Kraftstoffart ohne Hardwareänderung möglich ist.

Nach gängiger Hypothese ist ErdgasErdgasGrundlagen ein fossiler Energieträger, der wie Erdöl durch Umwandlungsprozesse organischer Stoffe unter hohem Druck und unter Abwesenheit von Sauerstoff im Erdinneren entstand und daher als Naturprodukt abhängig vom geologischen Fundort in seiner Zusammensetzung schwankt. Der Hauptanteil ist immer MethanMethan, der zwischen 75 bis 98 % variiert. Die weiteren Anteile bestehen hauptsächlich aus Stickstoff, Ethan und Kohlenstoffdioxid.

Prospective combustion engine applications require the highest possible energy conversion efficiencies for environmental and economic sustainability. For conventional Spark-Ignition (SI) engines, the quasi-hemispherical flame propagation combustion method can only be significantly optimized in combination with high excess air dilution or increased combustion speed. However, with increasing excess air dilution, this is difficult due to decreasing flame speeds and flammability limits. Pre-Chamber (PC) initiated jet ignition combustion systems significantly shift the flammability and flame stability limits towards higher dilution areas due to high levels of introduced turbulence and a significantly increased flame area in early combustion stages, leading to considerably increased combustion speeds and high efficiencies. By now, vehicle implementations of PC-initiated combustion systems remain niche applications, especially in combination with lean mixtures. This is also due to challenges regarding cold-start, combustion stability at low loads, and emissions. Nevertheless, PC ignition systems allow overall engine efficiencies >45%. Therefore, a market launch of an engine using globally lean mixtures ignited by a PC system is desirable. This requires a fast-running and predictive physical model to conduct robust design studies and complement existing testing methodologies (3D-CFD, experimental). This paper addresses the development of a quasi-dimensional burn rate model for PC ignition combustion systems. The presented modeling approach combines the well-established two-zone entrainment model (main-chamber) with a semi-empirical PC model that aims to detect the PC influence on the main-chamber combustion. Dedicated models predict the impact of the jet-induced turbulence and the increased flame area. The models are integrated into the so-called cylinder module developed at IFS (Institute of Automotive Engineering Stuttgart). For the model validation, measurement data of a single-cylinder research engine using different fuels (E1001, RON95E102), loads (IMEP = 6 − 15 bar), excess air dilutions (λ = 1 − 2) and compression ratios (16.41, 12.62) are used, showing a satisfactory prediction of the burn rate and pressure curve.

For metrological traceability of pressure sensors, static calibration procedures are standard. If these sensors are used in dynamic systems, unexpected phenomena or deviations occur in the recorded signal characteristics. By setting up a dynamic pressure calibration facility, it is possible to investigate this dynamic behavior and learn about the interactions between sensor and investigated system. To be able to identify the disturbing influences and interactions occurring during calibration and in subsequent measurement use, it is necessary to increase the existing understanding of the system. In the context of the contribution, the calibration procedure used, its properties such as repeatability, reproducibility as well as the system interaction of the influencing variables are analyzed. Special attention is paid to the effects of varying gas content in the calibration medium, its influence on the system and on the observed phenomena occurring. By varying the system parameters, while keeping an eye on shock amplitude and gradient, the hypotheses suspected in prior publications can be confirmed. Observing the influences of signal processing and sensor geometry on the shape of pressure traces clearly shows the complexity of interactions of the system components. All performed measurements impressively demonstrate the need to separate the influences in dynamically excited pressure-carrying systems, to better understand their causes, and thus to be able to perform precise sensor classification and calibration. Using a setup for dynamic calibration of pressure sensors, the article discusses a variety of phenomena of multiphase hydraulic systems and provides detailed insights into fluid mechanical relationships.

In this paper, three different possibilities of torque distribution as well as three different kinds of electric motor configurations for an electric all-wheel drive vehicle are simulated. The used vehicle for the observation has two electric drive systems, each integrated into an E-Axle. Each E-Axle has either an induction or a permanent magnet synchronous motor as well as a two-speed-gearbox and a separating clutch. The three different torque distributions include a 50/50-torque split between front- and rear-axle, a front-axle-drive with a rear-axle-drive option for high loads and an optimal torque distribution with consumption minimization strategy. The electric drives vary first by using two E-Axles with induction motors. Second, a variation with a permanent magnet synchronous motor on the front-axle and an induction motor on the rear-axle. Third, a configuration with both motors being permanent magnet synchronous motors. Each configuration is validated in three different load cases by varying the drive cycles as well as adding a 2.0 t trailer to the SUV base vehicle. In conclusion, the simulation results show the different effects of operational strategy and the configuration of the motors on the overall electric energy consumption of the all-wheel drive vehicle.

Future combustion engine applications require highest possible energy conversion efficiencies to reduce their environmental impact and be economically competitive. So far, spark-ignition (SI) engine combustion development mostly consisted of optimizing the hemispherical flame propagation combustion method. Thereby, a significant efficiency increase is only achievable in combination with high excess air dilution or increased combustion speed. However, with increasing excess air dilution, this is difficult due to decreasing flame speeds and flammability limits. Simultaneously, researchers have been investigating homogeneous charge compression ignition (HCCI) that achieves higher efficiencies due to its rapid volume reaction combustion and also enables high excess air dilution. However, the combustion is complex to control as it is initiated by auto-ignition (AI) processes. In-cylinder conditions reliably need to be reproduced to prevent damaging pre-ignitions. Consequently, HCCI has only been applied for low load operation. The spark-assisted compression ignition (SACI) represents a compromise between SI combustion and HCCI. Thereby, a flame propagation is initiated that triggers a controlled volume reaction in the remaining charge. By now, there is only one (mainly stoichiometric) application of SACI combustion in the market. In combination with lean mixtures, SACI allows overall efficiencies >40%. A market launch of a lean mixture SACI engine is therefore desirable. This requires a fast-running and predictive physical model to conduct robust concept studies in the early development process. This paper addresses the development of a quasi-dimensional burn rate model for the SACI combustion method. The modeling approach combines the well-established two-zone entrainment model (for flame propagation) with a multi pseudo-zone volume reaction model based on a distributed AI integral, which is linked to a detailed two-stage AI model. The model is integrated into the so-called cylinder module developed at IFS (Institute of Automotive Engineering Stuttgart). A validation versus measurement data shows a satisfactory prediction of the burn rate and pressure curve.

The path to the decarbonization of transport sector goes by the integrated use of different technologies, including natural gas engines, which represent an immediate and cost-effective solution in cutting CO2 emissions, thanks to the higher H/C ratio compared to commercial fuels. However, the engine design faces a number of challenges including the need for power density, cold start, combustion efficiency, emissions, while remaining profitable for application in commercial vehicles. With these constraints in mind, a consortium of different partners tackled the development of such an engine, financed by BMWI and resulting in a project called MethMag. Considering a gasoline engine of comparable power targets as a benchmark, the virtual development led to the design of a new combustion chamber, high-tumble channels, and a new piston, after optimization of the valve strategy, by using a full-variable valve train. In addition, different injector positions, and injector types were evaluated. Direct injection below intake valves was selected in combination with an active pre-chamber. The last was specifically designed for this engine, with an hollow-cone conventional gasoline injector and cooling possibility. The investigation of the different design combinations was possible using the fast response 3D-CFD-Tool QuickSim, developed at FKFS. The resulting single-cylinder engine is currently being manufatured, and it will be installed at Fraunhofer ICT for validation and further refinement. Following the performance prediction of the first manufactured geometry, the engine can operate ultra-lean up to λ ~ 1.8, with indicated efficiency higher than 42%.

Stricter pollutant emission regulations and CO2 reduction requirements for internal combustion engines make further development of gasoline engine combustion processes essential. Homogeneous lean-burn processes, also in combination with high powertrain hybridization, offer great potential for increasing efficiency. However, nitric oxide (NO) emissions increase due to excess air and the use of a conventional three-way catalytic converter is not effective because the excess air prevents the complete reduction of the produced NO. In stoichiometric operation, nitric oxide and carbon monoxide (CO) emissions are also expected to increase in importance with higher degrees of hybridization since engine starts with potentially cooled down exhaust gas after-treatment systems are expected to occur more frequently. Therefore, reliable prediction of NO and CO raw emissions is of crucial importance in engine design and calibration. The formation of NO and CO depends significantly on the air-fuel ratio and the temperatures in the burnt mixture. Accordingly, existing mixture inhomogeneities have a major influence on NO and CO formation, with research showing different behavior in stoichiometric and homogeneous-lean operation. Currently used 0D/1D emission models for NO and CO show large deviations from the measurement, especially in lean operation. Within an FVV project, a quasi-dimensional model based on a distribution function is developed to reproduce the influence of mixture inhomogeneities on emission formation.

One approach to avoid the soot/NOx-trade-off in conventional diesel engines is to reach a homogeneous air to fuel mixture before the start of combustion (SOC). There are already existing solutions for homogeneous mixtures with diesel fuel. Therefore, the diesel fuel must be vaporized before injection to reach comparable brake-specific fuel consumption (BSFC) to conventional diesel combustion without significant cylinder wall and piston impingement. However, with this type of homogeneous charge compression ignition (HCCI) it is impossible to control the combustion with the injection pattern and therefore it is not practical for robust ECU mapping. Hence, HCCI has never qualified for serial use. One way to counteract the resulting variance in SOC is a partially premixed charge in the combustion chamber before SOC. A high rate of exhaust gas recirculation (EGR) with injection-controlled combustion leads to ultra-low soot and NOx emissions in a so-called premixed charge compression ignition (PCCI) application. The possibility to use state-of-the-art components such as serial injectors, pistons and EGR system of conventional diesel engines qualifies PCCI for serial use. Furthermore, the pressure gradients are comparable to those of standard diesel combustion, which leads to known combustion noise and mechanical stress of the engine. In this project, a single-cylinder Mercedes-Benz engine is used to investigate PCCI combustion at IFS University of Stuttgart. The engine is fully equipped with pressure transducers (intake, in‑cylinder and exhaust). Boost and exhaust pressure are regulated externally. The high temperature EGR rate can be varied depending on the operating points. In addition, injection strategies and intake air temperature can be set independently in a wide range to gain a maximum spread of experimental data as basis for the simulation. The goal of this project is to establish a 0D-/1D-approach to predict ignition delays (ID) for PCCI operation with multiple injection strategies. Low and high-temperature combustion can be observed in many operating points. Therefore, the physical and chemical ID of low and high temperature combustion have to be validated regarding different injection strategies, EGR rates, intake and exhaust pressures, intake temperatures and engine load.

The driverless and electrically powered vehicle concept U-Shift enables a new type of flexibility and efficiency for the mobility of tomorrow by separating the drive unit (driveboard) and transport capsule. In combination with various capsule types, the driveboard is used to transport both people and goods. In a first step, a rollable Mock-up was built (U-Shift I project). The development of another prototype with extended functions for driverless driving (U-Shift II project) is described in this article. Automation – implementation of driverless operation based on sensor modules in the driveboard, supported by sensors in capsules and infrastructure. Chassis – integration of a lifting unit for flexible and quick capsule changes as well as a compact design of the wheel suspension. Drive train – design and implementation of a compact drive concept with wheel hub motors and a modular traction battery in connection with holistic energy and thermal management. Electrics/Electronics Architecture – Conception of a service-oriented architecture with distributed services in the driveboard, capsule and infrastructure. Vehicle structure – optimization of the load distribution in the driveboard and the capsules, as well as secure locking of the capsules on the vehicle. Citizen Participation – Dialogue on the Concept.