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The electrification of vehicles marks the introduction of new products to the automotive market and a continued effort to optimize their performance. The electric motor is an important component with which a further optimization of efficiency, power density and cost can be achieved. Additional benefits can be realized in the laminated core. This paper presents an innovative method to produce laminated stacks by a chain of processes different from conventional ways. The process chain presents a sequence of precision blanking, buffering, heat treatment and gluing. The effect of these processes is compared with existing solutions that typically contain some individual features but usually not the combination that enhances the overall effect. The heat treatment decreases residual stresses from previous process steps and reduces power losses in the laminated core. Depending on the design, benefits around 20% are found.

In the context of the energy transition, CO2-neutral solutions are of enormous importance for all sectors, but especially for the mobility sector. Hydrogen as an energy carrier has therefore been the focus of research and development for some time. However, the development of hydrogen combustion engines is in many respects still in the conception phase. Automotive system providers and engineering companies in the field of software development and simulation are showing great interest in the topic. In a joint project with the industrial partners Robert Bosch GmbH and AVL Germany, combustion in a H2-DI-engine for use in light-duty vehicles was methodically investigated using the CFD tool AVL FIRE®. The collaboration between Robert Bosch GmbH and the Institute for Mobile Systems (IMS) at Otto von Guericke University Magdeburg has produced a model study in which model approaches for the combustion of hydrogen can be analyzed.

Under the proposed Green Deal program, the European Union will aim to achieve zero net greenhouse gas (GHG) emissions by 2050. The interim target is to reduce GHG by 55% by 2030. In the current debate concerning CO2-neutral powertrains, bio-fuels and e-fuels could play an immediate and practical role in reducing lifecycle engine emissions. Hydrogen however, is one of the few practical fuels that can result in near zero CO2 emissions at the tailpipe, which is the main focus of current legislation. Compared to gasoline, hydrogen presents a higher laminar flame speed, a wider range of flammability and higher auto-ignition temperatures, making it among the most attractive of fuels for future engines. As a challenge, hydrogen requires a very low ignition energy. This may imply an increased susceptibility to Low Speed Pre-Ignition (LSPI), surface ignition and back-fire phenomena. In order to exploit hydrogen’s potential, the injection system plays an extremely important role.

Nowadays automobiles are getting smart and there is a growing need for the physical behavior to become part of its software. This behavior can be described in a compact form by differential equations obtained from modeling and simulation tools. In the offline simulation domain the Functional Mockup Interface (FMI) [3], a popular standard today supported by many tools, allows to integrate a model with solver (Co-Simulation FMU) into another simulation environment. These models cannot be directly integrated into embedded automotive software due to special restrictions with respect to hard real-time constraints and MISRA compliance. Another architectural restriction is organizing software components according to the AUTOSAR standard which is typically not supported by the physical modeling tools. On the other hand AUTOSAR generating tools do not have the required advanced symbolic and numerical features to process differential equations.

Software-in-the-Loop (SiL) test environments are the ideal virtual platforms for enabling continuous-development, -integration, -testing -delivery or -deployment commonly referred as Continuous-X (CX) of the complex functionalities in the current automotive industry. This trend especially is contributed by several factors such as the industry wide standardization of the model exchange formats, interfaces as well as architecture definitions. The approach of frontloading software testing with SiL test environments is predominantly advocated as well as already adopted by various Automotive OEMs, thereby the demand for innovating applicable methods is increasing. However, prominent usage of the existing monolithic architecture for interaction of various elements in the SiL environment, without regarding the separation between functional and non-functional test scope, is reducing the usability and thus limiting significantly the cost saving potential of CX with SiL.

Vibration testing is often carried out for automotive components to meet guidelines based on their operational environments. This is an iterative process wherein design changes may need to be made depending on an intermediate model’s dynamic behavior. Predicting the behavior based on modifications in boundary conditions of a well-defined numerical model imparts practical insights to the component’s responses. To this end, application of a general method using experimental free-free condition frequency response functions of a structure is discussed in the presented work. The procedure is shown to be useful for prediction of responses when kinematic boundary conditions are applied, without the need for an actual measurement. This approach is outlined in the paper and is applied to datasets where dynamic modifications are made at multiple boundary nodes.

The prime factor which influences noise and vibrations of electro-mechanical drives is wear at the components. This paper discusses the numerical methods developed for abrasion, vibration calculations and the coupling between wear and Noise Vibration and Harshness (NVH) models of the drive unit. The vibration domain model, initially, focuses on the calculations of mechanical excitations at the gear shafts which are generated via a nonlinear dynamic model. Furthermore, the bearings are studied for the influences on their stiffness and eventually their impact on the harmonics of the drivetrain. Later, free and forced vibrations of the complete drivetrain are simulated via a steady-state dynamic model. Consequently, the paper concentrates on the abrasion calculations at the gears. Wear is a complex process and understanding it is essential for determining the vibro-acoustics characteristics.

Acoustics and vibrations are amongst the foremost indicators in perceiving the quality of drive units. Analyzing these factors is vital for improve the performances of electro-mechanical systems. This paper deals with the study of vibro-acoustic behavior concerning the drivetrain components using system modeling and Finite Element calculations. A generic simulation methodology within system modeling is proposed enabling the vibro-acoustic simulation of electro-mechanical drivetrains. Excitations for these systems mostly arise from the electric motor and mechanical gears. The paper initially depicts the system model for gear whining considering the associated nonlinearities of the mesh. The results obtained from the gear mesh submodel, together with the excitations resulting from the motor, aid in the comprehension of the forces at the bearings and of the vibrations at the housings.

This paper presents a computationally inexpensive optimization algorithm to jointly compute the fuel-optimal state and input trajectories for the energy management of a hybrid electric vehicle (HEV) on a known driving mission. Specifically, we first introduce a model of the HEV that we leverage to formulate the fuel-optimal control problem as a mixed-integer convex program. Second, we use Pontryagin’s minimum principle and non-smooth convex analysis to derive the fuel-optimal control policy for the power split, the engine on/off decision, and the gear selection. Third, we combine the optimal control policy with single shooting and a bisection method to compute the optimal strategy for reaching a predefined terminal state of charge in the absence of path constraints. Fourth, we introduce a multi-point boundary value approach to deal with path constraints, thus obtaining the optimal control strategies for a complete driving cycle.

Large Eddy Simulations (LES) and tracer-based Laser-Induced Fluorescence (LIF) measurements were performed to study the dynamics of fuel wall-films on the piston top of an optically accessible, four-valve pent-roof GDI research engine for a total of eight operating conditions. Starting from a reference point, the systematic variations include changes in engine speed (600; 1,200 and 2,000 RPM) and load (1000 and 500 mbar intake pressure); concerning the fuel path the Start Of Injection (SOI=360°, 390° and 420° CA after gas exchange TDC) as well as the injection pressure (10, 20 and 35 MPa) were varied. For each condition, 40 experimental images were acquired phase-locked at 10° CA intervals after SOI, showing the wall-film dynamics in terms of spatial extent, thickness and temperature.

Safety-critical embedded software has to satisfy stringent quality requirements. One such requirement, imposed by all contemporary safety standards, is that no critical run-time errors must occur. Runtime errors can be caused by undefined or unspecified behavior of the programming language; examples are buffer overflows or data races. They may cause erroneous or erratic behavior, induce system failures, and constitute security vulnerabilities. A sound static analyzer reports all such defects in the code, or proves their absence. Sound static program analysis is a verification technique recommended by ISO/FDIS 26262 for software unit verification and for the verification of software integration. In this article we propose an analysis methodology that has been implemented with the static analyzer Astrée. It supports quick turn-around times and gives highly precise whole-program results.

Large Eddy Simulation (LES) of premixed turbulent combustion in a confined cylinder setup at engine relevant conditions has been carried out for three different initial turbulence intensities, mimicking different flame propagation regimes. Direct Numerical Simulation (DNS) of the setup under investigation provides the reference data to be compared against. The DNS fields have been filtered on the LES grid and are used as initial conditions for the LES at onset of combustion, guaranteeing a direct comparability of the single realizations between the modeled and reference data. Two different combustion models, the G-Equation and CMC-premixed (Conditional Moment Closure) are compared with respect to their predictive capabilities as well as their usability and computational cost. While the G-Equation is a widely adopted approach for industrial applications and usually relies on a tunable turbulent flame speed closure, the novel LES-CMC comes as a tuning parameter free model.

In the present work numerical simulations were carried out investigating the effect of fuel type, nozzle-geometry variations and back-pressure changes on high-pressure gas injections under application-relevant conditions. Methane, hydrogen and nitrogen with a total pressure of 500 bar served as high-pressure fuels and were injected into air at rest at 200 bar and 100 bar. Different nozzle shapes were simulated and the analysis of the results lead to a recommendation for the most advantageous geometry regarding jet penetration, volumetric growth, mixing enhancement and discharge coefficient. Additionally an artificial inlet boundary conditions was tested for the use with real-gas thermodynamics and was shown to be capable of reducing the simulation time significantly.

Most of the phenomena that occur during the high pressure cycle of a spark ignition engine are highly influenced by the gas temperature, turbulence intensity and turbulence length scale inside the cylinder. For a pre chamber gas engine, the small volume and the high surface-to-volume ratio of the pre chamber increases the relative significance of the gas-to-wall heat losses, the early flame kernel development and the wall induced quenching; all of these phenomena are associated up to a certain extent with the turbulence and temperature field inside the pre chamber. While three-dimensional (3D) computational fluid dynamics (CFD) simulations can capture complex phenomena inside the pre chamber with high accuracy, they have high computational cost. Quasi dimensional models, on the contrary, provide a computationally inexpensive alternative for simulating multiple operating conditions as well as different geometries.

The interaction of turbulent premixed methane combustion with the surrounding flow field can be studied using optically accessible test rigs such as a rapid compression expansion machine (RCEM). The high flexibility offered by such a test rig allows its operation at various thermochemical conditions at ignition. However, limitations inherent to such test rigs due to the absence of an intake stroke do not allow turbulence production as found in IC-engines. Hence, means to introduce turbulence need to be implemented and the relevant turbulence quantities have to be identified in order to enable comparability with engine relevant conditions. A dedicated high-pressure direct injection of air at the beginning of the compression phase is considered as a measure to generate adjustable turbulence intensities at spark timing and during the early flame propagation.

Engines with reduced emissions and improved efficiency are of high interest for road transport. However, achieving these two goals is challenging and various concepts such as PFI/DI/HCCI/PCCI are explored by engine manufacturers. The computational fluid dynamics is becoming an integral part of modern engine development programme because this method provides access to in-cylinder flow and thermo-chemical processes to develop a closer understanding to tailor tumble and swirling motions to construct green engines. The combustion modelling, its accuracy and robustness play a vital role in this. Out of many modelling methods proposed in the past flamelet based methods are quite attractive for SI engine application. In this study, FlaRe (Flamelets revised for physical consistencies) approach is used to simulate premixed combustion inside a gasoline PFI single-cylinder, four-stroke SI engine. This approach includes a parameter representing the effects of flame curvature on the burning rate.

Modern Diesel engines have become ever more complex systems with many degrees of freedom. Simultaneously, with increasing computational power, simulations of engines have become more popular, and can be used to find the optimum set up of engine operation parameters which result in the desired point in the emission-efficiency trade off. With increasing number of engine operation parameter combinations, the number of calculations increase exponentially. Therefore, adequate models for combustion and emissions with limited calculation costs are required. For obvious reasons, the accuracy of the ignition timing is a key point for the following combustion and emission model quality. Furthermore, the combination of mixing and chemical processes during the ignition delay is very challenging to model in a fast way for a wide range of operation conditions.

Compressed Natural Gas (CNG) is a promising alternative fuel for internal combustion engines as its combustion is fuel-efficient and lean in carbon dioxide compared to gasoline. The high octane number of methane gives rise to significant increase of the thermodynamic efficiency due to higher possible compression ratios. In order to use this potential, new stratified mixture formation concepts for CNG are investigated by means of numerical fluid simulations. For decades RANS methods have been the industry standard to model three-dimensional flows. Indeed, there are well-known deficiencies of the widely used eddy viscosity turbulence models based on the applied Boussinesq hypothesis. Reynolds stress turbulence models as well as scale resolving simulation approaches can be appealing alternative choices since they offer higher accuracy. However, due to their large computing effort, they are still mostly impractical for the daily use in industrial product development processes.

As automobiles become increasingly smarter, the need to understand within the automotive software the physical behavior of its parts is growing as well. The laws of physics governing such behavior are mostly formulated as differential equations, which today are usually created or obtained from various modeling tools. For solving them, the tools offer several solvers to satisfy the requirements of different problems. E.g. simple and fast explicit low order solvers for non-stiff problems and more complex implicit solvers for stiff problems. Though the modeling and code generation features as available in such tools are desirable for embedded automotive software, they cannot be used directly due to special restrictions with respect to hard realtime constraints. One such restriction is the organization of automotive software in components complying with the AUTOSAR standard which is not widely supported by the modeling tools.

The Side View Assist is the World’s first rider assistance system for two-wheelers. This is a Blind Spot Warning system, which uses four ultrasonic sensors to monitor the surrounding of the rider. Whenever there is a vehicle (i.e. a car, truck, or another motorbike) in the rider’s blind spot, the technology warns the rider with an optical signal close to the mirror. This will allow the rider to avoid a collision when changing lanes. In the current vehicle application, Side View Assist is active at speeds ranging from 25 to 80 kilometers per hour and supports riders whenever the difference in relative speed to other road users is small. The system helps to improve safety especially in cities, where heavy traffic makes it necessary to change lanes more often. Originally such systems have been developed for cars and different system solutions for cars have been in serial production for several years. The challenge was to adapt these systems so they would work for two-wheelers as well.