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With the automotive industry's increasing focus on electromobility and the growing share of electric cars, new challenges are arising for the development of electric motors. The requirements for torque and power of traction motors are constantly growing, while installation space, costs and weight are increasingly becoming limiting factors. Moreover, there is an inherent conflict in the design between power density and efficiency of an electric motor. Thus, a main focus in today's development lies on space-saving and yet effective and innovative cooling systems. This paper presents an approach for a multi-physical optimization that combines the domains of electromagnetics and thermodynamics. Based on a reference machine, this simulative study examins a total of nine different stator cooling concepts varying the cooling duct positions and end-winding cooling concepts.

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.

Salt Spray Test is being used since 1930’s to accelerate the corrosion testing of materials and to understand the longevity of applied coating. The sample in this kind of test is exposed to a salt mist in a controlled environment and its corrosion resistance is evaluated by measuring the corrosion rate. The Wet-Dry cycle in Salt Spray Test has the ability to simulate the drying and wetting which occurs in real driving scenario, leading to formation of a film of corrosion products which is useful in analyzing the kinetics of electrochemical reaction. Despite the advancement in severity of these tests to understand the atmospheric corrosion phenomena, they still consume time and resources. Secondly, sometimes these kind of tests do not consider into account the effect of Temperature, Humidity and other chemicals in play. Thus, numerical simulation plays a pivotal role in digitalizing the corrosion analysis to a certain extent.

The automotive world is progressing fast towards autonomous vehicles making sensors one of the critical components. There is a requirement for constant exchange of information between the vehicle and its surrounding environment, which is assisted by sensors such as Camera, LiDAR, and RADAR. However, exposure to harsh environmental conditions such as rain, dirt, snow, and bird droppings can hamper the functioning of the sensors and in turn interrupt accurate vehicle maneuvers. Sensor-cleaning mechanisms are required to be tested under various weather conditions and vehicle operating situations. Besides wind tunnel tests, digitalizing this whole process becomes important to take decision on design changes in early vehicle development stage. This work presents a digital methodology to test the LiDAR cleaning system in the advent of mud clearing at different vehicle speeds. The cleaning mechanism consists of a telescopic nozzle placed above the LiDAR translating back and forth.

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.

More and more applications (apps) are entering vehicles. Customers would like to have in-car apps in their infotainment system, which they already use regularly on their smartphones. Other apps with new functionalities also inspire vehicle customers, but only as long as the customer can utilize them. To ensure customer satisfaction, it is important that these apps work and that failures are found and corrected as quickly as possible. Therefore, in-car apps also implicate requirements for future vehicle diagnostics. This is because current vehicle diagnostic methods are not designed for handling dynamic software failures of apps. Consequently, new diagnostic methods are needed to support the diagnosis of in-car apps. Log data are a central building block in software systems for system health management or troubleshooting. However, there are different types of log data and log environment setups depending on the underlying system or software platform.

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.

For electric vehicles the ability for regenerative braking reduces the use of friction brakes. Particularly on the rear axle of vehicles with reduced dynamic requirements such as urban vehicles, this can offer a potential for downsizing or, in extreme cases, even the elimination of the friction brakes on the rear axle. Due to the fact that the rear axle service brakes also represent the typical parking brake location in SoA (State-of-Art) vehicles, a rigorous rethinking of the parking brake concept is necessary to incorporate safe vehicle standstill management for such novel brake system topology. This research study introduces a novel parking brake design that covers SoA but also legal requirements while retaining potentials associated with the elimination of the rear service brakes such as cost and packaging.

The automotive industry is facing new emission regulations, changing customer preferences and technology disruptions. All have in common, that external aerodynamics plays a crucial role to achieve emission limits, reduce fuel consumption and extend electric driving range. Probably the most challenging components in terms of numerical aerodynamic drag prediction are the wheels. Their contribution to the overall pressure distribution is significant, and the flow topology around the wheels is extremely complicated. Furthermore, deltas between different rim designs can be very small, normally in the range of only a few drag counts. Therefore, highly accurate numerical methods are needed to predict rim rankings and deltas. This paper presents experimental results of four different production rim designs, mounted to a modified production car. An accurate representation of the loaded, deformed tire geometry is used in all calculations for comparable conditions between wind tunnel and CFD.

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.

The electric range of plug-in hybrids as well as the installed electric power has steadily increased. With an electric power share of more than half of the overall system power, concepts of hybrid electric vehicles with at least two electric machines come into focus. Especially the concept of adding an individual electric axle to a state-of-the-art parallel hybrid, such as a P2-hybrid, is promising. However, the system complexity of a so-called P24-hybird increases significantly because the number of possible system states rises. This leads to an increased development and calibration effort for an online energy management. Especially a transfer from an optimized operating strategy to a rule-based energy management is challenging. Thus, a development framework for the calibration of an online energy management system (EMS) which is as fuel efficient as possible is needed.

The current automotive market is dynamic, leading to complex functionalities being incorporated into the control software of various components like engine, gearbox, battery, E-motor etc. This results in utilization of virtual environments for software testing to reduce the development time. The virtual platforms under the category X-in-the-Loop (XiL) e.g. Software-in-the-Loop (SiL) and Hardware-in-the-Loop (HiL) use simulated models to achieve a desired test goal. These component models must be rigorously validated to ensure the quality of XiL-Testing. Thus, it is essential to define a model release process that maintains model quality irrespective of the modeling approach used and the user. One of the challenges is to choose an appropriate Error Metric (EM) that sets criteria for model release. This paper proposes a combination of Theil’s Inequality Coefficient (TIC) and Unscaled Mean Bounded Relative Absolute Error (UMBRAE) as the EM.

In order to adhere with future automotive legislation and incentives, the electric range of plug-in hybrids has steadily increased. At the same time, the installed electric power has risen as well leading to future hybrid vehicles with an electric power share of more than half of overall system power and hybrid configurations with at least two electrical machines come into focus. The concept of adding a separate electrical axle to a P2-hybrid - a so called P24-hybrid, is of special interest. The system complexity of a such a system increases significantly as the number of possible system states increases. Thus, this paper analyzes the efficiencies and benefits of the different system states within the fuel-optimal operating strategy derived by global optimization. By varying the electrical power distribution between the two axles, the impact on fuel efficiency and the changes within the operating strategy are investigated.

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.

Sunroof buffeting is examined experimentally and numerically in this paper. Despite the fact that some consider the simulation process for sunroof buffeting to be mature, there remain substantial uncertainties even in recently published methodologies. Capturing the frequencies and especially the sound pressure levels correctly is essential if CFD simulations are intended to be used during early stages of a car development process. Numerous experimental results of sunroof buffeting and the interior low-frequency characteristics of a 2013 Mercedes-Benz S-Class have been used to develop a simplified car model: a full-size S-Class model with slightly simplified geometries in the interior as well as at the exterior. To avoid the effects of numerous different materials in the interior, it is solely made from polyurethane and aluminum and built to maximize its structural rigidity and air-tightness.

In this paper, the differences between a production car of the 2018 A-class and an early stage vehicle model with a mostly similar outer skin are examined experimentally and numerically. The aerodynamic development of vehicles at Mercedes-Benz is divided into several phases. When comparing force coefficients differences can be observed between these distinct hardware stages as well as when comparing steady state simulations to wind tunnel measurements. In early phases when prototype vehicles are not yet available, so-called aero foam models are used. These are well-defined full-sized vehicle models, as the outer skin is milled from Polyurethane. Important aerodynamic characteristics such as a motor compartment with a cooling module, deflecting axles with rotatable wheels and underbody covers are represented.

As the late combustion phase in SI engines is of high importance for a further reduction of fuel consumption and especially emissions, the impacts of unburnt mass, located in a small volume with a relatively large surface near the wall and in the top land volume, is of high relevance throughout the range of operation. To investigate and quantify the respective interactions, a state of the art Mercedes-Benz single cylinder research SI-engine was equipped with extensive measurement technology. To detect the axial and radial temperature distribution, several surface thermocouples were applied in two layers around the top land volume. As an additional reference, multiple surface thermocouples in the cylinder head complement the highly dynamic temperature measurements in the boundary zones of the combustion chamber.

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.