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The reliability of electronic components is of increasing importance for further progress towards automated driving. Thermal aging processes such as electromigration is one factor that can negatively affect the reliability of electronics. The resulting failures depend on the thermal load of the components within the vehicle lifetime - called temperature collective - which is described by the temperature frequency distribution of the components. At present, endurance testing data are used to examine the temperature collective for electronic components in the late development stage. The use of numerical simulation tools within Vehicle Thermal Management (VTM) enables lifetime thermal prediction in the early development stage, but also represents challenges for the current VTM processes [1, 2]. Due to the changing focus from the underhood to numerous electronic compartments in vehicles, the number of simulation models has steadily increased.

Future CO2 emission legislation requires the internal combustion engine to become more efficient than ever. Of great importance is the boosting system enabling down-sizing and down-speeding. However, the thermodynamic coupling of a reciprocating internal combustion engine and a turbocharger poses a great challenge to the turbine as pulsating admission conditions are imposed onto the turbocharger turbine. This paper presents a novel approach to a turbocharger turbine development process and outlines this process using the example of an asymmetric twin scroll turbocharger applied to a heavy duty truck engine application. In a first step, relevant operating points are defined taking into account fuel consumption on reference routes for the target application. These operation points are transferred into transient boundary conditions imposed on the turbine.

The overall efficiency of hybrid electric vehicles largely depends on the design and application of its energy management system (EMS). Despite the load coordination when operating the system in a hybrid mode, the EMS accounts for state changes between the different driving modes. Whether a transition between pure electric driving and internal combustion engine (ICE) powered driving is beneficial depends, among others, on the respective operation point, the route ahead as well as on the energetic expense for the engine start itself. The latter results from a complex interaction of the powertrain components and has a tremendous impact on the efficiency and quality of EMSs. Optimization based methods such as dynamic programming serve as benchmark for the design process of rule based control strategies. In case no energetic expenses are assigned to a state change, the resulting EMS suffers from being sub-optimal regarding the fuel consumption.

A raise of efficiency is the strongest selling point concerning the total cost of ownership (TCO), especially for commercial vehicles (CV). Accompanied by legislations, with contradictive development demands, satisfying solutions have to be found. The analysis of energy losses in modern engines shows three influencing parameters. Wall heat transfer (WHT) losses are awarded with the highest optimization potential. Critical for the occurrence of these losses is the WHT, which can be described by representing coefficients. To reduce WHT accompanying losses a decrease of energy transfer between combustion gas and combustion chamber wall is necessary. A measurement of heat fluxes is necessary to determine the WHT relations of the combustion chamber in an engine. As this has not been done for a Heavy-Duty (HD) engine, with peak pressures up to 250 bar, an increased in-cylinder turbulence and high exhaust gas recirculation (EGR)-rates before, it is presented in the following.

A wide variety of applications such as driver assistant and energy management systems are researched and developed in virtual test environments. The safe testing of the applications in early stages is based on parameterizable and reproducible simulations of different driving scenarios. One possibility is modeling the microscopic driving behavior to simulate the longitudinal vehicle dynamics of individual vehicles. The currently used driver models are characterized by a conflict regarding comprehensibility, accuracy and calibration effort. Due to the importance for further analyses this conflict of interests is addressed by the presentation of a new microscopic driver model in this paper. The proposed driver model stores measured driving behaviors with its statistical distributions in maps. Thereby, the driving task is divided into free flow, braking in front of stops and following vehicles ahead. This makes it possible to display the driving behavior in its entirety.

The TOP TIERTM Diesel fuel standard was first established in 2017 to promote better fuel quality in marketplace to address the needs of diesel engines. It provides an automotive recommended fuel specification to be used in tandem with regional diesel fuel specifications or regulations. This fuel standard was developed by TOP TIERTM Diesel Original Equipment Manufacturer (OEM) sponsors made up of representatives of diesel auto and engine manufacturers. This performance specification developed after two years of discussions with various stakeholders such as individual OEMs, members of Truck and Engine Manufacturers Association (EMA), fuel additive companies, as well as fuel producers and marketers. This paper reviews the major aspects of the development of the TOP TIERTM Diesel program including implementation and market adoption challenges.

Since 2013 the new Daimler Aeroacoustic Wind Tunnel (AAWT) is in operation at the Mercedes-Benz Technology Center in Sindelfingen, Germany. This construction was the second stage of a wind tunnel center project, which was launched in 2007 and started with the climatic wind tunnels including workshop and office areas. The AAWT features a test facility for full-scale cars and vans with a nozzle exit area of 28 m2, a five-belt system, and underfloor balance to measure forces with best possible road simulation. With a remarkable low background noise level of the wind tunnel, vehicle acoustics can be investigated under excellent conditions using high-performance measurement systems. An overview is given about the building and the design features of the wind tunnel layout. The aerodynamic and aeroacoustic properties are summarized. During the first years of operation, further improvements regarding the wind tunnel background noise and vehicle handling were made.

In the proposed work the transient thermal modeling of a vehicle cabin has been performed. Therefore, a reduced model has been developed based on a one-node discretization of the cabin air. The conduction in the solid parts is accounted for by a one-dimensional heat transfer approach, the radiation exchange between the surfaces is based on view factors adopted from a 3D reference and the convective heat transfer from the cabin surfaces to the cabin air is conducted with the help of heat transfer coefficients calculated in a 3D reference simulation. The cabin surface is discretized by planar wall elements, including the outer shell of the cabin and inner elements such as seats. Each wall element is composed of several homogeneous material layers with individual thicknesses. Investigations have been conducted on the temporal and spatial resolution of the layer structure of these wall elements, for the 3D model as well as for the reduced one.

Todays tuning of hydraulic vehicle shock absorbers is mainly an empirical iterative process performed in time-consuming and expensive ride tests, whereas the majority of damper simulation models used for investigating vehicle ride behavior is based on an abstract parameterization. For the manufacturing of automotive dampers, however, the valve code is essential. Minor changes in the valve code describing the shim stack in the hydraulic valves may have a noticeable impact on the damper characteristics, while the physical effects are still not sufficiently understood. Therefore, the paper presents a detailed physics-based structural model to investigate the pressure-deflection behavior of shim stacks and the influence of specific discs in the stack. The model includes a variety of effects like friction and preload, and is capable to predict the damper characteristics.

Downsizing and direct injection in modern DISI engines can lead to fuel impinging on the cylinder walls. The interaction of liquid fuel and engine oil due to fuel impinging on the cylinder wall causes problems in both lubrication and combustion. To analyze this issue with temporal and spatial resolution, we developed a laser-induced fluorescence (LIF) system for simultaneous kHz-rate imaging of fuel and oil films on the cylinder wall. Engine oil was doped with traces of the laser dye pyrromethene 567, which fluoresces red after excitation by 532 nm laser radiation. Simultaneously, the liquid fuel was visualized by UV fluorescence of an aromatic “tracer” in a non-fluorescent surrogate fuel excited at 266 nm. Two combinations of fuel and tracer were investigated, iso-octane and toluene as well as a multi-component surrogate and anisole. The fluorescence from oil and fuel was spectrally separated and detected by two cameras.

Due to the continuous increasing highway transport and the decreasing investments into infrastructure a better usage of the installed infrastructure is indispensable. Therefore the operation and interoperation of assistance and telematics systems become more and more necessary. Regarding these facts Highway Pilot was developed at Daimler Trucks. The Highway Pilot System moves the truck highly automated and independent from other road users within the allowed speed range and the required security distance. Daimler Trucks owns diverse permissions in Germany and the USA for testing these technologies on public roads. Next generation is the Highway Pilot Connect System that connects three highly automated driving trucks. The connection is established via Vehicle-to-Vehicle communication (V2V).

In order to offer a wide range of driving experiences to their customers, original equipment manufacturers implement different driving programs. The driver is capable of manually switching between these programs which alter drivability parameters in the engine control unit. As a result, acceleration forces and gradients are modified, changing the perceived driving experience. Nowadays, drivability is calibrated iteratively through road testing. Hence, the resulting set of parameters incorporated within the engine control unit is strongly dependent on the individual sentiments and decisions of the test engineers. It is shown, that implementing a set of objective criteria offers a way to reduce the influences of personal preferences and sentiments in the drivability calibration process. In combination with the expertise of the test engineers, the desired vehicle behavior can be formalized into a transient set point sequence to give final shape to the acceleration behavior.

The reduction of fuel consumption as well as the rising demands of customers regarding a vehicle’s driving dynamic and the legislator’s continually rising demands are a current issue in vehicle development. Hybrid vehicles offer a possibility to rise to this challenge. Realistic driving cycles are of utmost importance for the calibration of a hybrid vehicle’s operational strategy. Deriving replacement speed cycles from extensive customer data sets seems to be an approach for solving these problems. The contribution at hand describes the derivation of replacement cycles by using stochastic models, probabilistic (weighted) drawings and a combinatorial optimisation. The novelty value is that the characteristic influences of all drivers are being considered in the generation due to the stochastic modelling.

In order to achieve high customer satisfaction and to avoid high warranty costs caused by component failures of the power-train of hybrid electric vehicles (HEV), car manufacturers have to optimize the dimensioning of these elements. Hence, it is obligatory for them to gain knowledge about the different types of vehicle usage being predominant all over the world. Therefore, in this paper we present a Data Mining system that employs a Random Forest (RF) based dissimilarity measure in the dimensionality reduction technique t-Distributed Stochastic Neighbor Embedding (t-SNE) to automatically identify and visualize different types of vehicle usage by applying these methods to aggregated logged on-board data, i.e., load spectrum data. This kind of data is calculated and recorded directly on the control units of the vehicles and consists of aggregated numerical data, like the histogram of the velocity signal or the traveled distance of a vehicle.

Securing the desired strength and durability characteristics of suspension components is one of the most important topics in the development of commercial vehicles because these components undergo multiaxial variable amplitude loading. Leaf springs are essential for the suspension systems of trucks and they are considered as security relevant components in the product development phase. In order to guide the engineers in the design and testing department, a simulation method is developed as explained by Bakir et al. in a recently published SAE paper [1]. The main aim of the present study is to illustrate the validation of this simulation method for the durability of leaf springs based on the results from testing and measurements. In order to verify this CAE Method, the calculated stresses on the leaf springs are compared with the results of strain gage measurements and the fatigue failures of leaf springs are correlated with the calculated damage values.

The driving comfort is an important factor for buying decisions. For the interior noise of battery electric vehicles (BEV) high frequency tonal orders are characteristic. They can for example be caused by the gearbox or the electric drive and strongly influence the perception and rating of the interior noise by the customer. In this contribution methods for measuring, analyzing and predicting the excitation by the dynamic torque of the electric drive are presented. The dynamic torque of the electric drive up to 3.5 kHz is measured on a component test bench with the help of high frequency, high precision torque transducer. The analysis of the results for the order of interest shows a good correlation with the acoustic measurements inside the corresponding vehicle. In addition an experimental and numerical modal analysis of the rotor of the electric drive are performed.

In an automotive suspension, the shock absorber plays a significant role to enable the vehicle performances, especially in ride, handling and Noise-Vibration-Harshness (NVH). Understanding its physical characteristics is of great importance, as it has a main influence on the overall vehicle performance. Within this research project simulation models for different passive monotube shock absorber systems have been created in a 1-D system simulation software. The simulation models are designed and parameterized physically. To validate the simulation models measurements on different hydropulse-shaker with specially designed control signals to investigate the response during high frequency excitation, have been done. A detailed discussion of the several models and results of a simulation to measurement comparison is given. After detailed investigation the shock absorber simulation models are now adaptable to the multi body simulation.

In this paper a rule-based energy management for parallel hybrid electric vehicles (HEVs) is presented, which is based on the principles describing the optimal control behavior. Therefore we first show the general relations that can be used to describe the optimal limit of electric driving as well as the optimal torque split among the two propulsion systems. Subsequently these relations are employed to derive maps, which represent the optimal behavior depending on several input parameters. These maps are then used as inputs for the rules in the proposed energy management. This not only makes it possible to automatically calibrate the rule-based controller but also gives the optimal control in every driving situation. Given it is not fuel-efficient to turn the internal combustion engine (ICE) on or off for short intervals, it is further shown how this approach allows to adjust the established limit for electric driving by additional rules.

In the next 20 years the share of small electric vehicles (SEVs) will increase especially in urban areas. SEVs show distinctive design differences compared to traditional vehicles. Thus the consequences of impacts of SEVs with vulnerable road users (VRUs) and other vehicles will be different from traditional collisions. No assessment concerning vehicle safety is defined for vehicles within European L7e category currently. Focus of the elaborated methodology is to define appropriate test scenarios for this vehicle category to be used within a virtual tool chain. A virtual tool chain has to be defined for the realization of a guideline of virtual certification. The derivation and development of new test conditions for SEVs are described and are the main focus of this work. As key methodology a prospective methodical analysis under consideration of future aspects like pre-crash safety systems is applied.

Electric cars are getting popular more and more and the expectations of the customers are very challenging. Concerning comfort, the situation is clear: customers want an electric car to be quiet and without any annoying noise from the powertrain. To develop an electric powertrain with a minimum noise level and minimized whining it is necessary to have an accurate CAE-simulation and precise criteria to assess whining noise. Based on the experience with electric powertrains in research cars the CAE-modelling was improved and a new ‘whining intensity factor’ was acquired for the development of Daimler's electric cars. The results are a very low noise level and a minimized whining noise, nearly not noticeable giving a comfortable sound to the customers of the smart electric drive and the B-Class Electric Drive.