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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.

The Composite Lightweight Automotive Suspension System is a composite rear suspension knuckle/tieblade consisting of UD prepreg (epoxy resin), SMC (vinylester resin) carbon fibre and a steel insert to reduce the weight of the component by 35% and reduce Co2. The compression moulding manufacturing process and CAE optimisation are unique and ground-breaking for this product and are designed to allow high volume manufacture of approx. 30,000 vehicles per year. The manufacturing techniques employed allow for multi-material construction within a five minute cycle time to make the process viable for volume manufacture. The complexities of the design lie in the areas of manufacturing, CAE prediction and highly specialised design methods. It is a well-known fact that the performance of a composite part is primarily determined by the way it is manufactured.

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.

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.

This paper presents the application to full vehicle finite element simulation of a steady state rolling tire/wheel/cavity finite element model developed in previous work and validated at the subsystem level. Its originality consists in presenting validation results not only for a wheel on a test bench, but for a full vehicle on the road. The excitation is based on measured road data. Two methods are considered: enforced displacement on the patch centerline and enforced displacement on a 2D patch mesh. Finally the importance of taking the rotation of the tire into account is highlighted. Numerical results and test track measurements are compared in the 20-300 Hz frequency range showing good agreement for wheel hub vibration as well as for acoustic pressure at the occupant’s ears.

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.

This paper makes a contribution toward a more efficient chassis durability process for the development of passenger cars, in which the simulation of relevant load data is a time-consuming part. This is especially due to the full vehicle model complexity which is usually determined by the demands of rough road simulations. However, for the load calculation on a racetrack, time saving model approaches that are more simplified might be sufficient. Our investigation comprises two levels of vehicle model complexity: one with all chassis parts modeled in a multibody system environment and one characteristic curve based model in an internal simulation environment. Both approaches consider an original chassis control system as a Software-in-the-Loop model. By the evaluation of real-world experiments the main influence factors in terms of durability are demonstrated. With the help of those highly sensitive durability criteria the measurement and simulation results are then compared.

This paper describes the prediction process of wheel forces and moments via indirect transfer path analysis, followed by an analysis of the influence of wheel variants and suspension modifications. It proposes a method to calculate transmission of noise to the vehicle interior where wheel forces and especially moments were taken into account. The calculation is based on an indirect transfer path analysis with geometrical modifications of the frequency response functions. To generate high quality broadband results, this paper also points out some of the main clearance cutting criteria. The method has been successfully implemented to show the influence of wheel tire combinations as well as the influence of suspension modifications. Case studies have been performed and will be presented in this paper. Operational noise and vibration measurements have been carried out on Daimler NVH test tracks. The frequency response functions were estimated in an acoustic laboratory.

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.

In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).

This paper presents the application of a proposed fuzzy inference system as part of a stability control design scheme implemented with active steering actuator sets. The fuzzy inference system is used to detect the level of overseer/understeer at the high level and a speed-adaptive activation module determines whether an active front steering, active rear steering, or active 4 wheel steering is suited to improve vehicle handling stability. The resulting model-free system is capable of minimizing the amount of model calibration during the vehicle stability control development process as well as improving vehicle performance and stability over a wide range of vehicle and road conditions. A simulation study will be presented that evaluates the proposed scheme and compares the effectiveness of active front steer (AFS) and active rear steer (ARS) in enhancing the vehicle performance. Both time and frequency domain results are presented.

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.

A new turbocharged 60° 2.7L 4V-V6 gasoline engine has been developed by Ford Motor Company for both pickup trucks and car applications. This engine was code named “Nano” due to its compact size; it features a 4-valves DOHC valvetrain, a CGI cylinder block, an Aluminum ladder, an integrated exhaust manifold and twin turbochargers. The goal of this engine is to deliver 120HP/L, ULEV70 emission, fuel efficiency improvements and leadership level NVH. This paper describes the upfront design and optimization process used for the NVH development of this engine. It showcases the use of analytical tools used to define the critical design features and discusses the NVH performance relative to competitive benchmarks.

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.

Drivelines used in modern pickup trucks commonly employ universal joints. This type of joint is responsible for second driveshaft order vibrations in the vehicle. Large displacements of the joint connecting the driveline and the rear axle have a detrimental effect on vehicle NVH. As leaf springs are critical energy absorbing elements that connect to the powertrain, they are used to restrain large axle windup angles. One of the most common types of leaf springs in use today is the multi-stage parabolic leaf spring. A simple SAE 3-link approximation is adequate for preliminary studies but it has been found to be inadequate to study axle windup. A vast body of literature exists on modeling leaf springs using nonlinear FEA and multibody simulations. However, these methods require significant amount of component level detail and measured data. As such, these techniques are not applicable for quick sensitivity studies at design conception stage.