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Autonomous Driving is being utilized in various settings, including indoor areas such as industrial halls. Additionally, LIDAR sensors are currently popular due to their superior spatial resolution and accuracy compared to RADAR, as well as their robustness to varying lighting conditions compared to cameras. They enable precise and real-time perception of the surrounding environment. Several datasets for on-road scenarios such as KITTI or Waymo are publicly available. However, there is a notable lack of open-source datasets specifically designed for industrial hall scenarios, particularly for 3D LIDAR data. Furthermore, for industrial areas where vehicle platforms with omnidirectional drive are often used, 360° FOV LIDAR sensors are necessary to monitor all critical objects. Although high-resolution sensors would be optimal, mechanical LIDAR sensors with 360° FOV exhibit a significant price increase with increasing resolution.

Given the rapid advancement of connected and automated transportation, its applications have significantly increased. They are being studied worldwide to shape the future of mobility. Key promises are a more comfortable, efficient and socially adapted kind of mobility. As part of the EU Horizon2020 project SHared automation Operating models for Worldwide adoption (SHOW), the Karlsruhe Test Site in the Test Area Autonomous Driving Baden-Württemberg (TAF-BW) addresses aspects of scalability to overcome challenges, which have so far hindered market penetration of this future-oriented kind of mobility. The explored services, including passenger and cargo transport, are closely linked to the daily travel requirements of road users, particularly in peri-urban areas, to cover the last mile of their journeys, connecting them to public transport.

The functional extension of vibration reduction in continuous slip operation in modern wet-running clutch systems under dynamic excitation is being investigated by the authors. Therefore, a mixed virtual-physical validation environment has been developed using the IPEK X-in-the-Loop Framework and will be presented as part of this contribution. Thus, the validation environment enables the consideration of interactions with the residual systems, especially the residual drive train. In this contribution, the validation environment is used to investigate whether and how an attribute variation in the subsystem, respectively the tribological system, can provide improved vibration reduction without increased power dissipation due to damping but other reducing mechanisms favored. The results show significant differences in vibration reduction behavior whereas the power losses are almost the same between the investigated tribological system.

The requirements for modern drivetrains are increasing across all industries. Even mobile working machines such as agricultural and construction machinery are subject to increasingly higher demands in terms of efficiency and CO2 emissions. To verify these requirements and drive further development, it is necessary for testing processes to comprehensively evaluate the machine and its operational processes. For this purpose, the MOBiL testing approach was developed at the Institute of Mobile Machines. This approach incorporates parallel drivetrains, information flow and the environment of the driving and working task. To implement this approach in a complete vehicle testbench, a framework was developed that enables fully individual driving and working tasks of a mobile working machine to be replicated on a test bench. The basis for this framework is the Robot Operating System (ROS), which runs various nodes.

The increasing adoption of battery electric vehicles (BEVs), driven by the EU's target of no internal combustion engine vehicles from 2035 onwards, is driving significant changes in the automotive industry. However, the high degree of electrification and the unique low-speed acceleration behavior of BEVs therefore lead to new challenges. Measuring the drivetrain power and efficiency in a reproducible way and obtaining meaningful results is one of the challenges. To address this challenge, a novel test method is developed that offers a simple and preferably modification-free approach to drivetrain power and efficiency measurements for BEVs, allowing for efficient and reproducible testing. Different paths for determining the drivetrain power with varied measurement efforts are presented and evaluated. The test method is designed to provide reliable and accurate results for BEVs.

A gray-box optimization procedure based on evolutionary algorithms for the initial design of a suspension concept for four wheel independently driven and steered vehicles is developed. With the presented optimization method, the energy consumption together with state of the art knowledge about the parametrization and design of vehicle suspension systems leads to an optimization setup closely to real world requirements while the vehicle’s topology is exploited. To this, the modelling presented in [1] is considered as a geometric suspension model. Furthermore, to take advantage of the potential of such vehicles, an autonomous closed-loop setup with integrated motion control is utilized. During the optimization, the chassis parameters with the most impact on energy consumption and driving dynamics, namely camber, caster, scrub radius and the steering axis inclination (SAI) depending on a varying caster angle and SAI in relation to the steering angle, will be focused.

The fuel economic and emission performance of an innovative electric hybrid vehicle (HEV), Dualhybrid, with two internal combustion engines (ICEs) under cold start conditions was studied. Sub-models including powertrain, lubrication and cooling system as well as exhaust system were built and integrated into the models of Dualhybrid and two other reference models: Base model and Fullhybrid model. Coupled lubrication and the exhaust systems of the two ICEs are proposed. The effect of the combination of oil heating and electric heating on the fuel consumption of Dualhybrid was investigated. The results show that the coupled lubricating system of Dualhybrid is beneficial to improve the fuel economy in cold start. The method of hybrid heating can provide a sufficient heating power of the cabin in the initial stage of cold start without declining the fuel economic performance significantly.

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.

The emission of formaldehyde and its removal has recently been brought into the focus of exhaust gas catalysis beside reduction off pollutants like hydrocarbons, carbon monoxide and nitrogen oxides. In this study, five commercial Pt-based catalysts were tested on their ability to oxidize formaldehyde under a variety of gas mixtures representing typical conditions of lean burn gas engines. In general, most of the formaldehyde could be removed almost as efficiently as carbon monoxide and much easier than saturated hydrocarbons. The catalysts were aged in different simulated exhaust gas mixtures including varying SO2 concentrations at 500 °C for 100 h to investigate a possible loss of activity due to thermal aging and poisoning. In a sulfur-free simulated exhaust gas very high conversion with no detectable loss of activity due to the aging was observed. Also small amounts of SO2 (1.75 ppm) had only minor effects on formaldehyde conversion.

The ongoing changes in the development of new power trains and the requirements due to driver assistance systems and autonomous driving could be the enabler for completely new brake system configurations. The shift in the brake load collective has to be included in the systems requirements for electric vehicles. Many alternative concepts for hydraulic brake systems, even for decentralized configurations, can be found in the literature. For a decentralized system with all state of the art safety functionalities included, four actuators are necessary. Therefore, the single brake module should be as cost-effective as possible. Previous papers introduced systems which are for example based on plunger-like concepts, which are very expensive and heavy due to the needed gearing and design. In this paper a comparison between a state of the art hydraulic brake system using an electromechanical brake booster, and a completely new decentralized hydraulic brake concept is presented.

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.

A cooperation of several research partners supported by the German Federal Ministry of Research and Education proposes a new active matrix LED light source. A multi pixel flip chip LED array is directly mounted to an active driver IC. A total of 1024 pixel can be individually addressed through a serial data bus. Several of these units are integrated in a prototype headlamp to enable advanced light distribution patterns in an evaluation vehicle.

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.