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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.

Each component of a drive train generates waste heat due to its limited efficiency. This waste heat is usually released to an air flow guided through one or more heat exchangers. So, the realized cooling air volume flow is one important characteristic value during the vehicle development process. This paper presents some of the available techniques for the measurement of cooling air volume flow in the vehicle during the different stages of an aerodynamic development process in model scale and full scale. Additionally, it provides suggestions when comparing these experimental values to CFD results.

This paper presents an autonomous cruise control for battery electric vehicles. The presented approach is based on the usage of predictive route data which is extracted out of a digital map and a wide range radar system in order to capture vehicles in front. By using the predictive route data and the information of the radar system, the autonomous cruise control can control the vehicle's speed over a wide range of driving situations without any driver interaction. The main aim of the presented autonomous cruise control is to optimize the battery electric vehicle's energy consumption. The main idea is to use predictive route data in order to calculate a consumption optimal vehicle speed trajectory by means of online optimization. The benefits of the autonomous cruise control are shown by means of real test drives and measured data evaluation.

In use cars often drive through the wakes of other vehicles. It has long been appreciated that this imposes a fluctuating onset flow which can excite a structural response in vehicle panels, particularly the bonnet. This structure must be designed to be robust to such excitation to guarantee structural integrity and maintain customer expectations of quality. As we move towards autonomous vehicles and exploit platoons for drag reduction, this onset flow condition merits further attention. The work reported here comprises both measurements and simulation capturing the unsteady pressure distribution over the bonnet of an SUV following a similar vehicle at high speed and in relatively close proximity. Measurements were taken during track testing and include 48 static measurement locations distributed over the bonnet where the unsteady static pressures were recorded.

The hybrid power train technology offers various prospects to optimize the engine efficiency in order to minimize the CO₂ emissions of an internal-combustion-engine-powered vehicle. Today different types of hybrid architectures like parallel, serial, power split or through-the-road concepts are commonly known. To achieve lowest fuel consumption the following hybrid electric vehicle drive modes can be used: Start/Stop, pure electric/thermal driving, recuperation of brake energy and the hybrid mode. The high complexity of the interaction between those power sources requires an extensive investigation to determine the optimal configuration of a natural-gas-powered SI engine within a parallel hybrid power train. Therefore, a turbocharged 1.0-liter 3-cylinder CNG engine was analyzed on the test bench. Using an optimized combustion strategy, the engine was operated at stoichiometric and lean air/fuel ratio applying both high- and low-pressure EGR.

Until a few years ago the discussion of reduction of CO₂ emissions was completely out of place in motorsports. Nowadays, also in this field, car manufacturers want to investigate different approaches towards a more responsible and sustainable concept. For this target an interesting and feasible solution is the use of methane as an alternative fuel. At the 2009 edition of the 24-hour endurance race of the Nürburgring the Volkswagen Motorsport GmbH, in addition to vehicles powered by gasoline engines, introduced two vehicles powered by turbocharged CNG engines. The aim was to prove that also an "environment-friendly" concept is able to provide the required efficiency, dynamic and reliability for a successful participation in motorsports. After the success in the 2009 edition the engagement has been continued in 2010; this time exclusively with CNG vehicles.

In this paper the development approach and the results of numerical and experimental investigations on homogeneous charge compression ignition in a free piston engine are presented. The Free Piston Linear Generator (FPLG) is a new type of internal combustion engine designed for the application in a hybrid electric vehicle. The highly integrated system consists of a two-stroke combustion unit, a linear generator, and a mass-variable gas spring. These three subsystems are arranged longitudinally in a double piston configuration. The system oscillates linearly between the combustion chamber and the gas spring, while electrical energy is extracted by the centrally arranged linear generator. The mass-variable gas spring is used as intermediate energy storage between the downstroke and upstroke. Due to this arrangement piston stroke and compression ratio are no longer determined by a mechanical system.

In this paper, a serial/parallel hybrid electric vehicle with a 17 kWh battery and 400 V voltage level is simulated. The vehicle is a C-segment vehicle, which has optimized driving resistances. It also has an external recharge possibility, which enables fully electric driving. The vehicle uses an Otto-engine concept as well as two electric motors. One motor is a permanent magnet synchronous motor and can be used as traction motor or generator, the other one is an induction motor used as main traction motor for the vehicle. The vehicle uses a 2-speed gearbox, where the electric motors are mounted in P2-configuration. To reach optimal results for the fuel consumption, an operating strategy based on the Equivalent Consumption Minimization Strategy (ECMS) is introduced and implemented in the vehicle simulation.

In this work, a novel approach is introduced comprising a combination of unsupervised machine learning (ML) scheme and charging energy management of electric vehicles (EV). The main goal of this implementation is to reduce the load peak of charging EV’s, which are regular users of electric vehicle supply equipment (EVSE) of a certain building and, at the same time, to meet their electric and behavioral demands. The unsupervised ML considers certain features within the charging profiles in addition to the behavioral characteristics of the EV based on its intended use. Moreover, these features are extracted from large sets of history measurement data of the EVSE, which are stored in the data bank. The ML categorizes the EVs within certain clusters having defined specifications.

Within the last years, the number of electric vehicles in Europe is increasing faster than the number of charging stations. Based on this, the reliability of the charging process takes on greater significance. The communication between the electric vehicle (EV) and their charging station is a prerequisite to transfer the charging power. Using a universal charging communication test system allows an observation of the whole charging communication according to ISO 15118 and IEC 61851 standards. It is important to know whether the communication between the EV and the charging station functions accordingly, in order to ensure functionality. Furthermore, tolerances must comply with the standard. In a first step, the basic communication according to IEC 61851 is considered. Preliminary investigations of the pulse width modulation (PWM) signal have shown that some EVs are tolerant of the standards.

In the automotive industry, there is a continued need to improve the development process and handle the increasing complexity of the overall vehicle system. One major step in this process is a comprehensive and complementary approach to both simulation and testing. Knowledge of the overall dynamic vehicle behavior is becoming increasingly important for the development of new control concepts such as integrated vehicle dynamics control aiming to improve handling quality and ride comfort. However, with current well-established test systems, only separated and isolated aspects of vehicle dynamics can be evaluated. To address these challenges and further merge the link between simulation and testing, the Institute of Internal Combustion Engines and Automotive Engineering (IVK), University of Stuttgart is introducing a new Handling Roadway (HRW) Test System in cooperation with The Research Institute of Automotive Engineering and Vehicle Engines Stuttgart (FKFS) and MTS Systems Corporation.

This paper addresses the performance and potential of using electric vehicles in the Gulf Arab states. Based on a survey executed in Salalah, Oman, a representative test driving cycle has been set up. This cycle is the first of its kind for this region, where it is driven with a vehicle provided with special measurement equipment to log important values, e.g. vehicle's speed and position, temperatures and solar irradiance. More than 40 test drives are performed to obtain a representative driver profile. The driving cycle and driver profile are used in a simulation model which is capable of simulating the energy consumption for internal combustion engine or electric motor propulsion systems. The simulation model which contains detailed models for the driver, driving cycle, vehicle components and its dynamics is validated and used to compare the consumed energy for the two different propulsion systems.

Over the past years, the question as to what may be the powertrain of the future has become ever more apparent. Aiming to improve upon a given technology, the internal combustion engine still offers a number of development paths in order to maintain its position in public and private mobility. In this study, an innovative combustion process is investigated with the goal to further approximate the ideal Otto cycle. Thus far, similar approaches such as Homogeneous Charge Compression Ignition (HCCI) shared the same objective yet were unable to be operated under high load conditions. Highly increased control efforts and excessive mechanical stress on the components are but a few examples of the drawbacks associated with HCCI. The approach employed in this work is the so-called Spark Assisted Compression Ignition (SACI) in combination with a pre-chamber spark plug, enabling short combustion durations even at high dilution levels.

The electrification of vehicle fleets for urban delivery transport is becoming increasingly important due to ever stricter legal requirements and the high public pressure on companies. In this paper, a converted 3.5 t light-duty vehicle with a maximum gross weight of 7.5 t is presented. The vehicle has a serial hybrid electric powertrain with a maximum electric traction power of 150 kW and a 60 kW fuel cell range extender, and uses a 46 kWh battery with 400 V mean voltage level, resulting in a full electric range of 120 km. The electric drive is realized with an induction motor and a lithium-manganese-iron-phosphate (LMFP)-battery as well as a 2-speed gearbox. The fuel cell system has a fuel tank with 100 l volume and 700 bar pressure level, resulting in a total mass of around 4.2 kg of hydrogen. This enables an overall vehicle range of 400 km.

The field of vision of the driver during wet road conditions is essential for safety at all times. Additionally, the safe use of the increasing number of sensors integrated in modern cars for autonomous driving and intelligent driver assistant systems has to be ensured even under challenging weather conditions. To fulfil these requirements during the development process of new cars, experimental and numerical investigations of vehicle soiling are performed. This paper presents the surface contamination of self- and foreign-soiling tested in the wind tunnel. For these type of tests, the fluorescence method is state-of-the-art and widely used for visualizing critical areas. In the last years, the importance of parameters like the contact angle have been identified when designing the experimental setup. In addition, new visualization techniques have been introduced.

Aeroacoustics is important in the automotive industry, as it significantly influences driving comfort. Particularly in the case of battery electric vehicles (BEVs), the flow noise is already crucial at lower driving speeds, since these generate barely any drive noise and the masking effects produced by the engine are eliminated. Due to the increasing importance of drag minimization and elimination of the exhaust system, the underbody of BEVs is typically very streamlined and exhibits a low acoustic interference potential. However, even small geometric modifications to the vehicle can lead to changes in the flow around the vehicle and consequently to significant noise sources. Thus, significant flow resonances in the low frequency range below 30 Hz have been detected on certain vehicle configurations. Initial investigations have shown that the flow around the front wheel spoilers is relevant for the development of the flow phenomenon.

The increasing importance of minimizing drag and the absence of an exhaust system result in battery electric vehicles (BEVs) commonly having a very streamlined underbody. Although this shape of underbody is typically characterized by a low acoustic interference potential, significant flow resonance can be observed for certain vehicle configurations and frequencies below 30 Hz. Since the interior of the vehicle can be excited as a Helmholtz resonator, these low-frequency fluctuations result in reduced comfort for the passengers. As preliminary studies have shown, the flow around the front wheel spoilers significantly influences this flow phenomenon. Flow separation occurs at the front-wheel spoilers and at the front wheels. This leads to the generation of vortices which are growing significantly while being transported downstream with the flow. Even small geometric changes to add-on components on the underbody significantly influence both aerodynamics and aeroacoustics.