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Dust testing of vehicles on unpaved roads is crucial in the development process for automotive manufacturers. These tests aim to ensure the functionality of locking systems in dusty conditions, minimize dust concentration inside the vehicle, and enhance customer comfort by preventing dust accumulation on the car body. Additionally, deposition on safety-critical parts, such as windshields and sensors, can pose threats to driver vision and autonomous driving capabilities. Currently, dust tests are primarily conducted experimentally at proving grounds. In order to gain early insights and reduce the need for costly physical tests, numerical simulations are becoming a promising alternative. Although simulations of vehicle contamination by dry dust have been studied in the past, they have often lacked detailed models for tire dust resuspension. In addition, few publications address the specifics of dust deposition on vehicles, especially in areas such as door gaps and locks.

The improvement of vehicle soiling behavior has increasing interest over the past few years not only to satisfy customer requirements and ensure a good visibility of the surrounding traffic but also for autonomous vehicles, for which soiling investigation and improvement are even more important due to the demands of the cleanliness and induced functionality of the corresponding sensors. The main task is the improvement of the soiling behavior, i.e., reduction or even prevention of soiling of specific surfaces, for example, windows, mirrors, and sensors. This is mostly done in late stages of vehicle development and performed by experiments, e.g., wind tunnel tests, which are supplemented by simulation at an early development stage. Among other sources, the foreign soiling on the side mirror and the side window depend on the droplet detaching from the side mirror housing.

Dry dust testing of vehicles on unpaved dust roads plays a crucial role in the development process of automotive manufacturers. One of the central aspects of the test procedure is ensuring the functionality of locking systems in the case of dust ingress and keeping the dust below a certain concentration level inside the vehicle. Another aspect is the customer comfort because of dust deposited on the surface of the car body. This also poses a safety risk to customers when the dust settles on safety-critical parts such as windshields and obstructs the driver’s view. Dust deposition on sensors is also safety critical and is becoming more important because of the increasing amount of sensors for autonomous driving. Nowadays, dust tests are conducted experimentally at dust proving grounds. To gain early insights and avoid costly physical testing, numerical simulations are considered a promising approach. Simulations of vehicle contamination by dry dust have been studied in the past.

The investigation of vehicle soiling by improvement of vehicle parts to optimize the surrounding airflow is of great importance not only because of the visibility through windows and at mirrors but also the functionality of different types of sensors (camera, lidar, radars, etc.) for the driver assistance systems and especially for autonomous driving vehicles has to be guaranteed. These investigations and corresponding developments ideally take place in the early vehicle development process since later changes are difficult to apply in the vehicle production process for many reasons. Vehicle soiling is divided into foreign soiling and self-soiling with respect to the source of the soiling water, e.g., direct rain impact, swirled (dirty) water of other road users and own rotating wheels. The investigations of the soiling behavior of vehicles were performed experimentally in a wind tunnel and street tests.

The turbulent flow around vehicles causes high amplitude pressure fluctuations at the underbody, consisting of both hydromechanic and acoustic contributions. This induces vibrations in the underbody structures, which in turn may lead to sound transmission into the passenger compartment, especially at low frequencies. To study these phenomena we present a run time fully coupled acoustic-fluid-structure interaction framework expanding a validated hybrid CFD-CAA solver. The excited and vibrating underbody is resembled by an aluminium plate in the underbody of the SAE body which allows for sound transmission into the interior. Different excitation situations are generated by placing obstacles at the underbody upstream of the aluminium plate. For this setup we carry out a fully coupled simulation of flow, acoustics and vibration of the plate.

In order to predict reality as accurately as possible leads to the fact that numerical models in automotive vibroacoustic problems become increasingly high dimensional. This makes applications with a large number of model evaluations, e.g. optimization tasks or uncertainty quantification hard to solve, as they become computationally very expensive. Engineers are thus faced with the challenge of making decisions based on a limited number of model evaluations, which increases the need for data-efficient methods and reduced order models. In this contribution, variational autoencoders (VAEs) are used to reduce the dimensionality of the vibroacoustic model of a vehicle body and to find a low-dimensional latent representation of the system.

Raising demands towards lightweight design paired with a loss of originally predominant engine noise pose significant challenges for NVH engineers in the automotive industry. From an aeroacoustic point of view, low frequency buffeting ranks among the most frequently encountered issues. The phenomenon typically arises due to structural transmission of aerodynamic wall pressure fluctuations and/or, as indicated in this work, through rear vent excitation. A possible workflow to simulate structure-excited buffeting contains a strongly coupled vibro-acoustic model for structure and interior cavity excited by a spatial pressure distribution obtained from a CFD simulation. In the case of rear vent buffeting no validated workflow has been published yet. While approaches have been made to simulate the problem for a real-car geometry such attempts suffer from tremendous computation costs, meshing effort and lack of flexibility.

Classical decentralized architectures based on large networks of microprocessor-based Electronic Control Units (ECU), namely those used in self-driving cars and other highly-automated applications used in the automotive industry, are becoming more and more complex. These new, high computational power demand applications are constrained by limits on energy consumption, weight, and size of the embedded components. The adoption of new embedded centralized electrical/electronic (E/E) architectures based on dynamically reconfigurable hardware represents a new possibility to tackle these challenges. However, they also raise concerns and questions about their safety. Hence, an appropriate evaluation must be performed to guarantee that safety requirements resulting from an Automotive Safety Integrity Level (ASIL) according to the standard ISO 26262 are met. In this paper, a methodology for the evaluation of dynamically reconfigurable systems based on centralized architectures is presented.

The Deep Orange program is a concept vehicle development program focused on providing hands-on experience in design, engineering, prototyping and production planning as part of students’ two-year MS graduate education. Throughout this project, the team was challenged to create innovative concepts during the ideation phase as part of building the running vehicle. This paper describes the usability studies performed on two of the vehicle concepts that require driver interaction. One concept is a human machine interface (HMI) that uses a holographic companion that can act as a concierge for all functions of the vehicle. After creating a prototype using existing technologies and developing a user interface controlled by hand gestures, a usability study was completed with older adults. The results suggest the input method was not intuitive. Participants demonstrated better performance with tasks using discrete hand motions in comparison to those that required continuous motions.

A key metric of a car body structure is the body stiffness, which shows significant correlation with different vehicle performance attributes as NVH, comfort and vehicle handling. Typical approaches to identify static stiffness characteristics are the use of a static stiffness test bench or the ‘static-from-dynamic’ approach in which free-free acquired transfer functions are used to build a modal model from which the static stiffness characteristics are extracted. Both of these approaches have limitations, the static stiffness bench with respect to clamping conditions and reproducing those in CAE, the static-from-dynamic with respect to the modal analysis (EMA) that needs to be performed. EMA is a subjective process, which can limit result robustness. In addition, performing EMA on a trimmed body is difficult due to the high modal density and the high level of damping.

Electromechanical steering systems (EPS) provide assisting steering force through an electric motor, often paired with a screw drive. The combination of an electric motor and a screw drive lead to high inertia and thus to a reduced feedback of tire force behavior at the steering wheel. This force behavior contains information about driving conditions and road surface. However, the electric motor can be used to actively enhance and manipulate steering feedback. This article describes the driver perception of modified steering feedback. The presented data is collected carrying out a driving simulator study with average drivers as test subjects. In this study the driver experiences a modified steering feedback at a change of road friction coefficient. Based on the test subjects ratings the perception, acceptance and controllability of the presented steering feedback modifications are assessed.

Two optical techniques were developed and combined with a CFD simulation to obtain spatio-temporally resolved information on air/fuel mixing in the cylinder of a methane-fueled, fired, optically accessible engine. Laser-induced fluorescence (LIF) of anisole (methoxybenzene), vaporized in trace amounts into the gaseous fuel upstream of the injector, was captured by a two-camera system, providing one instantaneous image of the air/fuel ratio per cycle. Broadband infrared (IR) absorption by the methane fuel itself was measured in a small probe volume via a spark-plug integrated sensor, yielding time-resolved quasi-point information at kHz-rates. The simulation was based on the Reynolds-averaged Navier-Stokes (RANS) approach with the two-equation k-epsilon turbulence model in a finite volume discretization scheme and included the port-fuel injection event. Commercial CFD software was used to perform engine simulations close to the experimental conditions.

In times when automated driving is becoming increasingly relevant, dynamic simulators present an appropriate simulation environment to faithfully reproduce driving scenarios. A realistic replication of driving dynamics is an important criterion to immerse persons in the virtual environments provided by the simulator. Motion Cueing Algorithms (MCAs) compute the simulator’s control input, based on the motions of the simulated vehicle. The technical restrictions of the simulator’s actuators form the main limitation in the execution of these input commands. Typical dynamic simulators consist of a hexapod with six degrees of freedom (DoF) to reproduce the vehicle motion in all dimensions. Since its workspace dimensions are limited, significant improvements in motion capabilities can be achieved by expanding the simulator with redundant DoF by means of additional actuators.

This paper summarizes the development of a wireless message from infrastructure-to-vehicle (I2V) for safety applications based on Dedicated Short-Range Communications (DSRC) under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). During the development of the Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure (RSZW/LC) safety applications [1], the Basic Information Message (BIM) was developed to wirelessly transmit infrastructure-centric information. The Traveler Information Message (TIM) structure, as described in the SAE J2735, provides a mechanism for the infrastructure to issue and display in-vehicle signage of various types of advisory and road sign information. This approach, though effective in communicating traffic advisories, is limited by the type of information that can be broadcast from infrastructures.

This paper summarizes the validation of prototype vehicle-to-infrastructure (V2I) safety applications based on Dedicated Short Range Communications (DSRC) in the United States under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). After consideration of a number of V2I safety applications, Red Light Violation Warning (RLVW), Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure Warning (RSZW/LC) were developed, validated and demonstrated using seven different vehicles (six passenger vehicles and one Class 8 truck) leveraging DSRC-based messages from a Road Side Unit (RSU). The developed V2I safety applications were validated for more than 20 distinct scenarios and over 100 test runs using both light- and heavy-duty vehicles over a period of seven months. Subsequently, additional on-road testing of CSW on public roads and RSZW/LC in live work zones were conducted in Southeast Michigan.

Battery electric vehicles (BEVs) are equipped with Mobile Air Conditioning systems (MACs) to ensure a comfortable cabin temperature in all climates and ambient conditions as well as the optional conditioning of the traction battery. An assessment of the global electrical energy consumption of various MACs has been derived, where the basis of the assessment procedure is the climate data GREEN-MAC-LCCP 2007 (Global Refrigerants Energy & Environmental - Mobile Air Condition - Life Cycle Climate Performance) and the improved LCCP2013 (Life Cycle Climate Performance. The percentage driving time during 6 AM and 24 PM is divided into six different temperature bins with the solar radiation and relative humidity for 211 cities distributed over Europe, North, Central, and South America, Asia, South West Pacific, and Africa. The energy consumption of the MACs is determined by a thermal vehicle simulation. In this work, four different MACs are simulated and compared.

The Deep Orange program immerses automotive engineering students into the world of an OEM as part of their 2-year graduate education. In support of developing the program’s seventh vehicle concept, the students studied the sponsoring brand essence, conducted market research, and made a heuristic assessment of competitor vehicles. The upfront research lead to the definition of target customers and setting vehicle level targets that were broken down into requirements to develop various vehicle sub-systems. The powertrain team was challenged to develop a scalable propulsion concept enabled by a common vehicle architecture that allowed future customers to select (at the point of purchase) among various levels of electrification best suiting their needs and personal desires. Four different configurations were identified and developed: all-electric, two plug-in hybrid electric configurations, and an internal combustion engine only.

Water vapor is, aside from carbon dioxide, the major fossil fuel combustion by-product. Depending on its concentration in the exhaust gas mixture as well as on the exhaust gas pressure, its condensation temperature can be derived. For typical gasoline engine stoichiometric operating conditions, the water vapor dew point lies at about 53 °C. The exhaust gas mixture does however contain some pollutants coming from the fuel, engine oil, and charge air, which can react with the water vapor and affect the condensation process. For instance, sulfur trioxide present in the exhaust, reacts with water vapor forming sulfuric acid. This acid builds a binary system with water vapor, which presents a dew point often above 100 °C. Exhaust composition after leaving the combustion chamber strongly depends on fuel type, engine concept and operation point. Furthermore, the exhaust undergoes several chemical after treatments.

Adoption of high-pressure common-rail (HPCR) fuel systems, which subject diesel fuels to higher temperatures and pressures, has brought into question the veracity of ASTM International specifications for biodiesel and biodiesel blend oxidation stability, as well as the lack of any stability parameter for diesel fuel. A controlled experiment was developed to investigate the impact of a light-duty diesel HPCR fuel system on the stability of 20% biodiesel (B20) blends under conditions of intermittent use and long-term storage in a relatively hot and dry climate. B20 samples with Rancimat induction periods (IPs) near the current 6.0-hour minimum specification (6.5 hr) and roughly double the ASTM specification (13.5 hr) were prepared from a conventional diesel and a highly unsaturated biodiesel. Four 2011 model year Volkswagen Passats equipped with HPCR fuel injection systems were utilized: one on B0, two on B20-6.5 hr, and one on B20-13.5 hr.

New technologies such as multi-core and Ethernet provide vastly improved computing and communications capabilities. This sets the foundation for the implementation of new digital megatrends in almost all areas: driver assistance, vehicle dynamics, electrification, safety, connectivity, autonomous driving. The new challenge: We must share these computing and communication capacities among all vehicle functions and their software. For this step, we need a good resource planning to minimize the probability of late resource bottlenecks (e.g. overload, lack of real-time capability, quality loss). In this article, we summarize the status quo in the field of resource management and provide an outlook on the challenges ahead.