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With the automotive industry's increasing focus on electromobility and the growing share of electric cars, new challenges are arising for the development of electric motors. The requirements for torque and power of traction motors are constantly growing, while installation space, costs and weight are increasingly becoming limiting factors. Moreover, there is an inherent conflict in the design between power density and efficiency of an electric motor. Thus, a main focus in today's development lies on space-saving and yet effective and innovative cooling systems. This paper presents an approach for a multi-physical optimization that combines the domains of electromagnetics and thermodynamics. Based on a reference machine, this simulative study examins a total of nine different stator cooling concepts varying the cooling duct positions and end-winding cooling concepts.

Homologation is an important process in vehicle development and aerodynamics a main data contributor. The process is heavily interconnected: Production planning defines the available assemblies. Construction defines their parts and features. Sales defines the assemblies offered in different markets, where Legislation defines the rules applicable to homologation. Control engineers define the behavior of active, aerodynamically relevant components. Wind tunnels are the main test tool for the homologation, accompanied by surface-area measurement systems. Mechanics support these test operations. The prototype management provides test vehicles, while parts come from various production and prototyping sources and are stored and commissioned by logistics. Several phases of this complex process share the same context: Production timelines for assemblies and parts for each chassis-engine package define which drag coefficients or drag coefficient contributions shall be determined.

EU legislation provides for only local CO2 emission-free vehicles to be allowed in individual passenger transport by 2035. In addition, the directive provides for fuels from renewable sources, i.e. defossilised fuels. This development leads to three possible energy sources or forms of energy for use in individual transport. The first possibility is charging with electricity generated from renewable sources, the second possibility is hydrogen generated from renewable sources or blue production path. The third possibility is the use of renewable fuels, also called e-fuels. These fuels are produced from atmospheric CO2 and renewable hydrogen. Possible processes for this are, for example, methanol or Fischer-Tropsch synthesis. The production of these fuels is very energy-intensive and large amounts of renewable electricity are needed.

With the increasing importance of electrified powertrains, electric motors and gear boxes become an important NVH source especially regarding whining noises in the high frequency range. Engine encapsulation noise treatments become often necessary and present some implementation, modeling as well as optimization issues due to complex environments with contact uncertainties, pass-throughs and critical uncovered areas. Relying purely on mass spring systems is often a too massive and relatively unefficient solution whenever the uncovered areas are dominant. Coverage is key and often a combination of hybrid backfoamed porous stiff shells with integral foams for highly complex shapes offer an optimized trade-off between acoustic performance, weight and costs.

Meta material has been known for many years and the physics are well known since decades. But the challenge has always been to put the know how into (mass) production. This was the reason why no meta material has found its way into the automotive industry so far. But now things have changed: meta material became Meta Design and is going into serial production in 2024. Meta Design is a tunable spring mass system with foam acting as the spring and heavy layer as the mass. Meta Design is characterized by cavities in the foam and concentrated masses of the heavy layer as functionalized mass pins. By tuning the size of the cavities and the weight of the mass pins the acoustic performance can be adjusted to the requirements of each individual car line. After preliminary simulations, flat samples were tested in the lab. The next step was launched: the production and testing of a handmade prototype part of a firewall insulation for a Mercedes-Benz A-Class.

Dampers (PDs) are passive devices employed in vibration and noise control applications. They consist of a cavity filled with particles that, when fixed to a vibrating structure, dissipate vibrational energy through friction and collisions among the particles. These devices have been extensively documented in the literature and find widespread use in reducing vibrations in structural machinery components subjected to significant dynamic loads during operation. However, their application in reducing vehicle interior sound has received, up to now, relatively little attention. Previous work by the authors has proven the effectiveness of particle dampers in mitigating vibrations in vehicle body panels, achieving a notable reduction in structure-borne noise within the vehicle cabin with an additional weight comparable to or even lower than that of bituminous damping treatments traditionally used for this purpose.

Although structural intensity was introduced in the 80's, this concept never found practical applications, neither for numerical nor experimental approaches. Quickly, it has been pointed out that only the irrotational component of the intensity offers an easy interpretation of the dynamic behavior of structures by visualizing the vibration energy flow. This is especially valuable at mid and high frequency where the structure response understanding can be challenging. A new methodolodgy is proposed in order to extract this irrotational intensity field from the Finite Element Model of assembled structures such as Bodies In White. This methodology is hybrid in the sense that it employs two distinct solvers: a dynamic solver to compute the structural dynamic response and a thermal solver to address a diffusion equation analogous to the thermal conduction built from the previous dynamic response.

Design verification and quality control of automotive components require the analysis of the source location of ultra-short sound events, for instance the engaging event of an electromechanical clutch or the clicking noise of the aluminium frame of a passenger car seat under vibration. State-of-the-art acoustic cameras allow for a frame rate of about 100 acoustic images per second. Considering that most of the sound events introduced above can be far less than 10ms, an acoustic image generated at this rate resembles an hard-to-interpret overlay of multiple sources on the structure under test along with reflections from the surrounding test environment. This contribution introduces a novel method for visualizing impulse-like sound emissions from automotive components at 10x the frame rate of traditional acoustic cameras.

Gas bearings are an effective solution to high-speed rotor applications for its contamination free, reduced maintenance and higher reliability. However, low viscosity of gas leads to lower dynamic stiffness and damping characteristics resulting in low load carrying capacity and instability at higher speeds. Gas bearings can be enhanced by adding a foil structure commonly known as gas foil bearings (GFBs), whose dynamic stiffness can be tailored by modifying the geometry and the material properties resulting in better stability and higher load carrying capacity. A detailed study is required to assess the performance of high-speed rotor systems supported on GFBs, therefore in this study a bump type GFB is analyzed for its static and dynamic characteristics. The static characteristics are obtained by solving the non-linear Reynolds equation through an iterative procedure.

In electrified vehicles, auxiliary units can be a dominant source of noise, one of which is the refrigerant scroll compressor. Compared to vehicles with combustion engines, e-vehicles re-quire larger refrigerant compressors, as the battery and the electric motors must be cooled in addition to the interior. The compressor causes the acoustic excitation of other refrigeration circuit components and the chassis via pressure pulsations and vibration transmission, as well as emitting airborne sound directly. Sound measurements have been performed in an anecho-ic chamber to investigate the influence of operating conditions on the acoustics of an electric scroll compressor. This paper investigates the influence of the operating conditions on com-pressor acoustics and shows that rotation speed is the main factor influencing compressor noise. The sound spectra of fluid, structure and airborne noise are dominated by speed-dependent, tonal components.

For electric vehicles, road noise, together with wind noise, is the most important contributor for vehicle interior noise. Road noise is very dependent on the NVH behavior of axle system including wheels and tires. Axle system is part of vehicle platform which should be compatible with different body variants. Therefore, il is important to characterize the NVH performance of an axle system independently of car body structure, so that the design the axle can be optimized at the early stage according to the global requirements of all the related vehicles. The best way to characterize the NVH performance of an axle system is to measure the blocked forces on an appropriate test rig. However, the measurement of blocked forces from an axle system requires very stiff boundary conditions which is difficult to achieve in practice. For axles with rigid mountings, it is nearly impossible to measure the blocked forces on test rig.

Electrified vehicles are particularly quiet, especially at low speeds due to the absence of combustion noises. This is why there are laws worldwide for artificial driving sounds to warn pedestrians. These sounds are generated using a so-called Acoustic Vehicle Alerting System (AVAS) which must maintain certain minimum sound pressure levels in specific frequency ranges at low speeds. The creation of the sound currently involves an iterative and sometimes time-consuming process that combines composing the sound on a computer with measuring the levels with a car on an outside noise test track. This continues until both the legal requirements and the subjective demands of vehicle manufacturers are met. To optimize this process and reduce the measurement effort on the outside noise test track, the goal is to replace the measurement with a simulation for a significant portion of the development.

The automotive sector’s growing focus on sustainability has been spurred to investigate the creation of sustainable resources for different parts, emphasizing enhancing efficiency and minimizing environmental harm. For use in automobile flooring trays and underbody shields, this study examines the impact of injection molding on composite materials made of polyvinyl chloride (PVC) and Linum usitatissimum (flax) fibers. As processed organic fiber content was increased, the bending and tensile rigidity initially witnessed an upsurge, peaking at a specific fiber loading. At this optimal loading, the composite exhibited tensile strength, flexural strength, and elastic modulus values of 41.26 MPa, 52.32 MPa, and 2.65 GPa, respectively. Given their deformation resistance and impact absorption attributes, the mechanical properties recorded suggest that such composites can be efficiently utilized for automotive underbody shields and floor trays.

The analysis presented in this document demonstrates the mathematical model approach for determining the rotation of a door about the hinge axis. Additional results from the model are the torque due to gravity about the axis, opening force, and the door hold open check link force. Vector mechanics, equations of a plane, and parametric equations were utilized to develop this model, which only requires coordinate points as inputs. This model allows for various hinge axis angles and door rotation angles to quickly be analyzed. Vehicle pitch and roll angles may also be input along with door mass to determine the torque about the hinge axis. The vector calculations to determine the moment arm of the door check link and its resulting force are demonstrated for both a standard check link design and an alternate check link design that has the link connected to a slider translated along a shaft.

For intelligent vehicles, a robust perception system relies on training datasets with a large variety of scenes. The architecture of federated learning allows for efficient collaborative model iteration while ensuring privacy and security by leveraging data from multiple parties. However, the local data from different participants is often not independent and identically distributed, significantly affecting the training effectiveness of autonomous driving perception models in the context of federated learning. Unlike the well-studied issues of label distribution discrepancies in previous work, we focus on the challenges posed by scene heterogeneity in the context of federated learning for intelligent vehicles and the inadequacy of a single scene for training multi-task perception models. In this paper, we propose a federated learning-based perception model training system.

With the development of internet technology and autonomous vehicles (AVs), the multimodal transportation and distribution model based on AVs will be a typical application paradigm in the smart city scenario. Before AVs carry out logistics distribution, it is necessary to plan a reasonable distribution path based on each customer point, and this is also known as Vehicle Routing Problem (VRP). Unlike traditional VRP, the urban logistics distribution process based on multimodal transportation mode will use a set of different types of AVs, mainly including autonomous ground vehicles and unmanned aerial vehicles (UAVs). It is worth pointing out that there is currently no research on combining the planning of AVs distribution paths with the trajectory planning of UAVs. To address this issue, this article establishes a bilevel programming model. The upper-level model aims to plan the optimal delivery plan for AVs, while the lower-level model aims to plan a driving trajectory for UAVs.

A road test on semi-trailers is carried out, and accelerations of some characteristic points on the braking system,axles,and truck body is measured,also brake pressure and noise around the support frame is acquired.The measured data was analyzed to determine the causes of the brake noise, and the mechanism of the noise of the drum brake of semi-trailers during low-speed braking was investigated. The following conclusions are obtained: (1) Brake noise of the drum brake of the semi-trailer at low-frequency is generated from vibrations of the brake shoes, axle, and body, and the vibration frequency is close to 2nd natural frequency of the axle. (2) Brake noise is generated from stick-slip motion between the brake shoes and the brake drum, where the relative motion between the brake drum and the brake shoes is changed alternately with sliding and sticking, resulting in sudden changes in acceleration and shock vibration.

This paper addresses the issues of long-term signal loss in localization and cumulative drift in SLAM-based online mapping and localization in autonomous valet parking scenarios. A GPS, INS, and SLAM fusion localization framework is proposed, enabling centimeter-level localization with wide scene adaptability at multiple scales. The framework leverages the coupling of LiDAR and Inertial Measurement Unit (IMU) to create a point cloud map within the parking environment. The IMU pre-integration information is used to provide rough pose estimation for point cloud frames, and distortion correction, line and plane feature extraction are performed for pose estimation. The map is optimized and aligned with a global coordinate system during the mapping process, while a visual Bag-of-Words model is built to remove dynamic features.

SLAM (Simultaneous Localization and Mapping) plays a key role in autonomous driving. Recently, 4D Radar has attracted widespread attention because it breaks through the limitations of 3D millimeter wave radar and can simultaneously detect the distance, velocity, horizontal azimuth and elevation azimuth of the target with high resolution. However, there are few studies on 4D Radar in SLAM. In this paper, RI-FGO, a 4D Radar-Inertial SLAM method based on Factor Graph Optimization, is proposed. The RANSAC (Random Sample Consensus) method is used to eliminate the dynamic obstacle points from a single scan, and the ego-motion velocity is estimated from the static point cloud. A 4D Radar velocity factor is constructed in GTSAM to receive the estimated velocity in a single scan as a measurement and directly integrated into the factor graph. The 4D Radar point clouds of consecutive frames are matched as the odometry factor.

Verification and validation (V&V) of autonomous vehicles (AVs) is a challenging task. AVs must be thoroughly tested, to ensure their safe functionality in complex traffic situations including rare but safety-relevant events. Furthermore, AVs must mitigate risks and hazards that result from functional insufficiencies, as described in the Safety of the Intended Functionality (SOTIF) standard. SOTIF analysis includes iterative identification of driving scenarios that are not only unsafe, but also unknown. However, identifying SOTIF’s unknown-unsafe scenarios is an open challenge. In this paper we proposed a systematic optimization-based approach for identification of unknown-unsafe scenarios. The proposed approach consists of three main steps including data collection, feature extraction and optimization towards unknown unsafe scenarios.