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With the advent of this new era of electric-driven automobiles, the simulation and virtual digital twin modeling world is now embarking on new sets of challenges. Getting key insights into electric motor behavior has a significant impact on the net output and range of electric vehicles. In this paper, a complete 3D CFD model of an Electric Motor is developed to understand its churning losses at different operating speeds. The simulation study details how the flow field develops inside this electric motor at different operating speeds and oil temperatures. The contributions of the crown and weld endrings, crown and weld end-windings, and airgap to the net churning loss are also analyzed. The oil distribution patterns on the end-windings show the effect of the centrifugal effect in scrapping oil from the inner structures at higher speeds. Also, the effect of the sump height with higher operating speeds are also analyzed.

The study focuses on understanding the air and oil flow characteristics within a ball bearing during high-speed rotation, with a particular emphasis on optimizing frictional heat dissipation and oil lubrication methods. Computational fluid dynamics (CFD) techniques are employed to analyze the intricate three-dimensional airflow and oil flow patterns induced by the motion of rotating and orbiting balls within the bearing. A significant challenge in conducting three-dimensional CFD studies lies in effectively resolving the extremely thin gaps existing between the balls, races, and cages within the bearing assembly. In this research, we adopt the ball-bearing structured meshing strategy offered by Simerics-MP+ to meticulously address these micron-level clearances, while also accommodating the rolling and rotation of individual balls. Furthermore, we investigate the impact of different designs of the lubrication ports to channel oil to other locations compared to the ball bearings.

Performance testing and evaluation always plays an important role in the developmental process of a vehicle, which also applies to autonomous vehicles. The complex nature of an autonomous vehicle from architecture to functionality demands even more quality-and-quantity controlled testing and evaluation than ever before. Most of the existing testing methodologies are task-or-scenario based and can only support single or partial functional testing. These approaches may be helpful at the initial stage of autonomous vehicle development. However, as the integrated autonomous system gets mature, these approaches fall short of supporting comprehensive performance evaluation. This paper proposes a novel hierarchical and systematic testing and evaluation approach to bridge the above-mentioned gap.

This paper presents a computational fluid dynamics (CFD) model for predicting power losses associated with churning of oil by gears or other similar rotating components. The modeling approach and parameters are optimized to ensure the accuracy, robustness, and computational efficiency of these predictions. These studies include a look at two types of mesh and a turbulence model selection. The focus is on multiple reference frame (MRF) modeling technique for its computational efficiency advantage. Model predictions are compared to previously published experimental data [1] under varying operating conditions typical for an automotive transmission application. The model shows good agreement with the hardware both quantitatively and qualitatively, capturing the trends with speed and submersion level. The paper concludes with presenting some key lessons learned, and recommendation for future work to ultimately build a highly reliable tool as part of the virtual product development.

During a vehicle drive cycle, the oil in the engine oil pan sloshes very vigorously due to the acceleration of the vehicle. This can cause the pickup tube in the engine oil pan to become uncovered from oil and exposed to air, which affects the lubrication pump performance. Engine oil pan sloshing is inherently a 3D problem as the free oil surface is constantly changing. Multi-dimensional Computational Fluid Dynamics (CFD) methods are very useful to simulate such problems with high detail and accuracy but are computationally very expensive. Part of the engine lubrication system, such as the pump, can be modelled in 1D which can predict accurate results at relatively high computational speeds. By utilizing the advantages of both 1D and 3D CFD models, a coupled 1D-3D simulation approach has been developed to capture the detailed oil sloshing phenomenon in SimericsMP+ and the system level simulation is conducted in GT-SUITE where 3D spatial data is not required.

Advanced driver assistance systems (ADAS) are being developed for more and more complicated application scenarios, which often require more predictive strategies with better understanding of driving environment. Taking traffic vehicles’ maneuvers into account can greatly expand the beforehand time span for danger awareness. This paper presents a maneuver-based strategy to vehicle collision threat assessment. First, a maneuver-based trajectory prediction model (MTPM) is built, in which near-future trajectories of ego vehicle and traffic vehicles are estimated with the combination of vehicle’s maneuvers and kinematic models that correspond to every maneuver. The most probable maneuvers of ego vehicle and each traffic vehicles are modeled and inferred via Hidden Markov Models with mixture of Gaussians outputs (GMHMM). Based on the inferred maneuvers, trajectory sets consisting of vehicles’ position and motion states are predicted by kinematic models.

The objective of this study is to develop a robust framework to model shock-turbulence interactions that happen in many engineering applications dealing with compressible flows. The model is essentially a hybrid algorithm to address the conflict between turbulence modeling and shock-capturing requirements. A skew-symmetric form of a co-located finite volume scheme with minimum aliasing errors is implemented to model the turbulent region in the combination of a semi-discrete, central scheme to capture the discontinuities with sufficiently low dissipation to minimize the effect of large eddy simulation (LES) for turbulent flows. To evaluate the effectiveness of the model, LESs are conducted to study the interaction of stationary shocks with turbulent flows. The simulations of the shock-turbulence interaction show the same physical trends as previously published results for high-fidelity DNS and LES.

Fuel chemistry plays a crucial role in the continued reduction of particulate emissions (PE) and cleaner air quality from vehicles and equipment powered by internal combustion engines (ICE). Over the past ten years, there have been great improvements in predictive particulate emissions indices (correlative mathematical models) based on the fuel’s composition. Examples of these particulate indices (PI) are the Honda Particulate Matter Index (PMI) and the General Motors Particulate Evaluation Index (PEI). However, the analytical chemistry lab methods used to generate data for these two PI indices are very time-consuming. Because gasoline can be mixtures of hundreds of hydrocarbon compounds, these lab methods typically include the use of the high resolution chromatographic separation techniques such as detailed hydrocarbon analysis (DHA), with 100m chromatography columns and long (3 - 4 hours) analysis times per sample.

Longitudinal vortex generation is a common technique for enhancing heat transfer performance. It can be achieved by employing small flow manipulators, known as vortex generators (VGs), which are placed on the heat-transfer surface. The vortex generators can generate longitudinal vortices, which strongly disturb the flow structure, and have a significant influence on the velocity and temperature distributions, causing improved thermal transport. In this work, numerical simulations are conducted for a horizontal rectangular channel with and without a pair of longitudinal vortex generators. The vortex generators are fitted vertically on the bottom surface of the channel. The Computational Fluid Dynamics (CFD) analysis aims to acquire a better understanding of the flow structure and heat transfer mechanisms induced by longitudinal vortex generation. The simulation is performed using ANSYS Fluent, and three flow inlet velocities are considered: 1.38 m/s, 1.18 m/s, 0.98 m/s.

The design and development of electric vehicles involves many unique challenges. One such challenge involves accurately predicting driveline abuse torque loads early in the design cycle to aid with sizing drive-unit and driveline components. Since electrified drivelines typically lack a torque-limiting “fuse” element such as a torque converter or slipping clutch, they can be vulnerable to sudden transient events involving high wheel acceleration or deceleration. Component sizing must account for the loads caused by such events, and these loads must be accurately quantified early on when vehicle parameters haven’t been finalized yet. Early load predictions can be made by completing abuse maneuver simulations where key parameters are varied to gauge their influence on simulated loads. Understanding how these parameters impact loads allows for better risk assessment during the design process, as these parameters will inevitably change until a final design is iterated upon.

Speaker performance in Acoustic Vehicle Alerting System (AVAS) plays a crucial role for pedestrian safety. Sound radiation from AVAS speaker has obvious directivity pattern. Considering this feature is critical for accurately simulating the exterior sound field of electrical vehicles. This paper proposes a new process to characterize the sound directivity pattern of AVAS speaker. The first step of the process is to perform an acoustic testing to measure the sound pressure radiated from the speaker at a certain number of microphone locations in a free field environment. Based on the geometry of a virtual speaker, the locations of each microphone and measured sound pressure data, an inverse method, namely the inverse pellicular analysis, is adopted to recover a set of vibration pattern of the virtual speaker surface. The recovered surface vibration pattern can then be incorporated in the full vehicle numerical model as an excitation for simulating the exterior sound field.

Online road profiling capability is required for automotive active suspension systems to be realized in a commercial landscape. The challenges that impede the realization of these systems include a profiler’s ability to maintain an optimal resolution of the oncoming road profile (spatial frequency). Shifting of the profile measurement frame of reference due to body motion disturbances experienced by the vehicle also negatively impacts profiling capability. This work details the early development of a corrective look-ahead road profiling system (CLARPS) and its control logic. The CLARPS components are introduced and additional focus will be given to the development of the angle generating function (AGF) and how it drives the ability of the system to optimize look-ahead viewing angles for the best spatial frequency resolution of a road profile. The CLARPS simulation environment is demonstrated with numerical comparison of simulated road profiles at varying vehicle speeds.

Bearings are a major component in any rotating system. With continually increasing speeds, bearing failure modes take new unconventional forms that often are not understood. In high speed applications, rolling element forces and gyroscopic moments can be significantly high compared to the applied forces acting on a bearing. Such moments create a “driving” torque causing outer race to creep. In this paper a mathematical model for the dynamics of a rolling element in a high speed bearing is derived. Preload values counterbalancing the torque driving the outer race to rotate can be predicted from this model. An attempt to experimentally measure this torque using a specially designed apparatus with integrated strain gauge torque sensor is also described. Both model and experimental measurements are aimed at understanding, and therefore preventing bearing failures due to outer race (creep) rotations.

Hood insulators are widely used in automotive industry to improve noise insulation, pedestrian impact protection and to provide aesthetic appeal. They are attached below the hood panel and are often complex in shape and size. Pedestrian head impacts are highly dynamic events with a compressive strain rate experienced by the insulator exceeding 300/s. The energy generated by the impact is partly absorbed by the hood insulators thus reducing the head injury to the pedestrian. During this process, the insulator experiences multi-axial stress states. The insulators are usually made of soft multi-layered materials, such as polyurethane or fiberglass, and have a thin scrim layer on either side. These materials are foamed to their nominal thickness and are compression molded to take the required shape of the hood. During this process they undergo thickness reduction, thereby increasing their density.

Automotive technology is rapidly changing with electrification of vehicles, driver assistance systems, advanced safety systems etc. This advancement in technology is making the task of validation and verification of embedded software complex and challenging. In addition to the component testing, integration testing imposes even tougher requirements for software testing. To meet these challenges dSPACE is continuously evolving the Hardware-In-the-Loop (HIL) technology to provide a systematic way to manage this task. The paper presents developments in the HIL hardware technology with latest quad-core processors, FPGA based I/O technology and communication bus systems such as Flexray. Also presented are developments of the software components such as advanced user interfaces, GPS information integration, real-time testing and simulation models. This paper provides a real-world example of implication of integration testing on HIL environment for Chassis Controls.

All-wheel drive (AWD) vehicle performance considerably depends not only on total power amount needed for the vehicle motion in the given road/off-road conditions but also on the total power distribution among the drive wheels. In turn, this distribution is largely determined by the driveline system and its mechanisms installed in power dividing units. They are interwheel, interaxle reduction gears, and transfer cases. The paper presents analytical methods to evaluate the energy and, accordingly, fuel efficiency of vehicles with any arbitrary number of the drive wheels. The methods are based on vehicle power balance equations analysis and give formulas that functionally link the wheel circumferential forces with slip coefficients and other forces acting onto an AWD vehicle. The proposed methods take into consideration operational modes of vehicles that are tractive mode, load transportation, or a combination of both.

Given their high-power density, large range of speed change, and reputation of being quieter than counter-shaft gear sets, planetary gear sets (PGS) have advantages to be applied in electric vehicle (EV) applications. Since electric drive unit (EDU) designs are often subject to accelerated development timelines with more versatile gear set layouts than conventional automotive transmissions, accurate prediction of PGS load sharing is needed. In the past, PGS load sharing imbalance used to be considered as a gear set problem focusing only on the effect to gear performance. Finding a closed-form formula has been a focus in gear design. However, early bearing failure in wind turbine gearboxes exposed the limitation of this strategy. With extensive field and laboratory testing, engineers started to notice that load sharing imbalance is essentially a system issue. Non-torque loads on PGS should be considered in the estimation by a gearbox system model.

AASHTO I-Beam is a standard structural concrete part for bridge sections. The flexural performance of an AASHTO I-Beam is critical for bridge design. This paper presents an application of Digital Image Correlation (DIC) Method in full-scale AASHTO I-Beam flexural performance study. A full-scale AASHTO I-Beam pre-stressed with steel strands is tested by three-point bending method. The full-scale AASHTO I-Beam is first loaded from 0 kips to 100 kips and is then released from 100 kips to 0 kips. A dual-camera 3D Digital Image Correlation (DIC) system is used to measure the deflection and strain distribution during the testing. From the DIC results, the micro-crack generation progress during the loading progress can be observed clearly from the measured DIC strain map. To enable such a large-scale DIC measurement, the used DIC setup is optimized in terms of the optical imaging system and speckle pattern size.

Vehicle manufacturers conduct tests to develop crash sensing system calibrations. Ditch fall-over is one of a suite of laboratory tests used to develop rollover sensing calibrations that can trigger deployment of safety devices like roof rail airbags and seat belt pretensioners. The ditch fall-over test simulates a flat road followed by a ditch on one side of the road. The vehicle heads into the ditch and the driver applies swift steer input once the ditch slope is sensed. Typically, the steer input is applied when the two down-slope wheels on the ditch side enter the ditch. Multi-Body Dynamics (MBD) software can be used for virtual simulation of these test events. Conventionally in simulations, the vehicle-model is run without steer input and the marking line crossing time is observed/manually recorded from observation of simulation video. This recorded time is used to apply the steer input and the full event is then re-simulated.

In traditional FE based structure-borne noise analysis, interior trims are normally modeled as lump masses in the FE structure model and acoustic specific impedance of the trim is assigned to the FE acoustics model when necessary. This simplification has proven to be effective and sufficient for low frequency analysis. However, as the frequency goes into the mid-frequency range, the elastic behavior of the trim may impose some effects on the structural and acoustic responses. The approach described in this paper is based on the structural FE and acoustic SEA coupling analysis developed by ESI, aiming to improve the modeling efficiency for a possible quick turnaround in virtual assessments.