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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.

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.

The past five years have seen significant research into autonomous vehicles that employ a by-wire steering rack actuator and no steering wheel. There is a clear synergy between these advancements and the parallel development of complete Steer-by-Wire systems for human-operated passenger vehicle applications. Steer-by-Wire architectures presented thus far in the literature require multiple layers of electrical and/or mechanical redundancy to achieve the safety goals. Unfortunately, this level of redundancy makes it difficult to simultaneously achieve three key manufacturer imperatives: safety, reliability, and cost. Hindered by these challenges, as of 2020 only one production car platform employs a Steer-by-Wire system. This paper presents a Steer-by-Wire architectural solution featuring fail-operational steering control architected with the objective of achieving all system safety, reliability, and cost goals.

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.

The purchase of a new automobile is unquestionably a significant investment for most customers, and with this recognition, comes a correspondingly significant expectation for quality and reliability. Amongst automotive systems -when it comes to considerations of reliability - the brakes (perhaps along with the tires) occupy a rarified position of being located in a harsh environment, subjected to continuous wear throughout their use, and are critical to the safe performance of the vehicle. Maintenance of the brake system is therefore a fact of life for most drivers - something that almost everyone must do, yet given the potentially considerable expense, it is something that of great benefit to minimize.

Machine Learning (ML) based technologies are increasingly being used to fulfill safety-critical functions in autonomous and advanced driver assistance systems (ADAS). This change has been spurred by recent developments in ML and Artificial Intelligence techniques as well as rapid growth of computing power. However, demonstrating that ML-based systems achieve the necessary level of safety integrity remains a challenge. Current research and development work focused on establishing safe operation of ML-based systems presents individual techniques that might be used to gain confidence in these systems. As a result, there is minimal guidance for supporting a safety standard such as ISO 26262 - Road Vehicles - Functional Safety, to enable the development of ML-based systems. This paper presents a survey of recent ML literature to identify techniques and methods that can contribute to meeting ISO 26262 requirements.

Seat lateral support is often talked about as a design parameter, but usually in terms of psychological perception. There are many difficulties in quantifying lateral support mechanically to the engineering teams: Anthropometric variation causes different people to interact with the seat in different places and at different angles, BPD studies are usually planar and don’t distinguish between horizontal support and vertical resistance to sinking in, most mechanical test systems are typically single-DOF and can’t apply vertical and horizontal loads concurrently, and there is scant literature describing the actual lateral loads of occupants. In this study, we characterize the actual lateral loading on example seating from various sized/shaped occupants according to dynamic pressure distribution. From this information, a six-DOF load and position control test robot (KUKA OccuBot) is used to replicate that pressure distribution.

The main objective of this work is to present an adjoint-based methodology to address combined optimization of drag force and cooling flow rate of an industrial vehicle. In order to cope with cooling effect, the volumetric flow rate is treated through a newly introduced cost function and the corresponding adjoint source term is derived. Also an alternative strategy is presented to tackle aerodynamic vehicle design improvement that relies on a so-called indirect force computation. The overall optimization is treated as a Multi-Objective problem and an original approach, called Optimize Both Favor One (OBFO), is introduced that allows selective emphasis on one or another objective without resorting to artificial cost function balancing. Finally, comparative results are presented to demonstrate the merit of the proposed methodology.

As passenger vehicle design evolves and accelerates, the use of multi-body dynamics solvers has proven to be invaluable in the engineering workflow. MBD solvers allow engineers to build virtual vehicle models that can accurately simulate vehicle responses and calculate internal forces, which previously could only be assessed using physical prototype builds with hundreds of measurement transducers. Evaluation and selection of solvers within an engineering environment is inherently a multi-dimensional activity that can include ease of use, retention of previously developed expertise, accuracy, speed, and integration with existing analysis processes. We discuss here some of the challenges present in developing capability and accumulating data to support each of these criteria. Developing a pilot model that is capable of being applied to a comprehensive set of use cases, and then verifying those use cases, required significant project management activity.

This study brings to forefront the analysis capability of CFD for the oil-cooling of an Electric-Motor (E-Motor) powering an automobile. With the rapid increase in electrically powered vehicle, there is an increasing need in the CFD modeling community to perform virtual simulations of the E-Motors to determine the viability of the designs and their performance capabilities. The thermal predictions are extremely vital as they have tremendous impact on the design, spacing and sizes of these motors. In this paper, with the Simerics, Inc. software, Simerics-MP+®, a complete three dimensional CFD with conjugate heat transfer CHT model of an Electric Motor, including all the important parts like the windings, rotor and stator laminate, endrings etc. is created. The multiphase Volume of Fluid (VOF) approach is used to model the oil flow inside this motor.

Automotive liftgate latches have been subject to regulation for minimum strength and inertial resistance requirements since the late 1990’s in the US and globally since the early 2000’s, possibly due to liftgate ejections stemming from the first generation Chrysler minivans which employed latches that were not originally designed with this hazard in mind. Side door latches have been regulated since the 1960’s, and the regulation of liftgate, or back door latches, have been based largely on side door requirements, with the exception of the orthogonal test requirement that is liftgate specific. Based on benchmarking tests of liftgate latches, most global OEM’s design their latches to exceed the minimum regulatory requirements. Presumably, this is based on the need to keep doors closed during crashes and specifically to do so when subjected to industry standard tests.

Since steering wheel torque feedback is one of the crucial factors for drivers to gain road feel and ensure driving safety, it is especially important to simulate the steering torque feedback for a driving simulator. At present, steering wheel feedback torque is mainly simulated by an electric motor with gear transmission. The torque response is typically slow, which can result in drivers’ discomfort and poor driving maneuverability. This paper presents a novel torque feedback device with magnetorheological (MR) fluid and coil spring. A phase separation control method is also proposed to control its feedback torque, including spring and damping torques respectively. The spring torque is generated by coil spring, the angle of coil spring can be adjusted by controlling a brushless DC motor. The damping torque is generated by MR fluid, the damping coefficient of MR fluid can be adjusted by controlling the current of excitation coil.

Adaptive cruise control is an advanced vehicle technology that is unique in its ability to govern vehicle behavior for extended periods of distance and time. As opposed to standard cruise control, adaptive cruise control can remain active through moderate to heavy traffic congestion, and can more effectively reduce greenhouse gas emissions. Its ability to reduce greenhouse gas emissions is derived primarily from two physical phenomena: platooning and controlled acceleration. Platooning refers to reductions in aerodynamic drag resulting from opportunistic following distances from the vehicle ahead, and controlled acceleration refers to the ability of adaptive cruise control to accelerate the vehicle in an energy efficient manner. This research calculates the measured greenhouse gas emissions benefit of adaptive cruise control on a fleet of 51 vehicles over 62 days and 199,300 miles.

Due to growing interest in automated driving, the need for better understanding of human driving behavior in uncertain environment, such as driving behavior at un-signalized crossroad and roundabout, has further increased. Driving behavior at roundabout is greatly influenced by different dynamic factors such as speed, distance and circulating flow of the potentially conflicting vehicles, and drivers should choose whether to leave or wait at the upcoming exit according to these factors. In this paper, the influential dynamic factors and driving behavior characteristics at the roundabout is analyzed in detail, random forest method is then deployed to predict the driving behavior. For training the driving behavior model, four typical roundabout layouts were created under a real-time driving simulator with PanoSim-RT and dSPACE. Traffic participants with different motion style were also set in the simulation platform to mimic real driving conditions.

Analyzing low frequency brake noise (< 300Hz) has been challenging due to the difficulty associated with calculating dynamic friction behavior and its multiple structure-borne noise transfer paths. In theory, it is possible to simulate sound pressure level inside the cabin by calculating a transfer function between friction excitation, which is on the interface between rotor and pads, and cabin acoustic response, and by multiplying dynamic friction force at the rotor-pad interface to that transfer function. However, calculating the dynamic friction forces when brake noise occurs has been one of the most challenging research topics in the brake community. This paper describes a novel concept to simulate sound pressure level inside the cabin without knowing the dynamic friction forces at the rotor-pad interface in advance.

Electrical connections have a normal operational temperature range. A high resistance, such as a poor connection, in an electrical circuit has been reported to cause a temperature increase exceeding normal operational range at the connection. This study measures the temperature increase in a typical automotive bolted battery cable connection with low to zero torque values and simulated high resistance under different load conditions. The torque is changed from maximum design value to 0 Nm and the temperature increase at the connection is measured. The high resistance connections, manually created by adjusting the contacts, are tested for several power loss values at the connection. The temperature rise under these conditions at the connection is measured and subsequently recorded. The maximum temperature increase at the bolted cable connection recorded at low torque values including 0 Nm torque compared to the maximum typical design value of 17 Nm is 10.5 °C.

For virtual simulation of the vehicle attributes such as handling, durability, and ride, an accurate representation of pneumatic tire behavior is very crucial. With the advancement in autonomous vehicles as well as the development of Driver Assisted Systems (DAS), the need for an Intelligent Tire Model is even more on the increase. Integrating sensors into the inner liner of a tire has proved to be the most promising way in extracting the real-time tire patch-road interface data which serves as a crucial zone in developing control algorithms for an automobile. The model under development in Kettering University (KU-iTire), can predict the subsequent braking-traction requirement to avoid slip condition at the interface by implementing new algorithms to process the acceleration signals perceived from an accelerometer installed in the inner liner on the tire.

In recent years, intelligent vehicles have become one of the major research topics in vehicle engineering and have created a new opportunity for the automotive industry. Simulation and real experiment are both essential to the development of intelligent vehicle technologies. Vehicle positioning systems, such as global positioning system (GPS), play an important role in intelligent vehicle development. The GPS model plays a major part in the development of intelligent vehicle simulation systems. Primarily focusing on application requirements of intelligent vehicle simulation platforms for GPS sensor modeling, considering the major factors affecting positioning accuracy in vehicle driving environments, this article establishes a new GPS model and algorithm based on the physical and functional characteristics of GPS. As the basis of this model system, a precise ephemeris model is established to obtain the coordinates of GPS satellites at any given time.

The H-point is a critical part of vehicle design as it is the basis for many engineering dimensions within the vehicle interior. A complete design process includes comparisons of the design to competitive benchmark vehicles. However, the competitive design considerations needed to determine the common standard H-point reference are often unknown. The SAE Human Accommodation and Design Devices (HADD) technical committee recently published a new standard benchmark SgRP procedure [2]. This new standard practice needed to be tested with respect to the accuracy and repeatability for determining the unknown h-point design parameters within industry benchmarking tolerances. In 2019, the SAE HADD committee conducted a study to evaluate the reproducibility of the new procedure. This paper presents detailed results of that study and discusses opportunities for applying the new benchmark practice.

This report describes a new driving simulator capability at General Motors (GM) Research and Development's (R&D) Vehicle Development Research (VDR) Laboratory and its application in an iterative HMI development process. The paper also provides an overview of three recent simulator usability tests supporting HMI development.