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This study evaluated the interactions between sheet steel, lubricant and measurement system under typical sheet forming conditions using a fixed draw bead simulator (DBS). Deep drawing quality mild steel substrates with bare (CR), electrogalvanized (EG) and hot dip galvanized (HDG) coatings were tested using a fixed DBS. Various lubricant conditions were targeted to evaluate the coefficient of friction (COF) of the substrate and lubricant combinations, with only rust preventative mill oil (dry-0 g/m2 and 1 g/m2), only forming pre-lube (dry-0 g/m2, 1 g/m2, and >6 g/m2), and a combination of two, where mixed lubrication cases, with incremental amounts of a pre-lube applied (0.5, 1.0, 1.5 and 2.0 g/m2) over an existing base of 1 g/m2 mill oil, were analyzed. The results showed some similarities as well as distinctive differences in the friction behavior between the bare material and the coatings.

A simulation tool has been developed for predicting steering effort of a vehicle during steering power-assist system failure. The vehicle system is modeled with the inclusion of a system-level vehicle model and a steering system model that are linked together through the steering moment at the kingpin and front road wheel angle. A driver model has also been designed to provide closed-loop steering angular input to make the car follow a certain target path. The simulation model is correlated well with actual vehicle tests under various steering input and lateral acceleration conditions. Also illustrated are some examples of comparison between measured and simulated sensitivity study for selected factors.

Driveline torque distribution has long been a research topic, and in the last several decades research has been directed towards enhancing on-road vehicle stability and agility through application of controllable driveline systems. This paper discusses the impact of Direct Yaw Control AWD systems (DYC AWD Systems) on the combined acceleration and turning performance as it pertains to maneuverability and stability on all road surfaces. To achieve higher levels of both safety and performance, the application of a controllable DYC AWD system capable of applying direct yaw moment to the vehicle chassis serves as a key goal to achieve the optimal result. A classification of existing driveline systems is discussed and compared to these optimal requirements. Representative on-vehicle scenarios are discussed to illustrate the impact of AWD control on the vehicle stability and maneuverability and to highlight the effects to the vehicle operator.

Unusual noises during vehicle acceleration often reflect poorly on customer perception of product quality and must be removed in the product development process. Flow simulation can be a valuable tool in identifying root causes of exhaust noises created due to tailpipe openings surrounded by fascia structure. This paper describes a case study where an unsteady Computational Fluid Dynamics (CFD) simulation of the combined flow and acoustic radiation from an exhaust opening through fascia components provided valuable insight into the cause of an annoying flow noise. Simulation results from a coupled thermal/acoustic analysis of detailed tailpipe opening geometry were first validated with off-axis microphone spectra under wide open throttle acceleration. After studying the visualizations of unsteady flow velocity and pressure from the CFD, a problem that had proved difficult to solve by traditional “cut and try” methods was corrected rapidly.

Road induced structural feel “vehicle feels solidly built” is strongly related to the vehicle ride [1]. Excellent structural feel requires both structural and suspension dynamics considerations simultaneously. Road induced structural feel is defined as customer facing structural and component responses due to tire force inputs stemming from the unevenness of the road surface. The customer interface acceleration and noise responses can be parsed into performance criteria to provide design and tuning vehicle integration program recommendations. A dynamic impact bump method is developed for vehicle level structural feel performance assessment, diagnostics, and development tuning. Current state of on-road testing has the complexity of multiple impacts, averaging multiple road induced tire patch impacts over a length of a road segment, and test repeatability challenges.

More than four decades ago, the concept of zero defects was coined by Phillip Crosby. It was only a vision at the time, but the introduction of Artificial Intelligence (AI) in manufacturing has since enabled it to become attainable. Since most mature manufacturing organizations have merged traditional quality philosophies and techniques, their processes generate only a few Defects Per Million of Opportunities (DPMO). Detecting these rare quality events is one of the modern intellectual challenges posed to this industry. Process Monitoring for Quality (PMQ) is an AI and big data-driven quality philosophy aimed at defect detection and empirical knowledge discovery. Detection is formulated as a binary classification problem, where the right Machine Learning (ML), optimization, and statistics techniques are applied to develop an effective predictive system.

An objective benchmarking process for vehicle dynamics that incorporates both test and simulation was used in the development of a sedan. Data from objective measurements of vehicle handling response was used as input to simulation. Simulation results generated a range of system level characteristics to evaluate on a test vehicle. In detail, this process includes system level vehicle simulation software for model building and generating an array of output characteristics. The directional changes were then applied to early build prototype vehicles for focused objective and subjective vehicle evaluation.

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.

In the previous research1), the authors discovered that the sudden pressure increase phenomenon in diesel particulate filter (DPF) was a result of soot collapse inside DPF channels. The proposed hypothesis for soot collapse was a combination of factors such as passive regeneration, high humidity, extended soak period, high soot loading and high exhaust flow rate. The passive regeneration due to in-situ NO2 and high humidity caused the straw like soot deposited inside DPF channels to take a concave shape making the collapse easier during high vehicle acceleration. It was shown that even if one of these factor was missing, the undesirable soot collapse and subsequent back pressure increase did not occur. Currently, one of the very popular NOx reduction technologies is the Selective Catalytic Reduction (SCR) on Filter which does not have any platinum group metal (PGM) in the washcoat.

Vehicle certification requirements generally fall into 2 categories: self-certification and various forms of type approval. Self-certification requirements used in the United States under Federal Motor Vehicle Safety Standards (FMVSS) regulations must be objective and measurable with clear pass / fail criteria. On the other hand, Type Approval requirements used in Europe under United Nations Economic Commission for Europe (UNECE) regulations can be more open ended, relying on the mandated 3rd party certification agency to appropriately interpret and apply the requirements based on the design and configuration of a vehicle. The use of 3rd party certification is especially helpful when applying regulatory requirements for complex vehicle systems that operate dynamically, changing based on inputs from the surrounding environment. One such system is Adaptive Driving Beam (ADB).

Hybrid powertrain vehicles inherently create discontinuous sounds during operation. The discontinuous noise created from the electrical motors during transition states are undesirable since they can create tones that do not correlate with the dynamics of the vehicle. The audible level of these motor whines and discontinuous tones can be reduced via common noise abatement techniques or reducing the amount of regeneration braking. One electronic solution which does not affect mass or fuel economy is Masking Sound Enhancement (MSE). MSE is an algorithm that uses the infotainment system to mask the naturally occurring discontinuous hybrid drive unit and driveline tones. MSE enables a variety of benefits, such as more aggressive regenerative braking strategies which yield higher levels of fuel economy and results in a more pleasing interior vehicle powertrain sound. This paper will discuss the techniques and signals used to implement MSE in a hybrid powertrain equipped vehicle.

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.

As one of advanced driver assistance systems (ADAS), automatic parking system has great market prospect and application value. In this paper, based on an intelligent vehicle platform, an automatic parking system is designed by using multi-point preview theory. The vehicle kinematics model was established, based on Ackermann steering principle. By analyzing working conditions of parallel parking, complex constraint condition of parking trajectory is established and reference trajectory based on sine wave is proposed. In addition, combined with multi-point preview theory, the design of trajectory following controller for automatic parking is completed. The cost function is designed, which consider the trajectory following effect and the degree of easy handling. The optimization of trajectory following control is completed by using the cost function.

Understanding customer expectations is critical to satisfying customers. Holding customer clinics is one approach to set winning targets for the engineering functional measures to drive customer satisfaction. In these clinics, customers are asked to operate and interact with vehicle systems or subsystems such as doors, lift gates, shifters, and seat adjusters, and then rate their experience. From this customer evaluation data, engineers can create customer loss or preference functions. These functions let engineers set appropriate targets by balancing risks and benefits. Statistical methods such as cumulative customer loss function are regularly applied for such analyses. In this paper, a new approach based on the Taguchi method is proposed and developed. It is referred to as Taguchi Customer Loss Function (TCLF).

Fabric materials have diverse applications in the automotive industry which include upholstery, carpeting, safety devices, and interior trim components. The textile industry has invested substantial effort toward development of standard testing techniques for characterizing mechanical properties of different fabric types (e.g. woven and knitted). However, there are presently no standards for determination of Young's modulus, Poisson's ratio and tensile stress-strain properties required for the detailed modeling of fabric materials in vehicle structural simulations. This paper presents results from uniaxial tensile tests of different automotive seat cover fabric materials. Digital image correlation, a full field optical method for measuring surface deformation, was used to determine tensile properties in both the warp/wale and the weft/course directions. The fabrics were tested with and without the foam backing.

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.

Knowledge of the tire slip ratio can greatly improve vehicle longitudinal stability and its dynamic performance. Most conventional slip ratio observers were mainly designed based on input of non-driven wheel speed and estimated vehicle speed. However, they are not applicable for electric vehicles (EVs) with four in-wheel motors. Also conventional methods on speed estimation via integration of accelerometer signals can often lead to large offset by long-time integral calculation. Further, model uncertainties, including steady state error and unmodeled dynamics, are considered as additive disturbances, and may affect the stability of the system with estimated state error. This paper proposes a novel slip ratio observer based on input-to-state stability (ISS) method for electric vehicles with four-wheel independent driving motors.

The automotive industry is facing many significant challenges that go far beyond the design and manufacturing of automobile products. Connected, autonomous and electric vehicles, smart cities, urbanization and the car sharing economy all present challenges in a fast-changing environment which the automotive industry must adapt to. Cars no longer are just standalone systems, but have become constituent systems (CS) in larger System of Systems (SoS) context. This is reflected in the emergence of several acronyms such as vehicle-to-everything (V2X), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-grid (V2G) expressions. System of Systems are defined systems of interest whose elements (constituent systems) are managerially and operationally independent systems. This interoperating and/or integrated collection of constituent systems usually produce results unachievable by the individual systems alone, for example the use of car batteries as virtual power plants.

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.