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This study evaluates utilizing an accelerated test method that correlates customer interaction with a vehicle seat where bagginess and wrinkling is produced. The evaluation includes correlation from warranty returns as well as test vehicle results for test verification. Consumer metrics will be discussed within this paper with respect to potential application of this test method, including but not limited to JD Power ratings. The intent of the test method is to aid in establishing appropriate design parameters of the seat trim covers and to incorporate appropriate design measures such as tie downs and lamination. This test procedure was utilized in a Design for Six Sigma (DFSS) project as an aid in optimizing seat parameters influencing trim cover performance using a Design of Experiment approach. Presenter Lisa Fallon, General Motors LLC

This paper presents the design development of a SUV liftgate with the intention of minimizing low frequency noise. Structure topology optimization techniques were applied both to liftgate and body FEA models to reduce radiated power from the liftgate inner surface. Topology results are interpreted into structural changes to the original liftgate and body design. Favorable results of equivalent radiated power (ERP) performance with reduced cost and mass is shown compared to baseline liftgate and baseline with tuned vibration absorber (TVA). This simulation includes finite element modeling of coupled fluid/structure interaction between the interior air cavity volume and liftgate structure. In addition to ERP minimization, multi-model optimization (MMO) was used on separate models simultaneously to preserve liftgate structural performance for several customer usage load cases.

This article covers an application of third-generation advanced high-strength steel (3GAHSS) grades to vehicle lightweight body structure development. Design optimization of a vehicle body structure using a multi-scale material model is discussed. The steps in the design optimization and results are presented. Results show a 30% mass reduction potential over a baseline mid-size sedan body side structure with the use of 3GAHSS.

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.

The purge pump is used to pull evaporative gases from canister and send to engine for combustion in Turbocharged engines. The purge pump with impeller at one end and electric motor at the other end is supported by the ball bearing assembly. A bearing kinematic model to predict forcing function due to defect in ball bearing arrangement, coupled with bearing dynamic model of rotor because of rotating component, is proposed in this paper to get accumulated effect on transmitted force to the purge pump housing. Rotor dynamic of purge pump rotor components only produces certain order forcing responses which can be simulated into the multibody software environment, knowing the ball bearing geometry parameters hence providing stiffness parameter for rotor system.

Modeling and simulation are crucial in the development of advanced energy efficient control strategies. Utilizing real-world driving data as the underlying basis for control design and simulation lends veracity to projected real-world energy savings. Standardized drive cycles are limited in their utility for evaluating advanced driving strategies that utilize connectivity and on-vehicle sensing, primarily because they are typically intended for evaluating emissions and fuel economy under controlled conditions. Real-world driving data, because of its scale, is a useful representation of various road types, driving styles, and driving environments. The scale of real-world data also presents challenges in effectively using it in simulations. A fast and efficient simulation methodology is necessary to handle the large number of simulations performed for design analysis and impact evaluation of control strategies.

The market for electric vehicles and hybrid electric vehicles is expected to grow in the coming years, which is increasing interest in design optimization of electric motors for automotive applications. Under demanding duty cycles, the moving part within a motor, the rotor, may experience varying stresses induced by centrifugal force, a necessary condition for fatigue. Rotors contain hundreds of electrical steel laminations produced by stamping, which creates a characteristic edge structure comprising rollover, shear and tear zones, plus a burr. Fatigue properties are commonly reported with specimens having polished edges. Since surface condition is known to affect fatigue strength, an experiment was conducted to evaluate the effect of sample preparation on tensile and fatigue behavior of stamped specimens. Tensile properties were unaffected by polishing. In contrast, polishing was shown to increase fatigue strength by approximately 10-20% in the range of 105-107 cycles to failure.

Disc brakes operate with very close proximity of the brake pads and the brake rotor, with as little as a tenth of a millimeter of movement of the pads required to bring them into full contact with the rotor to generate braking torque. It is usual for a disc brake to operate with some amount of residual drag in the fully released state, signifying constant contact between the pads and the rotor. With this contact, every miniscule movement of the rotor pushes against the brake pads and changes the forces between them. Sustained loads on the brake corner, and maneuvers such as cornering, can both produce rotor movement relative to the caliper, which can push it steadily against one or both of the brake pads. This can greatly increase the residual force in the caliper, and increase drag. This dependence of drag behavior on the movement of the brake rotor creates some vehicle-dependent behavior.

The Hybrid Cellular Automaton (HCA) algorithm is a generative design approach used to synthesize conceptual designs of crashworthy vehicle structures with a target mass. Given the target mass, the HCA algorithm generates a structure with a specific acceleration-displacement profile. The extended HCA (xHCA) algorithm is a generalization of the HCA algorithm that allows to tailor the crash response of the vehicle structure. Given a target mass, the xHCA algorithm has the ability to generate structures with different acceleration-displacement profiles and target a desired crash response. In order to accomplish this task, the xHCA algorithm includes two main components: a set of meta-parameters (in addition target mass) and surrogate model technique that finds the optimal meta-parameter values. This work demonstrates the capabilities of the xHCA algorithm tailoring acceleration and intrusion through the use of one meta-parameter (design time) and the use of Kriging-assisted optimization.

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.

Hybrid high voltage battery pack is not only heavy mass but also large in dimension. It interacts with the vehicle through the battery tray. Thus the battery tray is a critical element of the battery pack that interfaces between the battery and the vehicle, including the performances of safety/crash, NVH (modal), and durability. The tray is the largest and strongest structure in the battery pack holding the battery sections and other components including the battery disconnect unit (BDU) and other units that are not negligible in mass. This paper describes the mass optimization work done on one of the hybrid batteries using CAE simulation. This was a multidisciplinary optimization project, in which modal performance and fatigue damage were accessed through CAE analysis at both the battery pack level, and at the vehicle level.

Styrene-Butadiene Rubber (SBR), a copolymer of butadiene and styrene, is widely used in the automotive industry due to its high durability and resistance to abrasion, oils and oxidation. Some of the common applications include tires, vibration isolators, and gaskets, among others. This paper characterizes the dynamic behavior of SBR and discusses the suitability of a visco-elastic model of elastomers, known as the Kelvin model, from a mathematical and physical point of view. An optimization algorithm is used to estimate the parameters of the Kelvin model. The resulting model was shown to produce reasonable approximations of measured dynamic stiffness. The model was also used to calculate the self heating of the elastomer due to energy dissipation by the viscous damping components in the model. Developing such a predictive capability is essential in understanding the dynamic behavior of elastomers considering that their dynamic stiffness can in general depend on temperature.

The paper presents the main results of a study on the simulation of energy efficient management of on-board electric and thermal systems for a medium-size passenger vehicle featuring a parallel-hybrid diesel powertrain with a high-voltage belt alternator starter. A set of advanced technologies has been considered on the basis of very aggressive fuel economy targets: base-engine downsizing and friction reduction, combustion optimization, active thermal management, enhanced aftertreatment and downspeeding. Mild-hybridization has also been added with the goal of supporting the downsized/downspeeded engine performance, performing energy recuperation during coasting phases and enabling smooth stop/start and acceleration. The simulation has implemented a dynamic response to the required velocity and manual gear shift profiles in order to reproduce real-driver behavior and has actuated an automatic power split between the Internal Combustion Engine (ICE) and the Electric Machine (EM).

Stamped components play an important role in supporting various sub-systems within a typical engine and transmission assembly. In some cases, the stamped components will not initially meet the design criteria, and material may need to be added to strengthen it. However, in other cases the component may be overdesigned, and there will be opportunities to reduce mass while still meeting all design criteria. In this latter case, multiple CAE simulations are often performed to enhance the component design by varying design parameters such as thickness, bend radius, material, etc., The conventional process will assess changes in one parameter at a time, while holding other parameters constant. Though this helps in meeting the design criteria, it is often very difficult to produce the best optimized design within the limited time span with this approach. With the aid of Altair-HyperMorph techniques, multiple design parameters can be varied simultaneously.

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.

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.

Torque ripple of electric motors is a unique feature in Battery Electric Vehicles (BEV) affecting vehicle performance. It is one of the disturbances from electric motors resulting in unpleasant vehicle fore-aft vibrations at specific vehicle speeds. In this study, the torque ripple modeling and simulation procedure has been developed. Critical modeling contents in a full vehicle ADAMS model and a brief overview of the propulsion control are described. Analytical data sets for torque fluctuations (torque ripple) from a couple of different sources are incorporated in the model. The CAE simulation procedure was applied to simulate vehicle performances of a General Motors Battery Electric Vehicle in an early vehicle design phase. Torque ripple phenomena are simulated both in an open-loop and closed-loop propulsion control environment to see how much vehicle fore-aft vibration suppression is achieved by the motor control methods.

Multi-core systems are promising a cost-effective solution for (1) advanced vehicle features requiring dramatically more software and hence an order of magnitude more processing power, (2) redundancy and mixed-IP, mixed-ASIL isolation required for ISO 26262 functional safety, and (3) integration of previously separate ECUs and evolving embedded software business models requiring separation of different software parts. In this context, designing, optimizing and verifying the mapping and scheduling of software functions onto multiple processing cores becomes key. This paper describes several multi-core task design and scheduling design options, including function-to-task mapping, task-to-core allocation (both static and dynamic), and associated scheduling policies such as rate-monotonic, criticality-aware priority assignment, period transformation, hierarchical partition scheduling, and dynamic global scheduling.

Torque ripple from electric motor can excite a system resonance perceived as vibration at the vehicle seat track. The CAE simulation procedure was applied to analyze the seat track acceleration excited by electric motor torque ripple. In this study, the transfer function between the electric motor torque and vehicle level seat track acceleration was developed, and it incorporates the control capability and vehicle sensitivity subfunctions. The motor level torque ripple requirement was developed, which can support motor design in early vehicle development stage based on vehicle level criteria. The analysis results obtained for motor level torque ripple requirement shows good agreement with the experimental validation using vehicle test data. The variation study on control capability and vehicle sensitivity was investigated, and the results can help to identify the solution to improve vehicle torque ripple response.

Due to the limitations on resistance spot welding of ultra-thin steel sheet (thicknesses below 0.5 mm) in high-volume automotive manufacturing, a comparison of friction stir spot welding and self-piercing riveting was performed to determine which process may be more amenable to enabling assembly of ultra-thin steel sheet. Statistical comparisons between mechanical properties of lap-shear tensile and T-peel were made in sheet thickness below 0.5 mm and for dissimilar thickness combinations. An evaluation of energy to fracture, fracture mechanisms, and joint consistency is presented.