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The comfort assessment of seats in the automotive industry has historically been accomplished by subjective ratings. This approach is expensive and time consuming since it involves multiple prototype seats and numerous people in supporting processes. In order to create a more efficient and robust method, objective metrics must be developed and utilized to establish measurable boundaries for seat performance. Objective measurements already widely accepted, such as IFD (Indentation Force Deflection) or CFD (Compression Force Deflection) [1], have significant shortcomings in defining seat comfort. The most obvious deficiency of these component level tests is that they only deal with a seats' foam rather than the system response. Consequently, these tests fail to take into account significant factors that affect seat comfort such as trim, suspension, attachments and other components.

The importance of achieving good (low) assembled lateral runout of the brake disc is well recognized in the industry - it is a critical feature for avoiding issues such as wear-induced disc thickness variation and vibration/shudder during braking. Significant efforts and expense has been invested by the industry into reducing disc brake lateral runout. However, wheel assemblies also have some inherent runout, which in turn cause cyclical forces to act on the brake corner during vehicle movement. Despite the stiffness of the wheel bearing (which aligns the brake disc with the caliper and knuckle), these “tire non-uniformity” forces can be sufficient to promote deflection of the assembly that is appreciable compared to typical disc lateral runout tolerances. This paper covers measurements of this phenomenon on three different vehicles (compact, mid-size, and large cars), under a variety of operating conditions such as speed, wheel assembly runout, and wheel assembly balance.

Twist spring-back would interfere with stamping or assembling procedures for advanced high strength steel. A “homeopathic” resolution for controlling the twist spring-back is proposed using unbalanced post-stretching configuration. Finite element forming simulation is applied to evaluate and compare the performance for each set of unbalanced post-stretching setup. The post-stretching is effectuated by stake bead application. The beads are separated into multiple independent segments, the height and radii of which can be adjusted individually and asymmetrically. Simulation results indicate that the twist spring-back can be effectively controlled by reducing the post-stretching proximate to the asymmetric part area. Its mechanism is qualitatively revealed by stress analyses, that an additional but acceptable cross-sectional spring-back re-balances the sprung asymmetrical geometry to counter the twist effect.

In electric vehicle applications, the majority of the traction motors can be categorized as Permanent Magnet (PM) motors due to their outstanding performance. As indicated in the name, there are strong permanent magnets used inside the rotor of the motor, which interacts with the stator and causes strong magnetic pulling force during the assembly process. How to estimate this magnetic pulling force can be critical for manufacturing safety and efficiency. In this paper, a full 3D magnetostatic model has been proposed to calculate the baseline force using a dummy non-slotted cylinder stator and a simplified rotor for less meshing elements. Then, the full 360 deg model is simplified to a half-pole model based on motor symmetry to save the simulation time from 2 days to 2 hours. A rotor position sweep was conducted to find the maximum pulling force position. The result shows that the max pulling force happens when the rotor is 1% overlapping with the stator core.

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.

The human-robot interaction (HRI) is involved in a lift assistant system of manufacturing assembly line. The admittance model is applied to control the end effector motion by sensing intention from force of applied by a human operator. The variable admittance including virtual damping and virtual mass can improve the performance of the systems. But the tuning process of variable admittance is un-convenient and challenging part during the real test for designers, while the offline simulation is lack of learning process and interaction with human operator. In this paper, the Iterative learning algorithm is proposed to emulate the human learning process and facilitate the variable admittance control design. The relationship between manipulate force and object moving speed is demonstrated from simulation data. The effectiveness of the approach is verified by comparing the simulation results between two admittance control strategies.

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.

The amount of acidic material in used engine oil is considered an indicator of the remaining useful life of the oil. Total acid number, determined by titration, is the most widely accepted method for determining acidic content but the method is not capable of speciation of individual acids. In this work, high molecular weight residue was isolated from used engine oil by dialysis in heptane. This residue was then analyzed using pyrolysis-comprehensive two dimensional gas chromatography with time-of-flight mass spectrometry. Carboxylic acids from C2-C18 were identified in the samples with acetic acid found to be the most abundant. This identification provides new information that may be used to improve the current acid detection methodologies for used engine oils.

The General Motors Reduced Scale Wind Tunnel Facility, which came into operation in the fall of 2015, is a new state-of-the-art scale model aerodynamic test facility that expands GM’s test capabilities. The new facility also increases GM’s aerodynamic testing through-put and provides the resources needed to achieve the growing demand for higher fuel economy requirements for next generation of vehicles. The wind tunnel was designed for a nominal model scale of 40%. The nozzle and test section were sized to keep wind tunnel interference effects to a minimum. Flow quality and other wind tunnel performance parameters are on par with or better than the latest industry standards. A 5-belt system with a long center belt and boundary layer suction and blowing system are used to model underbody flow conditions. An overhead probe traverse system is installed in the test section along with a model positioning robot used to move the model in an out of the test section.

The implementation of electronic shifters (e-shifter) for automatic transmissions in vehicles has created many new opportunities for the customer facing transmission interface and in-vehicle packaging. E-shifters have become popular in recent years as their smaller physical size leads to packaging advantages, they reduce the mass of the automatic transmission shift system, they are easier to install during vehicle assembly, and act as an enabler for autonomous driving. A button-style e-shifter has the ability to create a unique customer interface to the automatic transmission, as it is very different from the conventional column lever or linear console shifter. In addition to this, a button-style e-shifter can free the center console of valuable package space for other customer-facing functions, such as storage bins and Human-Machine Interface controllers.

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.

This paper proposes a model-based “Cascaded Dual Extended Kalman Filter” (CDEKF) for combined vehicle state estimation, namely, tire vertical forces and parameter identification. A sensitivity analysis is first carried out to recognize the vehicle inertial parameters that have significant effects on tire normal forces. Next, the combined estimation process is separated in two components. The first component is designed to identify the vehicle mass and estimate the longitudinal forces while the second component identifies the location of center of gravity and estimates the tire normal forces. A Dual extended Kalman filter is designed for each component for combined state estimation and parameter identification. Simulation results verify that the proposed method can precisely estimate the tire normal forces and accurately identify the inertial parameters.