Search Results

Exterior component integration presents competing performance challenges for balanced exterior styling, safety, ‘structural feel’ [1] and durability. Industry standard practices utilize noise and vibration mode maps and source-path-receiver [2] considerations for component mode frequency placement. This modal frequency placement has an influence on ‘structural feel’ and durability performance. Challenges have increased with additional styling content, geometric overhang from attachment points, component size and mass, and sensor modules. Base excitation at component attachment interfaces are increase due to relative positioning of the suspension and propulsion vehicle source inputs. These components might include headlamps, side mirrors, end gates, bumpers and fascia assemblies. Here, we establish basic expectations for the behavior of these systems, and ultimately consolidate existing rationales that are applied to these systems.

Churning loss is an important energy loss term for rolling bearings at high-speed condition. However, it is quite challenging to accurately calculate the churning loss. A CFD study based on unsteady Reynolds-Averaged-Navier-Stokes that resolves the gas-liquid interface was performed to examine the unsteady multiphase flow in a roller/ball bearing. In this study, the rotating motion of the cage, races, rollers/balls about the shaft as well as self-rotation of rollers/balls about their own axis were accounted to accurately predict the oil distribution in various parts of the bearings. A novel meshing strategy is presented to resolve thin gaps between the roller/balls and the races/cage while preserving the shape of balls/rollers, races and cage. Five rotational speeds of the shaft have been examined for roller bearing and ball bearing respectively. Additionally, effect of clearance between roller/balls and races is investigated.

Fretting is an important phenomenon that happens in many mechanical parts. It is the main reason in deadly failures in automobiles, airliners, and turbine engines. The damage is noticed between two surfaces clamped together by bolts or rivets that are nominally at rest, but have a small amplitude oscillation because of vibration or local cyclic loading. Fretting damage can be divided into two types. The first type is the fretting fatigue damage where a crack would initiate and propagate at specific location at the interface of the mating surfaces. Cracks usually initiate in the material with lower strength because of the local cyclic loading conditions which eventually lead to full failure. The second type is the fretting wear damage because of external vibration. Researchers have investigated this phenomenon by theoretical modeling and experimental approaches. Although a lot of research has been done on fretting damage, some of the parameters have not been well studied.

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.

Model-based control system design improves quality, shortens development time, lowers engineering cost, and reduces rework. Evaluating a control system's performance, functionality, and robustness in a simulation environment avoids the time and expense of developing hardware and software for each design iteration. Simulating the performance of a design can be straightforward (though sometimes tedious, depending on the complexity of the system being developed) with mathematical models for the hardware components of the system (plant models) and control algorithms for embedded controllers. This paper describes a software tool and a methodology that not only allows a complete system simulation to be performed early in the product design cycle, but also greatly facilitates the construction of the model by automatically connecting the components and subsystems that comprise it.

In a hydraulic system, parameter variation, contamination, and/or operating conditions can lead to instabilities in the pressure response. The resultant erratic pressure profile reduces performance and can lead to hardware damage. Specifically, in a transmission control system, the inability to track pressure commands can result in clutch or variator slip which can cause driveline disturbance and/or hardware damage. A variator is highly sensitive to slip and therefore, it is advantageous to identify such pressure events quickly and take remedial actions. The challenge is to detect the condition in the least amount of time while minimizing false alarms. A Neyman-Pearson and an energy detector (based on auto-correlation) are evaluated for the detection of pressure disturbances. The performance of the detectors is measured in terms of speed of detection and robustness to measurement noise.

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 use of automated test tools for automotive ECU development has been increasing in recent years, in particular for software testing, system validation and verification, and regression testing. One of the challenges for the ECU development community is that test cases created at a specific phase of software development cannot be easily re-used upstream or downstream in the development process. For example, test cases developed for a model-in-the-loop (MiL) test environment can not be easily re-used on a hardware-in-the-loop (HiL) tests system. This results in significant costs associated with re-engineering test cases and/or poor software quality. At ETAS, we understand that a critical aspect of test case design is the ability to share and re-use test scripts on different HiL hardware platforms and across different development environments (e.g. MiL, SiL, and HiL).

The Lockheed Martin Low-Speed Wind Tunnel (LSWT) is a closed-return wind tunnel with two solid-wall test sections. This facility originally entered into service in 1967 for aerodynamic research of aircraft in low-speed and vertical/short take-off and landing (V/STOL) flight. Since this time, the client base has evolved to include a significant level of automotive aerodynamic testing, and the needs of the automotive clientele have progressed to include acoustic testing capability. The LSWT was therefore acoustically upgraded in 2016 to reduce background noise levels and to minimize acoustic reflections within the low-speed test section (LSTS). The acoustic upgrade involved detailed analysis, design, specification, and installation of acoustically treated wall surfaces and turning vanes in the circuit as well as low self-noise acoustic wall and ceiling treatment in the solid-wall LSTS.

In today’s race for improved fuel economy and lower emissions from gasoline engines, precise metering of delivered fuel is essential. Gasoline Direct Injection fuel systems provide the means for improved combustion efficiency through mixture preparation and better atomization. These improvements can be achieved from both increasing fuel pressure and using multiple injection events, which significantly reduce the required energizing time per injection, and in a number of cases, force the injector to operate at less than full stroke. When the injector operates in this condition, the influence of variation in injector dynamics account for a large percentage of the delivered fuel and require compensation to ensure accurate fuel delivery. Injector dynamics such as opening delay and closing time are influenced by operating conditions such as fuel pressure, energizing time, and temperature.

Market demands for increased fuel economy and reduced emissions are placing higher aerodynamic and thermal analysis demands on vehicle designers and engineers. These analyses are usually carried out by different engineering groups in different parts of the design cycle. Design changes required to improve vehicle aerodynamics often come at the price of part thermal performance and vice versa. These design changes are frequently a fix for performance issues at a single performance point such as peak power, peak torque, or highway cruise. In this paper, the motivation for a holistic approach in the form of multi-disciplinary optimization (MDO) early in the design process is presented. Using a Response-surface Informed Transient Thermal Model (RITThM) a vehicle's thermal performance through a drive cycle is predicted and correlated to physical testing for validation.

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.

In the recent decades, tremendous effort has been made in automotive industry to reduce vehicle mass and development costs for the purpose of improving fuel economy and building safer vehicles that previous generations of vehicles cannot match. An accurate modeling approach of sheet metal fracture behavior under plastic deformation is one of the key parameters affecting optimal vehicle development process. FLD (Forming Limit Diagram) approach, which plays an important role in judging forming severity, has been widely used in forming industry, and localized necking is the dominant mechanism leading to fracture in sheet metal forming and crash events. FLD is limited only to deal with the onset of localized necking and could not predict shear fracture. Therefore, it is essential to develop accurate fracture criteria beyond FLD for vehicle development.

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 main objective of crash sensing is to predict a vehicle collision early in the event and command vehicle’s occupant protection systems to take appropriate actions to reduce the severity of crash injury. Currently Computer Aided Engineering (CAE) models are being used to predict the sensing signals with sensors placed at front end structure of the vehicle. The front-end structure as well as other critical components packaged in the front end play important role in absorbing energy and provide sensing signals during impact, headlamp being one such critical components. The headlamp with its lens being the exterior surface, experience large magnitude of loads from barrier during full frontal, angled and offset impact. The impact with barrier usually results in scattered damage to the headlamp and its lens. In this paper, CAE model of headlamp has been improved to reflect similar deformation pattern as observed in physical tests.

Stochastic Preignition (SPI) is an abnormal combustion event that occurs in a turbocharged engine and can lead to the loss in fuel economy and engine hardware damage, and in turn result in customer dissatisfaction. It is a significant limiting factor on the use and continued downsizing of turbocharged spark ignited direct injection (SIDI) gasoline engines. Understanding and mitigating all the factors that cause and influence the rate and severity of SPI occurrence are of critical importance to the engine’s continued use and fuel economy improvements for future designs. Previous studies have shown that the heavy molecular weight components of the fuel formulations are one factor that influences the rate of SPI from a turbocharged SIDI gasoline engine. All the previous studies have involved analyzing the fuel’s petroleum hydrocarbon chemistry, but not specifically the additives that are put in the fuel to protect and clean the internal components over the life of the engine.

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.

In today's competitive market, noise and vibration are among the most important parameters that impact the success of a vehicle. In body-on-frame construction vehicles, elastomeric body mounts play a major role in isolating the passenger compartment from road noise, harshness, shake, and other vibrations in the chassis as well as improving ride quality across a wide frequency range. This paper describes the work carried out to design a fluid filled mount with high lateral stiffness that can alter the perceived Noise, Vibration and Harshness (NVH) performance of current production body-on-frame trucks. It was found that the quietness and ride qualities can be significantly improved by positioning the glycol-filled mounts at the anti-node of the frame first vertical bending mode; under the C-pillar intersection with the frame. The performance of mounts in this area is known to be critical to ride quality.

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.