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This paper describes Programmed Ride Control (PRC), the automatic adjustable shock absorber system designed and patented by Ford Motor Company. The system utilizes low shock absorber damping under normal driving conditions to provide soft boulevard ride, automatically switching to firm damping when required for improved handling. The system's microprocessor control module “learns” where the straight ahead steering wheel position is, allowing the system to respond to absolute steering wheel angle. A closed loop control strategy is used to improve system reliability and to notify the driver in the event of a system malfunction. Fast acting rotary solenoids control the damping rate of the shock absorbers.

The main objective of the current paper was to investigate the fluid flow and pressure loss characteristics of DPF substrates with asymmetric channels utilizing 3-D Computational Fluid Dynamics (CFD) methods. The ratio of inlet to outlet channel width is 1.2. First, CFD results of velocity and static pressure distributions inside the inlet and outlet channels are discussed for the baseline case with both forward and reversed exhaust flow. Results were also compared with the regular DPF of same cell structure and wall material properties. It was found that asymmetrical channel design has higher pressure loss. The lowest pressure loss was found for the asymmetrical channel design with smaller inlet channels. Then, the effects of DPF length and filter wall permeability on pressure loss, flow and pressure distributions were investigated.

This paper reports on the injuries to the head, neck and thorax of fifteen child surrogates, subjected to varying levels of sudden acceleration. Measured response data in the child surrogate tests and in matched tests with a three-year-old child test dummy are compared to the observed child surrogates injury levels to develop preliminary tolerance data for the child surrogate. The data are compared with already published data in the literature.

Flame speed data reported in most literature are acquired in conventional apparatus such as the spherical combustion bomb and counterflow burner, and are limited to atmospheric pressure and ambient or slightly elevated unburnt temperatures. As such, these data bear little relevance to internal combustion engines and gas turbines, which operate under typical pressures of 10-50 bar and unburnt temperature up to 900K or higher. These elevated temperatures and pressures not only modify dominant flame chemistry, but more importantly, they inevitably facilitate pre-ignition reactions and hence can change the upstream thermodynamic and chemical conditions of a regular hot flame leading to modified flame properties. This study focuses on how auto-ignition chemistry affects flame propagation, especially in the negative-temperature coefficient (NTC) regime, where dimethyl ether (DME), n-heptane and iso-octane are chosen for study as typical fuels exhibiting low temperature chemistry (LTC).

This paper reports the analytical procedure developed for a simulation of knee impact during a barrier crash using a hybrid III dummy lower torso. A finite element model of the instrument panel was generated. The dummy was seated in mid-seat position and was imparted an initial velocity so that the knee velocity at impact corresponded to the secondary impact velocity during a barrier crash. The procedure provided a reasonably accurate simulation of the dummy kinematics. This simulation can be used for understanding the knee bolster energy management system. The methodology developed has been used to simulate impact on knee for an occupant belted or unbelted in a frontal crash. The influence of the vehicle interior on both the dummy kinematics and the impact locations was incorporated into the model. No assumptions have been made for the knee impact locations, eliminating the need to assume knee velocity vectors.

Motor vehicle crashes involving child Vulnerable Road Users (VRUs) remain a critical public health concern in the United States. While previous studies successfully utilized the crash scenario typology to examine traffic crashes, these studies focus on all types of motor vehicle crashes thus the method might not apply to VRU crashes. Therefore, to better understand the context and causes of child VRU crashes on the U.S. road, this paper proposes a multi-step framework to define crash scenario typology based on the Fatality Analysis Reporting System (FARS) and the Crash Report Sampling System (CRSS). A comprehensive examination of the data elements in FARS and CRSS was first conducted to determine elements that could facilitate crash scenario identification from a systematic perspective. A follow-up context description depicts the typical behavioral, environmental, and vehicular conditions associated with an identified crash scenario.

Tubular hydroforming is a novel process that has recently gained much attention due to its cost-effective application in the automotive industry. Hydroformed automotive parts have high strength to weight ratio and have good repeatability with high dimensional accuracy. At this time, there is little experience in modeling the hydroforming process to better understand its application and researchers have tried using stamping simulation software to analyze the process. Unlike conventional sheet stamping which is a displacement driven process, tubular hydroforming is a force driven process and its success is governed by the nature of internal pressurization. Hence, a new three-dimensional finite element model using a computationally efficient 6-noded shell element has been developed. A simple pressure prediction model has been developed and integrated into the formulation for effective control of the process.

Although there was a safety awareness from the earliest days of the automobile, systematic approaches to designing for safety became more widespread after 1950 when large numbers of vehicles came into use in both the United States and Europe, and governments in both continents undertook a widespread highway development. Industry response to safety objectives and also to government regulation has produced a large number of safety enhancing engineering developments, including radial tires, disc brakes, anti-lock brakes, improved vehicle lighting systems, better highway sign support poles, padded instrument panels, better windshield retention systems, collapsible hood structures, accident sensitive fuel pump shut-off valves, and other items. A significant development was the design of the energy absorbing front structures.

In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).

Research in any field of study requires analysis and comparisons or real-time predictions to extract useful information. To prove that the results have practical potential, various filtering techniques and methodologies should be designed and implemented. Filters being a class of signal processing helps innovate new technologies with various kinds of outcomes, using filters there are always various methods to solve a problem. Considering the current COVID-19 situation, researchers are working on sequencing the novel coronavirus and the genomes of people afflicted with COVID-19 using CPUs and GPUs along with various filtering techniques. In this paper we are using a method of filter implementation to collect raw heart rate data samples from fingertip and ear lobe and process those results on CPUs and GPUs. Our method of implementation to collect raw heart rate data is using a photoplethysmography method.

Real-time measurement or estimation of crank-angle-resolved engine cylinder pressure may become commonplace in the next generation of engine controllers to optimize spark, valve timing, or compression ratio. Toward the development of a real-time cylinder pressure estimator, this work presents a crank-angle-resolved engine cylinder pressure estimation model that could accept inputs such as speed, manifold pressure and throttle position, and deliver crank-angle resolved cylinder pressure in real-time, at engine speeds covering the useful operating range of most engines. The model was validated by comparing simulated cylinder pressure with thirteen sets of cylinder pressure data, from two different commercial engines from two different OEMs. Estimated pressures were compared against the actual measured pressure traces. The average relative error is about 3% while the maximum relative error is 5%. Both can be improved with further tuning.

This work analyzes a cantilevered piezoelectric beam device for harvesting energy from the simultaneous rotation and translational vibration of vehicle wheels. The device attaches to the wheel rim so that it displaces tangentially during operation. A lumped-parameter analytical model for the coupled electromechanical system is derived. The device has one natural frequency that is speed-dependent because of centripetal acceleration affecting the total stiffness of the device. Even though the device has one natural frequency, it experiences three resonances as the rotation speed varies. One resonance occurs when the rotation speed coincides with the speed-dependent natural frequency of the device. The other two resonances are associated with excitations from the vibration of the vehicle wheel. The device’s parameters are chosen so that these three resonances occur when the wheel travels near 30 mph, 55 mph, and 70 mph.

The reach capability of drivers is currently represented in vehicle design practice in two ways. The SAE Recommended Practice J287 presents maximum reach capability surfaces for selected percentiles of a generic driving population. Driver reach is also simulated using digital human figure models. In typical applications, a family of figure models that span a large range of the target driver population with respect to body dimensions is positioned within a digital mockup of the driver's workstation. The articulated segments of the figure model are exercised to simulate reaching motions and driver capabilities are calculated from the constraints of the kinematic model. Both of these current methods for representing driver reach are substantially limited. The J287 surfaces are not configurable for population characteristics, do not provide the user with the ability to adjust accommodation percentiles, and do not provide any guidance on the difficulty of reaches that are attainable.

Since road roughness is an important source of vehicle vibration, a system model for NVH analysis requires a tire model which accurately predicts spindle response to road input. Most tire models currently used in the auto industry do not meet this requirement, because they are based on static stiffness of the tire and do not produce realistic response to input at the patch. This paper investigates a new modal tire model with patch input capability as a component within a vehicle system model. Comparisons are also presented between the behavior of the new tire model and a conventional spring model. To validate the performance of the tire model for NVH analysis, simulated vehicle responses to bump input are compared to chassis roll test results. Good correlation between the model prediction and the chassis roll measurements is observed.

This paper presents a new transient passenger thermal comfort model. The model uses as inputs the vehicle environmental variables: air temperature, air velocity, relative humidity and mean radiant temperature all of which can vary as a function of time and space. The model also uses as inputs the clothing level and the initial physiological state of the body. The model then predicts as a function of time the physiological state of the body and an effective human thermal sensation response (e.g. cold, comfort, hot, etc.). The advantage of this model is that it can accurately predict the human thermal sensation response during transient vehicle warm-up and cooldown conditions. It also allows design engineers the ability to conduct parametric studies of climate control systems before hardware is available. Here we present the basis of the new thermal comfort model and its predictions for transient warm-up and cooldown conditions.

An analytical model based on “vortex sound” theory was investigated for predicting the frequency, the relative magnitude, the onset, and the offset of self-sustained interior pressure fluctuations inside a vehicle with an open sunroof. The “buffeting” phenomenon was found to be caused by the flow-excited resonance of the cavity. The model was applied to investigate the optimal sunroof length and width for a mid-size sedan. The input parameters are the cavity volume, the orifice dimensions, the flow velocity, and one coefficient characterizing vortex diffusion. The analytical predictions were compared with experimental results obtained for a system which geometry approximated the one-fifth scale model of a typical vehicle passenger compartment with a rectangular, open sunroof. Predicted and observed frequencies and relative interior pressure levels were in good agreement around the “critical” velocity, at which the cavity response is near resonance.

New vehicle control algorithms are needed to meet future emissions and fuel economy mandates that are quite likely to require a measurement of ambient specific humidity (SH). Current practice is to obtain the SH by measurement of relative humidity (RH), temperature and barometric pressure with physical sensors, and then to estimate the SH using a fit equation. In this paper a novel approach is described: a system of neural networks trained to estimate the SH using data that already exists on the vehicle bus. The neural network system, which is referred to as a virtual SH sensor, incorporates information from the global navigation satellite system such as longitude, latitude, time and date, and from the vehicle climate control system such as temperature and barometric pressure, and outputs an estimate of SH. The conclusion of this preliminary study is that neural networks have the potential of being used as a virtual sensor for estimating ambient and intake manifold's SH.

A nonlinear finite element passenger car radial-ply tire model was developed to investigate a tire's three-dimensional transmissibility in the X, Y, and Z directions. The reaction forces of the tire axle in longitudinal (X axis), lateral (Y axis), and vertical (Z axis) directions were recorded when the tire encountered a cleat, and then the FFT (Fast Fourier Transform) algorithm was applied to extract tire's transient response information in the frequency domain. The result showed that this passenger car tire has clear peaks at 47-51 and 91-92 Hz longitudinal, 41-45 Hz lateral, and 80-83Hz vertical. An analytical rigid ring model was also formulated, based on the dynamic equations of the rigid ring tire model. The characteristic equations were obtained and solved for eigenvalues and eigenvectors, which represent tire's free vibration natural frequencies and mode shapes.

About 10 years ago in the US, an automotive OEM consortium formed the Oxygenated Fuels Task Force which in turn created the SAE Cooperative Research Project Group 2 to develop a simple rational method for qualifying materials. At that time the focus was Methanol/Gasoline blends. This work resulted in SAE J1681, Gasoline/Methanol Mixtures for Materials Testing. Recently this document was rewritten to make it the single, worldwide, generic source for fuel system test fluids. The paper will describe the rationale for selecting the fuel surrogate fluids and why this new SAE standard should replace all existing test fuel or test fluid standards for fuel system materials testing.

Shearography has been proved to be highly effective for nondestructive testing (NDT), especially for NDT of composite materials used in the automotive and aerospace engineering. While its application in material testing and material research has already achieved more and more acceptance in research and industry, its applications are mainly limited to the inspection and testing of an object surface which can directly be observed by a shearographic camera. Its application is mainly limited to inspect and test an object surface which can directly be observed by a shearographic camera. It is impossible to inspect an internal surface of a container. If the reflected light of the surface, which has to be examined, can’t reach the shearographic camera there is still no inspection possible. This paper presents the development of a rigid shearographic endoscope. The development enabled shearographic inspection on both external and internal surfaces of objects.