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The objective of this paper focused on the modeling of an adaptive energy absorbing steering column which is the first phase of a study to develop a modeling methodology for an advanced steering wheel and column assembly. Early steering column designs often consisted of a simple long steel rod connecting the steering wheel to the steering gear box. In frontal collisions, a single-piece design steering column would often be displaced toward the driver as a result of front-end crush. Over time, engineers recognized the need to reduce the chance that a steering column would be displaced toward the driver in a frontal crash. As a result, collapsible, detachable, and other energy absorbing steering columns emerged as safer steering column designs. The safety-enhanced construction of the steering columns, whether collapsible, detachable, or other types, absorb rather than transfer frontal impact energy.

This paper presents the final phase of a study to develop the modeling methodology for an advanced steering assembly with a safety-enhanced steering wheel and an adaptive energy absorbing steering column. For passenger cars built before the 1960s, the steering column was designed to control vehicle direction with a simple rigid rod. In severe frontal crashes, this type of design would often be displaced rearward toward the driver due to front-end crush of the vehicle. Consequently, collapsible, detachable, and other energy absorbing steering columns emerged to address this type of kinematics. These safety-enhanced steering columns allow frontal impact energy to be absorbed by collapsing or breaking the steering columns, thus reducing the potential for rearward column movement in severe crashes. Recently, more advanced steering column designs have been developed that can adapt to different crash conditions including crash severity, occupant mass/size, seat position, and seatbelt usage.

This paper proposes an approach that characterizes a driver's driving behavior and style in real-time during car-following drives. It uses an online learning of the evolving Takagi-Sugeno fuzzy model combined with the Markov model. The inputs fed into the proposed algorithm are from the measured signals of on-board sensors equipped with current vehicles, including the relative distance sensors for Adaptive Cruise Control feature and the accelerometer for Electronic Stability Control feature. The approach is verified using data collected using a test vehicle from several car-following test trips. The effectiveness of the proposed approach has been shown in the paper.

This paper proposes an approach to use ABS wheel speed sensor signals together with other vehicle state information from a brake control module to detect an unbalanced tire or tires in real-time. The proposed approach consists of two-stage algorithms that mix a qualitative method using band-pass filtering with a quantitative parameter identification using conditional least squares. This two-stage approach can improve the robustness of tire imbalance or imbalances. The proposed approach is verified through vehicle testing and the test results show the effectiveness of the approach.

In an attempt to predict the responses of side crash pressure sensors, the Corpuscular Particle Method (CPM) was adopted and enhanced in this research. Acceleration-based crash sensors have traditionally been used extensively in automotive industry to determine the air bag firing time in the event of a vehicle accident. The prediction of crash pulses obtained from the acceleration-based crash sensors by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crash zones. As a result, the sensor algorithm developments for acceleration-based sensors are largely based on prototype testing. With the latest advancement in the crash sensor technology, side crash pressure sensors have emerged recently and are gradually replacing acceleration-based sensor for side impact applications.

An Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors in an attempt to assist pressure sensor algorithm development by using computer simulations. Acceleration-based crash sensors have traditionally been used to deploy restraint devises (e.g., airbags, air curtains, and seat belts) in vehicle crashes. The crash pulses recorded by acceleration-based crash sensors usually exhibit high frequency and noisy responses depending on the vehicle's structural design. As a result, it is very challenging to predict the responses of acceleration-based crash sensors by using computer simulations, especially those installed in crush zones. Therefore, the sensor algorithm developments for acceleration-based sensors are mostly based on physical testing.

With a goal to help develop pressure sensor calibration and deployment algorithms using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this research to predict the responses of side crash pressure sensors for unitized vehicles. For occupant protection, acceleration-based crash sensors have been used in the automotive industry to deploy restraint devices when vehicle crashes occur. With improvements in the crash sensor technology, pressure sensors that detect pressure changes in door cavities have been developed recently for vehicle crash safety applications. Instead of using acceleration (or deceleration) in the acceleration-based crash sensors, the pressure sensors utilize pressure change in a door structure to determine the deployment of restraint devices. The crash pulses recorded by the acceleration-based crash sensors usually exhibit high frequency and noisy responses.

In an attempt to assist pressure sensor algorithm and calibration development using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors for body-on-frame vehicles. Acceleration based, also called G-based, crash sensors have been used extensively to deploy restraint devices, such as airbags, curtain airbags, seatbelt pre-tensioners, and inflatable seatbelts, in vehicle crashes. With advancements in crash sensor technologies, pressure sensors that measure pressure changes in vehicle side doors have been developed recently and their applications in vehicle crash safety are increasing. The pressure sensors are able to detect and record the dynamic pressure change when the volume of a vehicle door changes as a result of a crash.

A highly controlled six-vehicle crash test program was conducted to provide an estimate of the test-to-test variability of the NHTSA-proposed passenger car dynamic side impact test procedure. The results of this program showed that the rear seat test dummy response measurements are especially sensitive to various parameters of the test procedure. This paper provides estimates of front and rear seated SID dummy response measurement variability in four-door, 1990 Ford Taurus vehicles. Conclusions and recommendations from this controlled crash test program are made to provide guidance to help reduce the test-to-test variability of the test dummy responses.

The development of combined finite element and spring / rigid mass crash simulation dummy models for automotive applications is described. In order to better understand the crash phenomena and occupant kinematics during vehicle crashes, recent developments have been focused on the use of finite element techniques in the simulation of both structure and structure / dummy interactions. The combination of spring /rigid mass modeling and finite element technique is used to develop models of fiftieth percentile Hybrid III and Side impact Dummies in a finite element program (RADIOSS). In general, the dummies are modeled with rigid masses and joints with techniques similar to those used in Crash Victim Simulation programs like MADYMO and CAL3D. Only selected components, like the Hybrid III dummy thorax and the SID pelvis and jacket, are modeled with finite element shell and brick elements to improve dummy / restraint system and dummy / structure interaction responses.

A model of Ford's current FTP based OBD-II catalyst monitor has been developed and used in determining the optimal monitored catalyst volume for several LEV applications. The model predictions were found to agree reasonably well with the available experimental data. Furthermore, the results of this study indicate that the optimal monitored catalyst volume for meeting LEV requirements is vehicle application specific. As a result, it is concluded that a general guideline for sizing of the monitored catalyst volume for LEVs will most likely be inadequate and could result in grossly suboptimal catalyst monitor function for some applications. The model which is described in this paper offers a potentially more effective means of determining the best monitored catalyst volume for a given vehicle application. It should be possible to utilize this model during the early phase of a vehicle program in order to provide for the optimal packaging of the catalyst monitor sensor (CMS).

The effect of fuel sulfur on the dual HEGO sensor OBD-II catalyst monitor has been investigated. Laboratory studies revealed two competing effects of the fuel sulfur on the operation of the catalyst monitor: 1. the loss of catalyst oxygen storage capacity, and 2. the degradation in the response rate of the rear HEGO sensor. The magnitude of the loss in catalyst OSC relative to the increase in rear HEGO sensor response time determined whether the rear HEGO sensor index increased, decreased, or remained constant as the fuel sulfur level was increased. The effect of fuel sulfur on tailpipe emissions and the catalyst monitor was also measured for two LEVs equipped with Pd-only catalyst technology (a 1997MY Escort and a 1998MY Crown Victoria). For both vehicles, the effect of the fuel sulfur on the rear HEGO sensor response characteristics dominated; as the fuel sulfur level was increased, tailpipe emissions increased, but the rear HEGO sensor index decreased.

Experimental forms of two different types of engine oil viscosity sensors have been tested that use uniformly poled disks of piezoelectric PZT ceramic. In both cases, the disks were used to form electromechanical resonators functioning as the frequency-controlling element in a transistor oscillator circuit. The simpler type of sensor used only one disk, vibrating in a radial-longitudinal mode of vibration. In this mode, a disk 2.54 cm in diameter and 0.127 cm thick had a resonant frequency of approximately 90 kHz. The second type of sensor used two such disks bonded together by a conducting epoxy, with poling directions oriented in opposite directions. This composite resonator vibrated in a radially-symmetrical, flexural mode of vibration, with the lowest resonant frequency at approximately 20 kHz. The presence of tangential components of motion on the major faces of both resonators made them sensitive to the viscosity of fluids in which they were immersed.

A piezoelectrically driven vibrating cantilever blade is damped by a number of mechanisms including viscous damping in a still fluid and aerodynamic damping in a flow. By measuring the damping of devices operating at resonance in the 1 to 5 kHz region, one can measure such properties as mass flow, absolute pressure or the product of molecualar mass and viscosity. In the case of the mass flow measurement, the device offers a mechanical alternative to hotwire and hot film devices for the automotive application.

Increasing electronics content, growing computing power, and proliferation of opportunities for information connectivity (through improved sensors, GPS, road and traffic information systems, wireless internet access, vehicle-to-vehicle communication, etc.) are technology trends which can significantly transform and impact future automotive vehicle's control and diagnostic strategies. One aspect of the increasing vehicle connectivity is access to ambient and road condition information, such as ambient temperature, ambient pressure, humidity, % cloudiness, visibility, cloud ceiling, precipitation, rain droplet size, wind speed, and wind direction based on wireless internet access. The paper discusses the potential opportunities made available through wireless communication between the vehicle and the internet.

Nowadays is a common sense the importance of the CAE usage in the modern automotive industry. The ability to predict the design behavior of a project represents a competitive advantage. However, some CAE models have become so complex and detailed that, in some cases, one just can not build up the model without a considerable amount of information. In that case simplified models play an important role in the design phase, especially in pre-program stages. This work intends to build an archetypal vehicle dynamics model able to predict the rollover resistance of a vehicle design. Through the study of a more complex model, carried out in Adams environment, it was possible to identify the key degrees of freedom to be considered in the simplified model along with important elements of the suspension which are also important design factors.

Exhaust gas temperature is often measured with a device such as thermocouple or RTD (Resistance Temperature Detector). An alternative method to determine the gas temperature would be to use an existing gas sensor heating mechanism to perform as a temperature sensor. A planar type FLOH (Fast Light Off HEGO-Heated Exhausted Gas Oxygen) sensor under transient vehicle speed/load conditions is suited to this function and was modeled to predict the exhaust gas temperature. The numerical input to the model includes exhaust flow rate, heater voltage, and heater current. Laboratory experiments have been performed to produce an equation relating the resistance of the heater and the temperature of the sensor (heater), which provides a method to indirectly determine HEGO sensor temperature.

In 1999, the first generation NOx sensor from NGK Spark Plug, Co., Ltd. was commercialized for use in gasoline LNT NOx after-treatment systems [ 1 ]. Since then, as emissions regulations and OBD requirements have become more stringent, the demand for a high-accuracy NOx sensor with fast light-off has increased, particularly for diesel after-treatment systems. To meet such market demands, NGK Spark Plug, Co., Ltd. has developed, in collaboration with Ford Motor Company, a second generation NOx sensor.

Several shortcomings of mechanical door checks are overcome using a magnetorheological damper. Because the damper is electrically actuated, it can check in any desired position. The logical decision to activate or release the door check can be made either by passive circuitry based on input signals from switches attached to door handles or under microprocessor control, in which case the decision can take into account a variety of unconventional input factors, including the magnitude of the force applied to the door, the rate of change of the applied force, and the angle of door opening. With the addition of an appropriate proximity sensor, the controllable damper can prevent the door from inadvertently hitting a nearby obstacle. Details of the damper mechanism are described, and several implemented control strategies, both passive and microprocessor based, are discussed.

Drive shaft modelling effects frontal crash finite element simulation. A 35 mph rigid barrier impact of a body on frame SUV with an one piece drive shaft and a unibody SUV with a two piece drive shaft have been studied and simulated using finite element analyses. In the model, the drive shaft can take significant load in frontal impact crash. Assumptions regarding the drive shaft model can change the predicted engine motion in the simulation. This change influences the rocker @ B-pillar deceleration. Two modelling methods have been investigated in this study considering both joint mechanisms and material failure in dynamic impact. Model parameters for joint behavior and failure should be determined from vehicle design information and component testing. A body on frame SUV FEA model has been used to validate the drive shaft modeling technique by comparing the simulation results with crash test data.