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Traditionally, the controls system in production vehicles with automatic transmission interprets the driver’s accelerator pedal position as a demand for transmission input torque. However, with the advent of electrified vehicles, where actuators are located at different positions in the drivetrain, and of autonomous vehicles, which are self-driving, it is more convenient to interpret the demand (either human or virtual) in vehicle acceleration or wheel torque domain. To this end, a Wheel Torque-based longitudinal Control (WTC) framework was developed, wherein demands can be converted accurately between the vehicle acceleration or wheel torque domain and the transmission assembly input torque domain.

North American drivers particularly dislike wheel dust (brake dust on their wheels). For some vehicle lines, customer surveys indicate that wheel dust is a significant concern. For this reason, Ford and its suppliers are investigating the root causes of brake dust and developing test procedures to detect wheel dust issues up-front. Intuitively, it would appear that more brake wear would lead to more wheel dust. To test this hypothesis, a gage was needed to quantitatively measure the wheel dust. Gages such as colorimeters were evaluated to measure the brightness (L*) of the wheel, which ranged from roughly 70-80% (clean) to 10-20% (very dirty). Gage R&R's and subjective ratings by a panel of 30 people were used to validate the wheel dust gages. A city traffic vehicle test and an urban dynamometer procedure were run to compare the level of wheel dust for 10 different lining types on the same vehicle.

AS a basis for the analyses of this symposium, a hypothetical car has been used to evaluate the engine power distribution in performance. Effects of fuel,-engine accessories, and certain car accessories are evaluated. The role of the transmission in making engine power useful at normal car speeds is also discussed. Variables encountered in wind and rolling resistance determinations are reevaluated by improved test techniques. Net horsepower of the car in terms of acceleration, passing ability and grade capability are also summarized.

The demand for seating comfort is growing - in cars as well as trucks and other commercial vehicles. This is expected as the seat is the largest surface area of the vehicle that is in contact with the occupant. While it is predominantly luxury cars that have been equipped with climate controlled seats, there is now a clear trend toward this feature becoming available in mid-range and compact cars. The main purpose of climate controlled seats is to create an agreeable microclimate that keeps the driver comfortable. It also reduces the “stickiness” feeling which is reported by perspiring occupants on leather-covered seats. As part of the seat design process, a physical test is performed to record and evaluate the life cycle and the performance at ambient and extreme temperatures for the climate controlled seats as well as their components. The test calls for occupied and unoccupied seats at several ambient temperatures.

On the development process of truck vehicles, the dynamic behavior must be considered together with the costs involved in this development. Objective measurements, subjective evaluations and CAE simulations are used in order to support this development process. Ride comfort, acceleration and braking performance, handling and NVH are examples of attributes considered in the dynamic behavior evaluation of a tuck. Some characteristics of steering column vibration, noise and harshness are relevant to guarantee driver comfort level and vehicle safety. In this work, CAE models validated by experimental measurements were used to identify cab and vehicle modes of vibration which have significant influence on steering column response. Using this procedure, an alternative was proposed in order to decrease the amplitudes of cab and steering column vibration.

A DMS (Driver Monitoring System) is one of the most important safety features that assist in the monitoring functions and alert drivers when distraction or drowsiness is detected. The system is based in a DSMC (Driver Status Monitoring Camera) mounted in the vehicle's dash, which has a predefined set of operational requirements that must be fulfilled to guarantee the correct operation of the system. These conditions represent a trade space analysis challenge for each vehicle since both the DSMC and the underlying vehicle’s requirements must be satisfied. Relying upon the camera’s manufacturer evaluation for every iteration of the vehicle’s design has proven to be time-consuming, resources-intensive, and ineffective from the decision-making standpoint.

With the increasing number of cars on the street, the exchange of information between those cars becomes essential to improve the driving skills of each driver, resulting in a safer, intelligent and more dynamic traffic. The task now is to make it accessible for everyone. One possible and cheap way to solve this issue is to seek possibilities on free technologies within market trends. Using the smartphone platforms, which holds a high level of embedded technologies, becoming a global communication device even to interpersonal and to social networks, and AppLink Development Kit for smartphones and vehicles integration, this paper will cover aspects about the integration of the kit to an database application based on the cloud, enabling real-time interaction between two cars. Making possible to a driver have access to information and current status of other cars to aid ones life on heavy traffic.

Researchers report an estimated 35.7 million of vehicles with touchscreens will be sold in 2019 worldwide [1]. As the use of touchscreens grows in the automotive industry, there is a need to study how driver’s arm and hand moves to access the touchscreen as well as how the driver utilizes the hardware around the touchscreen. In order to aid drivers while using the touchscreen and to minimize distractions, the drivers’ hand must be able to freely move to perform a task on the touchscreen without the trim interfering with the task. At the same time some trim may be used to support the hand and fingers while accessing the touchscreen particularly during tasks that take a longer period of time to complete. A study was performed to understand the effect of the size and the angle of a shelf placed under a touchscreen. Motion capture (Mocap) data of the hand of subjects performing two different tasks on the touchscreen was collected in the Human Occupant Package Simulator (HOPS).

A vehicle integrated sensing and analysis system has been designed, implemented, and demonstrated to nonintrusively monitor several biological signals of the driver. The biological driver signals measured by the system are the heart electrical signals or pseudo Lead-I electrocardiography (pLI-ECG), the galvanic skin response (GSR) or electrical conductance measured from the driver's fingers to palm, the palm skin temperature, the face skin temperature, and the respiration rate. The pLI-ECG and GSR measurements are made through direct contact of the driver hands with stainless steel electrodes integrated in the steering wheel rim. The temperature measurements are made with non-contacting infrared temperature sensors, also located on the steering wheel. The respiration rate was measured using a flexible thin film piezoelectric sensor affixed to the seatbelt.

Onboard, embedded cellular modems are enabling a range of new connectivity features in vehicles and rich, real-time data set transmissions from a vehicle’s internal network up to a cloud database are of particular interest. However, there is far too much information in a vehicle’s electrical state for every vehicle to upload all of its data in real-time. We are thus concerned with which data is uploaded and how that data is processed, structured, stored, and reported. Existing onboard data processing algorithms (e.g. for DTC detection) are hardcoded into critical vehicle firmware, limited in scope and cannot be reconfigured on the fly. Since many use cases for vehicle data analytics are still unknown, we require a system which is capable of efficiently processing and reporting vehicle deep data in real-time, such that data reporting can be switched on/off during normal vehicle operation, and that processing/reporting can be reconfigured remotely.

The strain-life approach is now commonly used for fatigue life analysis and predictions in the ground vehicle industry. This approach requires the use of material properties obtained from strain-controlled uniaxial fatigue tests. These properties include fatigue strength coefficient (σf′), fatigue strength exponent (b), fatigue ductility coefficient (εf′), fatigue ductility exponent (c), cyclic strength coefficient (K′), and cyclic strain hardening exponent (n′). To obtain the aforementioned properties for the material, raw data from stable cyclic stress-strain loops are fitted in log-log scale. These data include total, elastic and plastic strain amplitudes, stress amplitude, and fatigue life. Values of the low cycle fatigue properties (σf′, b, εf′, c) determined from the raw data depend on the method of measurement and fitting. This paper examines the merits and influence of using different measurement and fitting methods on the obtained properties.

A traditional vane type oil pump used inside the engines and the transmissions has equal angles or spacing between the vanes. The equal spacing intensifies pressure fluctuations generated within the pump leading to narrowband pressure spikes at the pump main order and its harmonics. Unequal spacing, however, can relax the severity of the spikes by breaking down the narrowband peaks and distributing them over a larger frequency range. Optimization of the angles within the pump design constraint can maximize the benefit of unequal spacing in reducing the pressure pulsations for a lower risk of engine or transmission whine. The scope of this paper is around the optimization process for vane spacing and different objective functions which can be used to obtain optimized solutions. The simulation results for optimized spacing based on two different objective functions for 7, 8 and 9 vanes are presented. The design constraints for the optimization are discussed as well.

The validation of an assembly of component finite element models to high frequencies is a difficult challenge. Basic steps coupled with advanced correlation techniques are required to produce system finite element models that correlate to modal test data. This paper describes those steps as they were applied to a system model of a complex transaxle.

This paper describes a method to validate in-vehicle speech recognition by combining synthetically mixed speech and noise samples with batch speech recognition. Vehicle cabin noises are prerecorded along with the impulse response from the driver's mouth location to the cabin microphone location. These signals are combined with a catalog of speech utterances to generate a noisy speech corpus. Several factors were examined to measure their relative importance on speech recognition robustness. These include road surface and vehicle speed, climate control blower noise, and driver's seat position. A summary of the main effects from these experiments are provided with the most significant factors coming from climate control noise. Additionally, a Signal to Noise Ratio (SNR) experiment was conducted highlighting the inverse relationship with speech recognition performance.

To manage the function of a vehicle's engine, transmission, and related subsystems, almost all modern vehicles make use of one or more electronic controllers running embedded software, henceforth referred to as a Powertrain Controller System or PCS. Fully validating this PCS is a necessary step of vehicle development, and the validation process requires extensive amounts of testing. Traditionally, this validation testing is done with open-loop signal generators, powertrain dynamometers, and real vehicles. Such testing methods either cannot simulate complex control system interactions, or are expensive and subject to variability. To address these concerns while decreasing development time and improving vehicle quality, Ford Motor Company is placing increasing focus on validating a PCS through simulation. One such testing method is a Hardware-in-the-Loop (HIL) simulation, which mates the physical elements of a PCS to a real-time computer simulation of a powertrain.

Bluetooth Low Energy (BLE) is an energy-efficient radio communication technology that is rapidly gaining popularity for various Internet of Things (IoT) applications. While BLE was not designed specifically with vehicular communications in mind, its simple and quick connection establishment mechanisms make BLE a potential inter-vehicle communication technology, either replacing or complementing other vehicle-to-vehicle (V2V) technologies (such as the yet to be deployed DSRC). In this paper we propose a framework for V2V communication using BLE and evaluate its performance under various configurations. BLE uses two major methods for data transmission: (1) undirected advertisements and scanning (unconnected mode) and (2) using the central and peripheral modes of the Generic Attribute Profile (GATT) connection (connected mode).

Previously fuel consumption on a drive cycle has been shown to be proportional to traction work, with an offset for powertrain losses. This model had different transfer functions for different drive cycles, performance levels, and applied powertrain technologies. Following Soltic it is shown that if fuel usage and traction work are both expressed in terms of cycle average power, a wide range of drive cycles collapse to a single transfer function, where cycle average traction power captures the drive cycle and the vehicle size. If this transfer function is then normalized by weight, i.e. by working in cycle average power/weight (P/W), a linear model is obtained where the offset is mainly a function of rated performance and applied technology. A final normalization by rated power/weight as the primary performance metric further collapses the data to express the cycle average fuel power/rated power ratio as a function of cycle average traction power/rated power ratio.

Advanced features in automotive systems often necessitate the management of complex interactions between subsystems. Existing control strategies are designed for certain levels of robustness, however their performance can unexpectedly deteriorate in the presence of significant uncertainties, resulting in undesirable system behaviors. This limitation is further amplified in systems with complex nonlinear dynamics. Hydro-mechanical clutch actuators are among those systems whose behaviors are highly sensitive to variations in subsystem characteristics and operating environments. In a P2 hybrid propulsion system, a wet clutch is utilized for cranking the engine during an EV-HEV mode switching event. It is critical that the hydro-mechanical clutch actuator is stroked as quickly and as consistently as possible despite the existence of uncertainties. Thus, the quantification of uncertainties on clutch actuator behaviors is important for enabling smooth EV-HEV transitions.

Wet clutch packs are widely used in today’s automatic transmission systems for gear-ratio shifting. The frictional interfaces between the clutch plates are continuously lubricated with transmission fluid for both thermal and friction management. The open clutch packs shear transmission fluid across the rotating plates, contributing to measurable energy losses. A typical multi-speed transmission includes as many as 5 clutch packs. Of those, two to three clutches are open at any time during a typical drive cycle, presenting an opportunity for fuel economy gain. However, reducing open clutch drag is very challenging, while meeting cooling requirements and shift quality targets. In practice, clutch design adjustment is performed through trial-and-error evaluation of hardware on a test bench. The use of analytical methodologies is limited for optimizing clutch design features due to the complexity of fluid-structure interactions under rotating conditions.

Ford's new 2.3 Litre I-4 Turbocharged Engine and Powertrain was specifically developed to match the new 1979 Mustang/ Capri. This engine/vehicle combination was developed to provide the customer excellent vehicle performance, good fuel economy and driveability. Extensive vehicle and dynamometer work was done to match the turbocharger to the engine and optimize in-vehicle mid-range to high end performance. The relatively high compression ratio (9.0:1) was retained from the naturally aspirated engine to preserve low end manual transmission vehicle performance before turbocharger boost. Revisions to basic engine components and structures to insure durability will be discussed.