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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.

There are a multitude of dynamics faced by any industry. There is also a consistent search and development of technological platforms and services to address these changes. This necessitates a shared work philosophy which involves multiple stakeholders. Verification and validation are integral part of any development irrespective of product, process, or services. Also, every industry has a regulatory compliance to adhere too. But the extent of complexity and the level of dependencies or interactions between modules as well as stakeholders involved, creates slippage at some or other level. Nowadays the industries are also driven by reuse for cost effectiveness. Though it marks the significant improvement in the capability to compete, compatibility is a key measure to a successful product or service launch and sustainability.

In this paper, a novel mixed-integer programming model is developed to optimally assign the die sets to candidate plants to minimize the total costs. The total costs include freight shipping stamped parts to assembly plants, die set movement, outsourcing, and utilization. Therefore, the objective function is weighted multi-criteria and it takes into consideration some of the key constraints in the real-world condition including “must-move die sets”. An optimization tool has been developed that takes several inputs and feeds them as the input to the mathematical model and generates the optimal assignments with the directional costs as the output. The tool has been tested for several plants at Ford and has proved its robustness by saving millions of dollars. The developed tool can easily be applied to other manufacturing systems and original equipment manufacturers (OEMs).

This paper presents experimental results that validate eco-driving and eco-heating strategies developed for connected and automated vehicles (CAVs). By exploiting vehicle-to-infrastructure (V2I) communications, traffic signal timing, and queue length estimations, optimized and smoothed speed profiles for the ego-vehicle are generated to reduce energy consumption. Next, the planned eco-trajectories are incorporated into a real-time predictive optimization framework that coordinates the cabin thermal load (in cold weather) with the speed preview, i.e., eco-heating. To enable eco-heating, the engine coolant (as the only heat source for cabin heating) and the cabin air are leveraged as two thermal energy storages. Our eco-heating strategy stores thermal energy in the engine coolant and cabin air while the vehicle is driving at high speeds, and releases the stored energy slowly during the vehicle stops for cabin heating without forcing the engine to idle to provide the heating source.

Historical driver behavior and drive style are crucial inputs in addition to V2X connectivity data to predict future events as well as fuel consumption of the vehicle on a trip. A trip is a combination of different maneuvers a driver executes to navigate a route and interact with his/her environment including traffic, geography, topography, and weather. This study leverages big data analytics on real-world customer driving data to develop analytical modeling methodologies and algorithms to extract maneuver-based driving characteristics and generate a corresponding maneuver distribution. The distributions are further segmented by additional categories such as customer group and type of vehicle. These maneuver distributions are used to build an aggressivity distribution database which will serve as the parameter basis for further analysis with traffic simulation models.

As an alternative lightweight material, chopped carbon fiber reinforced Sheet Molding Compound (SMC) composites, formed by compression molding, provide a new material for automotive applications. In the present study, the monotonic and fatigue behavior of chopped carbon fiber reinforced SMC is investigated. Tensile tests were conducted on coupons with three different gauge length, and size effect was observed on the fracture strength. Since the fiber bundle is randomly distributed in the SMC plaques, a digital image correlation (DIC) system was used to obtain the local modulus distribution along the gauge section for each coupon. It was found that there is a relationship between the local modulus distribution and the final fracture location under tensile loading. The fatigue behavior under tension-tension (R=0.1) and tension-compression (R=-1) has also been evaluated.

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.

In the recent years, adjoint optimization has gained popularity in the automotive industry with its growing applications. Since its inclusion in the mainstream commercial CFD solvers and its continuously added capabilities over the years, its productive usage became readily available to many engineers who were previously limited to interfacing the customized adjoint source code with CFD solvers. The purpose of this work is to demonstrate using an adjoint solver a method to optimize duct shape that meets multiple design objectives simultaneously. To overcome one of the biggest challenges in the duct design, i.e. the severe packaging constraints, the method here uses geometrically constrained adjoint to ensure that the optimum shape always fits into the user-defined packaging space. In this work, adjoint solver and surface sensitivity calculations are used to develop the optimization method.

Friction reduction in lubricated components through engine oil formulations has been investigated in the present work. Three different DI packages in combination with one friction modifier were blended in SAE 5 W-20 and SAE 0 W-16 viscosity grades. The friction performance of these oils was compared with GF-5 SAE 5 W-20 oil. A motored cranktrain assembly has been used to evaluate these, in which friction mean effective pressure (FMEP) as a function of engine speeds at different lubricant temperatures is measured. Results show that the choice of DI package plays a significant role in friction reduction. Results obtained from the mini-traction machine (MTM2) provide detailed information on traction coefficient in boundary, mixed and elastohydrodynamic (EHD) lubrication regimes. It has been shown that the results from the cranktrain rig are fairly consistent with those found in MTM2 tests for all the lubricants tested.

This paper summarizes the development of a wireless message from infrastructure-to-vehicle (I2V) for safety applications based on Dedicated Short-Range Communications (DSRC) under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). During the development of the Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure (RSZW/LC) safety applications [1], the Basic Information Message (BIM) was developed to wirelessly transmit infrastructure-centric information. The Traveler Information Message (TIM) structure, as described in the SAE J2735, provides a mechanism for the infrastructure to issue and display in-vehicle signage of various types of advisory and road sign information. This approach, though effective in communicating traffic advisories, is limited by the type of information that can be broadcast from infrastructures.

To assess the fuel consumption of vehicles, three sets of input data are required; drive cycles, vehicle parameters, and environmental conditions. As the first part of a series of studies on real-world fuel consumption, this study focuses on the drive cycles. In principle, drive cycles should represent real-world usage. Some of them aim at a specific usage such as a city driving condition or an aggressive driving style. However, the definition of city or aggressive driving is very subjective and difficult to quantitatively correlate with the real-world usage. This study proposes a methodology to quantify the speed and dynamics of drive cycles, or vehicle speed traces in general, against the real-world usage. After reviewing parameter sets found in other studies, relative cubic speed (RCS) and positive kinetic energy (PKE) are selected to represent the speed and dynamics through energy flow balance at the wheels.

SiC devices have inherent fast switching capabilities due to their superior material properties, and are considered potential candidates to replace Si devices for traction inverters in electrified vehicles in future. However, due to the comparatively low gate threshold voltage, SiC devices may encounter oscillatory false triggering especially during fast switching. This paper analyzed the causes of false triggering, and also studied the impact of a critical parasitic parameter - common source inductance. It is shown that crosstalk is the main cause for the false triggering in the case and some positive common source inductance help to mitigate the crosstalk issue. A packaging layout method is proposed to create the positive common source inductance through layout of control terminals / busbars, and/or the use of control terminal bonded wires at different height.

Electric vehicles are highly sensitive to variations in environmental factors (like temperature, drive style, grade, etc.). The distribution of real-world range of electric vehicles due to these environmental factors is an important consideration in target setting. This distribution can be obtained by running several simulations of an electric vehicle for a number of high-frequency velocity, grade, and temperature real-world trip profiles. However, in order to speed up simulation time, a unique set of drive profiles that represent the entire real-world data set needs to be developed. In this study, we consider 40,000 unique velocity and grade profiles from various real-world applications in EU. We generate metadata that describes these profiles using trip descriptor variables. Due to the large number of descriptor variables when considering second order effects, we normalize each descriptor and use principal component analysis to reduce the dimensions of our dataset to six components.

Self-pierced rivet (SPR) and adhesive are two important joining technologies widely used in automobile industry, and they are often used together to form a hybrid joint. SPR and adhesives can often be used in close proximity in a component, leading to an interaction of the two joints. This interaction can influence the corrosion and noise, vibration and harshness (NVH) characteristics of the structure, as well as its strength and durability. In this paper, the stress distribution in an SPR-adhesive hybrid joint is evaluated by using the finite element method, and then compared with that in an adhesive joint. Results indicate that the stress concentrates at the edge of adhesive layer in hybrid joint and adhesive joint and around the rivet in an SPR joint. The effect of rivet is numerically investigated by either removing the rivet from the hybrid joint or changing the position of the rivet on the overlapping area.

Ultrasonic fatigue tests (testing frequency around 20kHz) have been conducted on A356 aluminum alloys with different copper contents and AS7GU aluminum alloy. Tests were performed in dry air and submerged in water conditions. The effect of copper content was investigated and it was concluded that copper content plays an important role influencing the humidity effect on A356 aluminum alloy ultrasonic fatigue lives. Also, for the same copper content, copper in solute solution or in precipitate have different humidity sensitivities.

The business environment is ever changing, several innovations have allowed companies to transcend borderlines and become global entities. While the opportunities are numerous so are the challenges. In this fiercely competitive global marketplace, success requires companies to pay closer attention to supplier relations. The relationship between an automotive industry and its suppliers is an example of it, so the application of CAE (Computer Aided Engineering) superelement technique may improve, in terms of NVH (Noise, Vibration and Harshness), the vehicle development efficiency, without compromising confidentiality directives. Most of NVH requirements must be tracked through Transfer Functions (TFs) analyses at response points located on the Trimmed-Body Finite Element Model (FEM), as for example: Point Mobility, Vibration Transfer Function (VTF) and Acoustic Transfer Function (ATF).

The development costs that new design requires are subject to everyday discussions and saving opportunities are mandatory. Using CAE to predict design changes can avoid excessive costs with prototypes parts, considering the high reliability those current mathematical models can provide. This paper presents the methodology used during the development of a parabolic leaf spring for the rear suspension of a commercial truck, considering mainly the parabolic profiles and stress distribution on the leaves, calculated using CAE software (ANSYS) and experimental tests to measure the actual stress on each leaf, certifying the correlation between computational calculations and real stress on the parts during bench and vehicle evaluations.

In order to optimize the development of bolted joints used to components attachments in the Sidemember of commercial vehicles, the joints development has become relevant to better definition of the fasteners size, eliminating overweight and avoiding under or super-sized. This paper presents a development sequential approach of bolted joints applied on commercial vehicles ensuring the correct specifications usage of the fasteners and the joint to keep their clamp force. The evaluations were conducted based on theoretical and practical aspects applied on products and in the definition of all elements contained in a joint. The calculation methodology was developed based on standardized bolts and forces generated through the reactions of the components required for each vehicle family.

The design and operation of a vehicle’s heating, ventilation, and air conditioning (HVAC) system has great impact on the performance of the vehicle’s Automatic Speech Recognition (ASR) and Hands-Free Communication (HFC) system. HVAC noise provides high amplitudes of broadband frequency content that affects the signal to noise ratio (SNR) within the vehicle cabin, and works to mask the user’s speech. But what’s less obvious is that when the airflow from the panel vents or defroster openings can be directed toward the vehicle microphone, a mechanical “buffeting” phenomenon occurs on the microphone’s diaphragm that distresses the ASR system beyond its ability to interpret the user’s voice. The airflow velocity can be strong enough that a simple windscreen on the microphone is not enough to eliminate the problem. Minimizing this buffeting effect is a vital key to building a vehicle that meets the customer’s expectations for ASR and HFC performance.

Ford Motor Company’s assembly plants build vehicles in a certain sequence. The planned sequence for the plant’s trim and final assembly area is developed centrally and is sent to the plant several days in advance. In this work we present the study of two cases where the plant changes the planned sequence to cope with production constraints. In one case, a plant pulls ahead two-tone orders that require two passes through the paint shop. This is further complicated by presence in the body shop area of a unidirectional rotating tool that allows efficient build of a sequence “A-B-C” but heavily penalizes a sequence “C-B-A”. The plant changes the original planned sequence in the body shop area to the one that satisfies both pull-ahead and rotating tool requirements. In the other case, a plant runs on lean inventories. Material consumption is tightly controlled down to the hour to match with planned material deliveries.