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The largest automobile companies have several corporate, regulatory and customer requirements to integrate into engineering of development [1]. These information need to be split in technical team called disciplines as electrical, chassis, powertrain, etc. The advanced engineering team is responsible to conduct this process with general purpose of facilitating the managing and tracking of creation and execution of the total vehicle/system. However, the interrelation, complexity and lack of engineer's know-how of these systems have been creating innumerous issues into development, launch, manufactory and quality. Insufficient dedicated tools, requirement definitions and poor initial programs formulation are some reasons of these issues. It means that the ability applied in advanced engineering principles and analytical techniques in an automotive engineering context have to be improved.

Understanding the variation in the deployment times for crash sensor systems is important to ensure robust performance of a crash sensor system. Increases in both the numbers of crash modes and deployable devices have reduced the margins for the decisions about when to deploy any given device. Currently, the industry practice is to run a sweep over the potential sources of variation, recording the minimum and maximum deployment time. Questions such as: “How often do the extremes occur?” or “Are there multiple peaks in the deployment time?” can not be answered. This work uses numerical analysis methods to build on the current sweep methodology to obtain information on the distribution of the deployment times so that questions such as these can be answered when evaluating sensor calibrations. The end result is better informed engineering decisions during the calibration development.

Plug in hybrid electric vehicles (PHEVs) have gained interest over last decade due to their increased fuel economy and ability to displace some petroleum fuel with electricity from power grid. Given the complexity of this vehicle powertrain, the energy management plays a key role in providing higher fuel economy. The energy management algorithm on PHEVs performs the same task as a hybrid vehicle energy management but it has more freedom in utilizing the battery energy due to the larger battery capacity and ability to be recharged from the power grid. The state of charge (SOC) profile of the battery during the entire driving trip determines the electric energy usage, thus determining overall fuel consumption.

Utilization of statistical methods can improve vehicle stopping-distance projections and reduce the complexity of brake deceleration models. These techniques can be very useful in the course of ascertaining whether an untested vehicle conforms to the applicable Federal Motor Vehicle Safety Standard (FMVSS), but they have much broader uses in the design of brake systems.

This paper describes a Design of Experiments (DOE) approach to analyze the significant factors contributing to a high frequency hiss noise emitted by a composite intake manifold. The methodologies used to identify relevant contributing factors are discussed. The approach developed using both subjective and objective response metrics are outlined. The significant factors and their optimal levels are identified through DOE and recommended for incorporation into future design. Moreover, the hiss noise level measured with the recommended improvements on the composite nylon intake manifold is shown to be competitive compared to that of the same type of engine with aluminum intake manifold.

A steady state vehicle model is developed that will predict engine and automatic transmission operating conditions based on various vehicle configurations and operating conditions. The model provides a better understanding of the effects, including direction and magnitude, of changes in vehicle configuration and/or operating conditions on powertrain requirements. The model results can then be used as input into powertrain matching decisions. In general, the model will begin by determining vehicle road load requirements (wheel speed and torque) as a function of vehicle speed based on ambient, road, and vehicle inputs. Such road load requirement will then be cascaded into input and output requirements of the rear axle, transmission gearing, torque converter (locked and unlocked), and finally the engine. Wide open throttle engine torque data will also be translated into tractive effort at the wheels and resulting acceleration capability versus the vehicle road load requirements.

IC engines have been the dominant automotive powertrain in the 20th century because of their advantages in power density, thermal efficiency, simplicity, durability and mobility. Condensing 100 years of information on automotive engine system technology evolution shows five different development stages: “bone and muscle”, “instinct”, “nerve and brain”, “intelligence”, and “system optimization”. Currently, the last step is facing the pressure of the “clean revolution” plus the “e-commerce revolution”. To meet future emission requirements and reduce CO2 emissions, the conventional engine system will be pushed to new physical limits, leading to higher cost and reduced durability. Therefore, the automobile industry should consider re-engineering or system optimization of the engines, including configuring the system architecture to be as transparent as possible to suit the fast changing environment of e-commerce.

The automotive industry is currently experiencing a massive transformation, one like it has not quite seen in the past. With the advent of highly software-driven, always on, connected vehicles, the automotive industry is experiencing itself at a crossroads. While the traditional component-driven design approach to vehicle development worked in the favor of the industry for decades due to vehicles being mostly mechanical in nature, the industry now finds itself struggling to develop well-integrated vehicle solutions with the large dependency on software systems. The fast-paced nature of the software world makes it imperative to approach the development of automobiles from a Systems Engineering perspective. A function-based approach to the development of vehicle architectures can ensure cohesive systems development and a well-integrated vehicle.

This work presents a study of crash energy and severity in frontal offset Vehicle-To-Vehicle (VTV) crash tests. The crash energy is analyzed based on analytical formulations and empirical data. Also, the crash severity of different VTV tests is analyzed and compared with the corresponding full frontal rigid barrier test data. In this investigation, the Barrier Equivalent Velocity (BEV) concept is used to calculate the initial impact velocity of frontal offset VTV test modes such that the offset VTV tests are equivalent to full frontal impact tests in terms of crash severity. Linear spring-mass model and collinear impact assumptions are used to develop the mathematical formulation. A scale factor is introduced to account for these assumptions and the calculated initial velocity is adjusted by this scale factor. It is demonstrated that the energies due to lateral and rotational velocity components are very small in the analyzed frontal VTV tests.

An experimental study was conducted using a dynamic rollover component test system (ROCS) to study the effects of activating a pyro-mechanical buckle pre-tensioner and an electric retractor on the driver and front right passenger head and pelvis excursions. The ROCS is a unique system capable of producing vehicle responses that replicate four distinct phases of a tripped rollover: trip initiation, roll initiation, free-flight vehicle rotation, and vehicle to ground contact. This component test system consists of a rigid occupant compartment derived from a mid-size SUV with complete 1st row seating and interior trim, a simulated vehicle suspension system and an elastic vehicle-to-ground-contact surface. The ROCS system was integrated with a Deceleration Rollover Sled (DRS). Dynamic responses of the ROCS system, including both the rigid compartment and occupant, were measured and recorded.

In light-duty direct-injection (DI) diesel engines, combustion chamber geometry influences the complex interactions between swirl and squish flows, spray-wall interactions, as well as late-cycle mixing. Because of these interactions, piston bowl geometry significantly affects fuel efficiency and emissions behavior. However, due to lack of reliable in-cylinder measurements, the mechanisms responsible for piston-induced changes in engine behavior are not well understood. Non-intrusive, in situ optical measurement techniques are necessary to provide a deeper understanding of the piston geometry effect on in-cylinder processes and to assist in the development of predictive engine simulation models. This study compares two substantially different piston bowls with geometries representative of existing technology: a conventional re-entrant bowl and a stepped-lip bowl. Both pistons are tested in a single-cylinder optical diesel engine under identical boundary conditions.

This Paper introduces a modular, flexible and user-friendly dynamic powertrain model of the US Army's High Mobility Multi-Wheeled Vehicle (HMMWV). It includes the DDC 6.5L diesel engine, Hydra-matic 4L80-E automatic transmission, Torsen differentials, transfer case, and flexible drive and axle shafts. This model is used in a case study on transmission optimization design to demonstrate an application of the model. This study shows how combined optimization of the transmission hardware (clutch capacity) and control strategy (shift time) can be explored, and how the models can help the designer understand dynamic interactions as well as provide useful design guidance early in the system design phase.

An integral part of combustion system development for previous NA gasoline engines was the optimization of charge motion towards the best compromise in terms of full load performance, part load stability, emissions and, last but not least, fuel economy. This optimum balance may potentially be different in GTDI engines. While it is generally accepted that an increased charge motion level improves the mixture preparation in direct injection gasoline engines, the tradeoff in terms of performance seems to become less dominant as the boosting systems of modern engines are typically capable enough to compensate the flow losses generated by the more restrictive ports. Nevertheless, the increased boost level does not come free; increased charge motion generates higher pumping- and wall heat losses. Hence it is questionable and engine dependent, whether more charge motion is always better.

When driving or riding in a vehicle, the customer is bombarded with sensory stimuli. These include tactile, auditory, olfactory and visual. In addition, the customer may be asked to perform various routine driving tasks that can have an influence on the perception of each of the aforementioned senses. Or perhaps, the influence of one sense may affect the perception of another. Since sound rarely occurs void of felt vibration and vice-versa, there is reason to believe one may influence the perception of the other, or that the two may interact in some way when the customer is exposed to a particular NVH (Noise Vibration and Harshness) event in a vehicle. The NVH engineer wishes to gage a sound or vibration's impact on the customer and make a determination as to whether corrective actions on the vehicle are necessary. NVH issues routinely show up as top warranty and customer satisfaction concerns.

This paper presents two brake control functions which are initiated when there is an impact force applied to a host vehicle. The impact force is generated due to the host vehicle being collided with or by another vehicle or object. The first function - called the post-impact braking assist - initiates emergency brake assistance if the driver is braking during or right after the collision. The second function - called the post-impact braking - initiates autonomous braking up to the level of the anti-lock-brake system if the driver is not braking during or right after the collision. Both functions intend to enhance the current driver assistance features such as emergency brake assistance, electronic stability control, anti-brake-lock system, collision mitigation system, etc.

Researchers and engineers are utilizing big data analytics to draw further insights into transportation systems. Large amounts of data at the individual vehicle trip level are being collected and stored. The true potential of such data is still to be determined. In this paper, we are presenting a data-driven, novel, and intuitive approach to model driver behaviors using microscopic traffic simulation. Our approach utilizes metaheuristic methods to create an analytical tool to assess vehicle performance. Secondly, we show how microscopic simulation run outputs can be post-processed to obtain vehicle and trip level performance metrics. The methodology will form the basis for a data-driven approach to unearthing trip experiences as realized by drivers in the real world. The methodology will contribute to, A.) Using vehicle trajectory traces to identify underlying vehicle maneuver distributions as obtained from real-world driver data, B.)

Many decisions need to be made when test track data is used to set up Squeak & Rattle evaluations of subsystems or components. These decisions are judgment-based so different people with different backgrounds and experience levels will make different decisions - few of which can be called right or wrong - but they are different which causes problems. Squeak & Rattle evaluation has become more scientific in recent years as subjective evaluation has been replaced by quantitative methods like N10 Loudness and shakers have become quiet. It is the authors' contention that the variations caused by different judgment calls can no longer be tolerated. Therefore a methodical process was developed which assures that different people will get the same results from the same set of test track data.

The traditional analysis of squeal noise for drum brakes is done in a separate approach, with CAE and laboratory/experimental techniques done independently or in a non-iterative sequential manner. In this paper, an innovative approach of directing the frequency response testing based on CAE is used and the overall process is embedded in a system approach. The drum brake design was changed to accomplish higher loads in a car. The initial results of the tests came out noise during the vehicle test. After retrieving the noisy parts from the vehicle, it was tested for frequency response, but in a directional manner suggested by the CAE model. This new approach hasn't been done before in industry practice. The CAE identified that two modes (around the noise frequency) swapped their orders compared to the old design and suggested design changes. The new design was evaluated with a mocked up prototype. This was followed by getting cast parts and testing them for frequency response.

This paper is divided into two parts: Part 1 - Systems engineering fundamentals Part 2 - Engine cooling design from a systems engineering perspective In Part 1, we explain how the task of designing a complex system can be made easier by the application of Systems Engineering principles. (This part is self contained and may be of general interest to those who have no special interest in engine cooling). Systems Engineering provides three key benefits: It facilitates communication: Requirements define the problem, they allow team members to see their own work in context Key information is standardized and made easier to visualize and verify. An “audit trail” is maintained ensuring that important information is documented, and human memory is no longer relied on for important decisions. Translates requirements into design.

Recently, papers have been published purporting to study the effect of rear axle tramp during tread separation events, and its effect on vehicle handling [1, 2]. Based on analysis and physical testing, one paper [1] has put forth a mathematical model which the authors claim allows vehicle designers to select shock damping values during the development process of a vehicle in order to assure that a vehicle will not experience axle tramp during tread separations. In the course of their work, “lumpy” tires (tires with rubber blocks adhered to the tire's tread) were employed to excite the axle tramp resonance, even though this method has been shown not to duplicate the physical mechanisms behind an actual tread belt separation. This paper evaluates the theories postulated in [1] by first analyzing the equations behind the mathematical model presented. The model is then tested to see if it agrees with observed physical testing.