Search Results

This paper presents the application of a proposed fuzzy inference system as part of a stability control design scheme implemented with active steering actuator sets. The fuzzy inference system is used to detect the level of overseer/understeer at the high level and a speed-adaptive activation module determines whether an active front steering, active rear steering, or active 4 wheel steering is suited to improve vehicle handling stability. The resulting model-free system is capable of minimizing the amount of model calibration during the vehicle stability control development process as well as improving vehicle performance and stability over a wide range of vehicle and road conditions. A simulation study will be presented that evaluates the proposed scheme and compares the effectiveness of active front steer (AFS) and active rear steer (ARS) in enhancing the vehicle performance. Both time and frequency domain results are presented.

A new turbocharged 60° 2.7L 4V-V6 gasoline engine has been developed by Ford Motor Company for both pickup trucks and car applications. This engine was code named “Nano” due to its compact size; it features a 4-valves DOHC valvetrain, a CGI cylinder block, an Aluminum ladder, an integrated exhaust manifold and twin turbochargers. The goal of this engine is to deliver 120HP/L, ULEV70 emission, fuel efficiency improvements and leadership level NVH. This paper describes the upfront design and optimization process used for the NVH development of this engine. It showcases the use of analytical tools used to define the critical design features and discusses the NVH performance relative to competitive benchmarks.

Exhaust pressures (P3) are hard parameters to measure and can be readily estimated, the cost of the sensors and the temperature in the exhaust system makes the implementation of an exhaust pressure sensor in a vehicle control system a costly endeavor. The contention with measured P3 is the accuracy required for proper engine and vehicle control can sometimes exceed the accuracy specification of market available sensors and existing models. A turbine inlet exhaust pressure observer model based on isentropic expansion and heat transfer across a turbocharger turbine was developed and investigated in this paper. The model uses 4 main components; an open loop P3 orifice flow model, a model of isentropic expansion across the turbine, a turbine and pipe heat transfer models and an integrator with the deviation in the downstream turbine outlet parameter.

The purpose of this work is to analytically investigate automotive exhaust system noise generation and propagation phenomena. The turbulent exhaust gas flow interacts with the exhaust system structure, and as a result of this interaction, the structure vibrates and radiates noise. In the meantime, pressure wave becomes acoustic wave at its outlet. This study focuses on an exhaust system and carrying out transient fluid-structure analysis by using an explicit finite element solver that is capable of solving the Navier Stokes equations for turbulent, compressible viscous fluids as well as the field equations for solid structures in a fully coupled fashion. The time domain signals obtained from the transient analysis are post-processed to yield frequency domain data, sound pressure levels, noise source pattern as well as the selected acoustic field contour snapshots.

The ability to operate a spark-ignition (SI) engine near the knock limit provides a net reduction of engine fuel consumption. This work presents a real-time knock control system based on stochastic knock detection (SKD) algorithm. The real-time stochastic knock control (SKC) system is developed in MATLAB Simulink, and the SKC software is integrated with the production engine control strategy through ATI's No-Hooks. The SKC system collects the stochastic knock information and estimates the knock level based on the distribution of knock intensities fitting to a log-normal (LN) distribution. A desired knock level reference table is created under various engine speeds and loads, which allows the SKC to adapt to changing engine operating conditions. In SKC system, knock factor (KF) is an indicator of the knock intensity level. The KF is estimated by a weighted discrete FIR filter in real-time.

Future Diesel emission standards for passenger cars, light and medium duty vehicles, require the combination of a more efficient NOx reduction performance along with the opportunity to reduce the complexity and the package requirements to facilitate it. With the increasing availability of aqueous urea, DEF or AdBlue® at service stations, and improved package opportunities, the urea SCR technical solution has been demonstrated to be very efficient for NOx reduction; however the complexity in injecting and distributing the reductant remains a challenge to the industry. The traditional exhaust system contains Diesel Oxidation Catalysts (DOC), Diesel Particulate Filters (DPF) and Selective Catalytic Reduction (SCR), all require additional heat to facilitate each of their specific functions.

Automakers have the opportunity to utilize bio-based composite materials to lightweight cars while replacing conventional, nonrenewable resource materials. In this study, Life Cycle Assessment (LCA) is used to understand the potential benefits and tradeoffs associated with the implementation of bio-based composite materials in automotive component production. This cradle-to-grave approach quantifies the fiber and resin production as well as material processing, use, and end of life for both a conventional glass-reinforced polypropylene component as well as a cellulose-reinforced polypropylene component. The comparison is calculated for an exterior component on a high performance vehicle. The life cycle primary energy consumption and global warming potential (GWP) are evaluated. Reduced GWP associated with the alternative component are due to the use of biomass as process energy and carbon sequestration, in addition to the alternative material component's lightweighting effect.

There have been many articles published in the last decade or so concerning the components of an electronic stability control (ESC) system, as well as numerous statistical studies that attempt to predict the effectiveness of such systems relative to crash involvement. The literature however is free from papers that discuss how engineers might develop such systems in order to achieve desired steering, handling, and stability performance. This task is complicated by the fact that stability control systems are very complex and their designs and what they can do have changed considerably over the years. These systems also differ from manufacturer to manufacturer and from vehicle to vehicle in a given maker of automobiles. In terms of ESC hardware, differences can include all the components as well as the addition or absence of roll rate sensors or active steering gears to name a few.

During the development of a new friction material, besides the interface between lining/drum is also fundamental take in account all aspects involving the attachment of the linings on the brake shoes. This paper presents an optimization approach to the development and manufacturing parameters of brake linings, applied on medium and heavy duty commercial vehicles, aiming to assure the correct specification of the riveted joint clamp forces. These evaluations were conducted based on the quality tools documents and the theoretical aspects of the product usage as well as the modeling of key elements of the referred mechanism throughout various known applications. A calculation methodology was developed based on brake geometry, its generated forces and braking reactions required for each vehicle family.

New emissions certification requirements for medium duty vehicles (MDV) meeting chassis dynamometer regulations in the 8,500 lb to 14,000 lb weight classes as well as heavy duty (HD) engine dynamometer certified applications in both the under 14,000 lb and over 14,000 lb weight classes employing large diameter exhaust pipes (up to 4″) have created new exhaust stream sampling concerns. Current On-Board-Diagnostic (OBD) dyno certified particulate matter (PM) requirements were/are 7x the standard for 2010-2012 applications with a planned phase in down to 3x the standard by 2017. Chassis certified applications undergo a similar reduction down to 1.75x the standard for 2017 model year (MY) applications. Failure detection of a Diesel Particulate Filter (DPF) at these low detection limits facilitates the need for a particulate matter sensor.

Emissions sample probes are widely used in engine and vehicle emissions development testing. Tailpipe bag summary data is used for certification, but the time-resolved (or modal) emissions data at various points along the exhaust system is extremely important in the emission control technology development process. Exhaust gas samples need to be collected at various locations along the exhaust aftertreatment system. Typically, a tube with a small diameter is inserted inside the exhaust pipe to avoid any significant effect on flow distribution. The emissions test equipment draws a gas sample from the exhaust stream at a constant volumetric flow rate (typically around 10 SLPM). The sample probe tube delivers exhaust gas from the exhaust pipe to emissions test equipment through multiple holes on the surface of tube. There can be multiple rows of holes at different axial planes along the length of the sample probe as well as multiple holes on a given axial plane of the sample probe.

The tremendous growth of complexity in automotive control system electronics in the past 30 years has driven the industry to employ ever more advanced development techniques, ranging from formally managing functional architecture to employing more sophisticated functional safety development processes. The industry now finds itself facing emerging trends that will include more vehicle electrification, connectivity, personalization, and automation. Contextual and location awareness will also play larger roles. In light of these trends, vehicle control development processes will need to continue to evolve. This paper will explore some of the challenges that automakers will face as they move to incorporate these new technologies.

In nowadays market, highlighted by global products, companies are pushed to sell products that comply with legal and customer requirements in different countries and, not unusually, different continents. In order to achieve such challenge, and pressed to reduce project and production costs, companies are spreading design centers around the world, based on regional expertise. These excellence centers must work together to benefit from synergies and local skills from different regions. Such projects are staffed by Virtual Team (BINDER, 2007), whose members barely face each other. This means teams will work frequently with people they have never met, who live on different time zones and have different cultures. As a consequence, communication is done basically through computer-based media, mainly based on emailing, and must be even clearer and more direct than with the people who work on the next desk.

Several emission performance tests like Butane Working Capacity (BWC), Cycle Life, and ORVR load tests are required for the certification of a vehicle; these tests are both expensive and time consuming. This paper presents a test process based upon analytical simulation of BWC of an automotive carbon canister in order to greatly reduce the cost incurred in physical tests. The computational model for the fixed-bed system of a carbon canister is based upon non-equilibrium, non-Isothermal, and non-adiabatic algorithm to simulate the real life loading/purging of hydrocarbon vapors from this device.

While providing significant benefits to vehicle operation and emissions, on board diagnosis comes at a cost. In many cases the additional cost comes in the form of reduced optimal performance. Often the additional cost can be mitigated by considering the OBD requirements early in the development stages. In this presentation we show these trade-offs in a number of case studies. We will point out where the ability to diagnose comes at the cost of suboptimal performance, and where system design decisions can facilate the OBD task. Presenter Michiel Van Nieuwstadt, Ford Motor Co.

This article is a new methodology to create a strong and reliable procedure to measure oil level at dealers. Most of time, commercial trucks run full loaded. Engine oil level indication systems are designed to measure oil level at that condition. However commercial trucks are assembled and sold empty and without bodies for trucks. In result of this condition, vehicles with a false indication of low engine oil level are detected at dealers' pre-delivery inspection, resulting in oil addition. This oil addition causes unnecessary costs, since vehicles are produced with maximum oil level. The methodology presented in this study analyzes and treats all variables involved in engine oil level measurements from engine production line until dealers' pre-delivery inspection

The electroluminescence, a process where light is emitted by the recombination of electrically accelerating charges (electrons and holes) on a solid state chip, is the basis of light-emitting-diodes (LEDs) technology. Until the early 90s, LEDs were considered light sources of low efficiency. Nowadays, white high power, high efficiency LED's, based upon fluorophores are extremely promising for both vehicular / automotive and machinery usages. Associate with its high efficient light production, the long life capability of these devices keep improving their performance. In this study, three models of LEDs, from two different manufacturers were used.

Diesel NOx emissions control utilizing combined Lean NOx Trap (LNT) and so-called passive or in-situ Selective Catalytic Reduction (SCR) catalyst technologies (i.e. with reductant species generated by the LNT) has been the subject of several previous papers from our laboratory [ 1 - 2 ]. The present study focuses on hydrocarbon (HC) emissions control via the same LNT+SCR catalyst technology under FTP driving conditions. HC emissions control can be as challenging as NOx control under both current and future federal and California/Green State emission standards. However, as with NOx control, the combined LNT+SCR approach offers advantages for HC emission control over LNT-only aftertreatment. The incremental conversion obtained with the SCR catalyst is shown, both on the basis of vehicle and laboratory tests, to result primarily from HC adsorbed on the SCR catalyst during rich LNT purges that reacts during subsequent lean engine operation.

Most people still remember the introduction of the IBM PC in 1981 and the first Microsoft Windows operating system in 1985. These were the pioneering technologies that started a revolution in automotive test equipment in the service bay. What was once a purely mechanical garage environment where information was published annually in large paper manuals has evolved into a highly technical computing environment. Today vehicle networks link onboard vehicle control systems with diagnostic systems and updated service information is published daily over the Internet. A lot has changed over the last twenty years, and manufacturers of diagnostic test equipment are learning to deal with the constantly evolving computing platforms and host operating systems. This paper traces the history of automotive diagnostic equipment at Ford Motor Company and shares some of the hard lessons learned from the early systems.

Urea-selective catalytic reduction (SCR) after-treatment systems are used for reducing oxides of nitrogen (NOx) emissions in medium and heavy duty diesel vehicles. This paper addresses control-oriented modeling, starting from first-principles, of SCR after-treatment systems. Appropriate simplifications are made to yield governing equations of the Urea-SCR. The resulting nonlinear partial differential equations (PDEs) are discretized and linearized to yield a family of linear finite-dimensional state-space models of the SCR at different operating points. It is further shown that this family of models can be reduced to three operating regions. Within each region, parametric dependencies of the system on physical mechanisms are derived. Further model reduction is shown to be possible in each of the three regions resulting in a second-order linear model with sufficient accuracy.