Search Results

A fully flexible valve actuation (FFVA) system was developed for a single cylinder research engine to investigate high efficiency clean combustion (HECC) in a diesel engine. The main objectives of the study were to examine the emissions, performance, and combustion characteristics of the engine using late intake valve closing (LIVC) to determine the benefits and limitations of this strategy to meet Tier 2 Bin 5 NOx requirements without after-treatment. The most significant benefit of LIVC is a reduction in particulates due to the longer ignition delay time and a subsequent reduction in local fuel rich combustion zones. More than a 95% reduction in particulates was observed at some operating conditions. Combustion noise was also reduced at low and medium loads due to slower heat release. Although it is difficult to assess the fuel economy benefits of LIVC using a single cylinder engine, LIVC shows the potential to improve the fuel economy through several approaches.

The auto industry has had decades of experience with designing safe vehicles. The introduction of highly integrated features brings new challenges that require innovative adaptations of existing safety methodologies and perhaps even some completely new concepts. In this paper, we describe some of the new challenges that will be faced by all OEMs and suppliers. We also describe a set of generic top-level potential hazards that can be used as a starting point for the Preliminary Hazard Analysis (PHA) of a vehicle software-intensive motion control system. Based on our experience with the safety analysis of a system of this kind, we describe some general categories of hazard causes that are considered for software-intensive systems and can be used systematically in developing the PHA.

The GREEN-MAC-LCCP© [Global Refrigerants Energy & Environmental - Mobile Air Condition - Life Cycle Climate Performance] model described here is an evolution of a previous GM model that assesses the lifecycle energy and GHG emissions associated with the production, use and disposal of alternative refrigerants and MAC components. This new model reduces the complexity of inputs and provides a consistent output analysis. This model includes Microsoft Excel Visual Basic© code to automatically make the calculations once inputs are complete.

The purpose of this paper is to present the results of hot surface ignition (HSI) testing and American Society for Testing and Materials (ASTM) auto-ignition testing (AIT) performed on gasoline fuel mixtures containing varying levels of ethanol. With the increased consumer interest in ethanol-based fuels as a measure of reducing the United States dependence on foreign oil, the use of E85 and other ethanol/petroleum fuel blends is on the increase. While some autoignition data for summer and winter blends of gasoline on hot surfaces exist beyond the standard ASTM E659-78 test procedure [1], there is little data on ethanol-based fuels and their HSI characteristics.

Model-based design and development is emerging in the automotive industry, largely revealing its popularity in chassis control systems [1]. Although it is an efficient and accepted design tool for chassis systems, proper processes and strategies need to be in place to ensure the integrity and correctness of the production software. This paper describes software testing strategies for complex chassis control systems in a model-based environment. In detail, it highlights various testing methods for different phases, such as unit testing and integration testing. It will also address issues and challenges that were faced with each method and propose possible solutions.

This paper presents a comprehensive Matlab/Simulink-based framework that affords a rapid, systematic, and efficient engine control system development process including automated code generation. The proposed framework hinges on three essential pillars: 1 ) an accurate model for the target engine, 2) a toolset for systematic control design, and 3) a modular system architecture that enhances feature reusability and rapid algorithm deployment. The proposed framework promotes systematic model-based algorithm development and validation in virtual reality. Within this context, the framework affords integration and evaluation of the entire control system at an early development stage, seamless transitions across inherently incompatible product development stages, and rapid code generation for production target hardware.

The fierce competition and shifting consumer demands require automotive companies to be more efficient in all aspects of vehicle development and specifically in the area of embedded engine control system development. In order to reduce development cost, shorten time-to-market, and meet more stringent emission regulations without sacrificing quality, the increasingly complex control algorithms must be transportable and reusable. Within an efficient development process it is necessary that the algorithms can be seamlessly moved throughout different development stages and that they can be easily reused for different applications. In this paper, we propose a flexible engine control architecture that greatly boosts development efficiency.

Well-to-Wheels analyses are important tools that provide a rigorous examination and quantify the environmental burdens associated with fuel production and fuel consumption during the vehicle use phase. Such assessments integrate the results obtained from the Well-to-Tank (WtT) and the Tank-to-Wheels (TtW) analysis components. The purpose of this study is to provide a preliminary Tank-to-Wheels assessment of the benefits associated with the introduction of alternative powertrains and fuels in the Chinese market by the year 2015 as compared to the results obtained with conventional internal combustion engine vehicles (ICEVs). An emphasis is given on the vehicles powered by those fuels that have the potential to play a major role in the Chinese auto-sector, such as: M10, M85, E10, E85, Di-methyl Ether (DME) and Coal-to-Liquids (CTL). An important conclusion of this report is that hybridization reduces fuel consumption in all propulsion systems.

In today’s highly competitive automotive environment people are always looking to develop processes that are fast, efficient, and effective. Moving testing from expensive prototype vehicles into the laboratory is an approach being implemented for many different vehicle subsystems. Specifically a process has recently been developed at General Motors that predicts exhaust back pressure performance for a running vehicle using laboratory testing and spreadsheet calculations. This paper describes the laboratory facility and procedure, the theory behind the calculations, and the correlation between vehicle test and laboratory based results. It also comments on the benefits of the process with respect to reduction in design iterations, quicker availability of results, and money savings.

By adapting vehicle control systems to the skill level of the driver, the overall vehicle active safety provided to the driver can be further enhanced for the existing active vehicle controls, such as ABS, Traction Control, Vehicle Stability Enhancement Systems. As a follow-up to the feasibility study in [1], this paper provides some recent results on data-driven driving skill characterization. In particular, the paper presents an enhancement of discriminant features, the comparison of three different learning algorithms for recognizer design, and the performance enhancement with decision fusion. The paper concludes with the discussions of the experimental results and some of the future work.

Reducing Carbon Dioxide (CO2) emissions is one of the major challenges for automobile manufacturers. This is driven by environmental, consumer, and regulatory demands in all major regions worldwide. For conventional vehicles, a host of technologies have been applied that improve the overall efficiency of the vehicle. This reduces CO2 contributions by directly reducing the amount of energy consumed to power a vehicle. The hybrid electric vehicle (HEV) continues this trend. However, there are limits to CO2 reduction due to improvements in efficiency alone. Other major improvements are realized when the CO2 content of the energy used to motivate vehicles is reduced. With the introduction of Extended Range Electric Vehicles (E-REVs) and Plug-in HEVs (PHEVs), electric grid energy displaces petroleum. This enables the potential for significant CO2 reductions as the CO2 per unit of electrical energy is reduced over time with the improving mix of energy sources for the electrical grid.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

Diesel engines offer better fuel economy compared to their gasoline counterpart, but simultaneous control of NOx and particulates is very challenging. The blended 2-way SCR/DPF is recently emerging as a compact and cost-effective technology to reduce NOx and particulates from diesel exhaust using a single aftertreatment device. By coating SCR catalysts on and inside the walls of the conventional wall-flow filter, the 2-way SCR/DPF eliminates the volume and mass of the conventional SCR device. Compared with the conventional diesel aftertreatment system with a SCR and a DPF, the 2-way SCR/DPF technology offers the potential of significant cost saving and packaging flexibility. In this study, an engine dynamometer test cell was set up to repeatedly load and regenerate the SCR/DPF devices to mimic catalyst aging experienced during periodic high-temperature soot regenerations in the real world.

This paper presents the development of a transmission closed loop pressure control system. The objective of this system is to improve transmission pressure control accuracy by employing closed-loop technology. The control system design includes both feed forward and feedback control. The feed forward control algorithm continuously learns solenoid P-I characteristics. The closed loop feedback control has a conventional PID control with multi-level gain selections for each control channel, as well as different operating points. To further improve the system performance, Robust Optimization is carried out to determine the optimal set of control parameters and controller hardware design factors. The optimized design is verified via an L18 experiment on spin dynamometer. The design is also tested on vehicle.

An optimum combustion chamber was designed for a reverse-tumble wall-controlled gasoline direct-injection engine by systematically optimizing each design element of the combustion system. The optimization was based on fuel-economy, hydrocarbon, combustion-stability and smoke measurements at a 2000 rev/min test-point representation of road-load operating condition. The combustion-chamber design parameters that were optimized in this study included: piston-bowl depth, piston-bowl opening width, piston-bowl-volume ratio, exhaust-side squish height, bowl-lip draft angle, distance between spark-plug electrode and piston-bowl lip, spark-plug-electrode length, and injector spray-cone angle. No attempt was made to optimize the gross engine parameters such as bore and stroke or the intake system, since this study focused on optimizing a reverse-tumble wall-controlled gasoline direct-injection variant of an existing port-fueled injection engine.

Superior fuel economy was achieved for a small-displacement spark-ignition direct-injection (SIDI) engine by optimizing the stratified combustion operation. The optimization was performed using computational analyses and subsequently testing the most promising configurations experimentally. The fuel economy savings are achieved by the use of a multihole injector with novel spray shape, which allows ultra-lean stratification for a wide range of part-load operating conditions without compromising smoke and hydrocarbon emissions. In this regard, a key challenge for wall-controlled SIDI engines is the minimization of wall wetting to prevent smoke, which may require advanced injection timings, while at the same time minimizing hydrocarbon emissions, which may require retarding injection and thereby preventing over-mixing of the fuel vapor.

Full-load operation of a small-displacement spark-ignition direct-injection (SIDI) engine was thoroughly investigated by means of computational analysis and engine measurements. The performance is affected by many different factors, which can be grouped as those pertaining to volumetric efficiency, to mixing and stratification, and to system issues, respectively. Volumetric efficiency is affected by flow losses, tuning and charge cooling. Charge cooling due to spray vaporization is often touted as the most significant benefit of direct-injection on full-load performance. However, if wall wetting occurs, this benefit may be completely negated or even reversed. The fuel-air mixing is strongly affected by the injection timing and characteristics at lower engine speeds, while at higher engine speeds the intake flow dominates the transport of fuel particles and resultant vapor distribution. A higher injector flow rate enhances mixing especially at higher engine speeds.

The equipment for collecting dilute exhaust samples involves the use of bag materials (i.e., Tedlar®) that emit hydrocarbons that contaminate samples. This study identifies a list of materials and treatments to produce bags that reduce contamination. Based on the average emission rates, baked Tedlar®, Capran® treated with alumina deposition, supercritical CO2 extracted Kynar® and supercritical CO2 extracted Teflon NXT are capable of achieving the target hydrocarbon emission rate of less than 15 ppbC per 30 minutes. CO2 permeation tests were also performed. Tedlar, Capran, Kynar and Teflon NXT showed comparable average permeation rates. Based on the criteria of HC emission performance, changes in measured CO2 concentration, ease of sealing, and ease of surface treatment, none of the four materials could be distinguished from one another.

Signal delivery is the means of translating a physical parameter from a sensor measurement to the application software in the electronic controller. Signal delivery is also translating a digital word from the application software to an actuator response. In both cases, there are many transform functions along the path that will introduce noise, error, and non-linearity. This paper will discuss the importance of understanding the error and sensitivity to variation that signal delivery analysis provides. The analysis will direct design change to improve control system robustness as well as decisions for failure events.

Copolymer materials have been used for the collection of vehicle exhaust gas samples since the inception of regulatory standards. Some of these copolymers contain N,N-dimethylacetamide (DMA), which is added to improve the physical properties of the copolymer and eliminate manufacturing problems. DMA is highly soluble in water, and in effect is rinsed from the emission bag surface by humid exhaust gas samples. This study shows that DMA can thus incorrectly add to test vehicle overall hydrocarbon emissions. The DMA contribution can be significant for lower level emission vehicles. This study introduces a new bag material, KYNAR®, which significantly reduces this interference.