Search Results

An automated process was developed for the calibration of numerical aftertreatment models. The chemical kinetic mechanism examined in this case was part of a simplified SCR model. The process adopted for calibrating the SCR model was based on a micro-population multi-objective genetic algorithm. The algorithm developed was used to calibrate the SCR model using data derived from another, more detailed model to ensure that the evaluation focused only on the effectiveness of the calibration process and was not affected by issues of experimental inaccuracies or details of the model chemistry involved.

In order to detect degradation of engine oil lubricant, bench testing along with a number of diesel-powered Ford trucks were instruments and tested. The purpose of the bench testing was primarily to determine performance aspects such as repeatability, hysteresis effects and so on. Vehicle testing was conducted by designing and installing a separate oil reservoir along with a circulation system which was mounted in the vicinity of the oil pan. An innovative oil sensor was directly installed on the reservoir which can measure five (5) independent oil parameters (viscosity, density, permittivity, conductance, temperature). In addition, the concept is capable of detecting the oil level continuously during normal engine operation. The sensing system consists of an ultrasonic transducer for the oil level detection as well as a Tuning Fork mechanical resonator for the oil condition measurement.

A small hybrid system was developed for the 2009 model hybrid vehicle. The Intelligent Power Unit (IPU), which consists of a high-voltage battery and a Power Control Unit (PCU), occupies 19% less volume and is 28% lighter than the previous model(1). In order to reduce the size and weight of the IPU, the number of nickel-metal hydride battery modules was reduced, enabling the battery box to be made smaller and lighter. In order to provide the necessary output with fewer battery modules, the length of the battery electrodes was increased, thus raising the output from each battery module. The volume and weight of the PCU were reduced by integrating the inverter, DC-DC converter, and ECU into a single package. The size reduction of the IPU enabled the IPU to be installed at the bottom of the luggage compartment. As a result, the available space in the luggage compartment is the same as that of a conventional vehicle.

Engine operating strategies typically geared towards higher fuel economy and lower NOx widely affect exhaust composition and temperature. These exhaust variables critically drive the performance of After Treatment (AT) components, and hence should guide their screening and selection. Towards this end, the effect of H2 level in diesel exhaust on the performance of a Diesel Oxidation Catalyst (DOC) was studied using flow reactor experiments, vehicle emission measurements and mathematical models. Vehicle chassis dynamometer data showed that exhaust from light-duty and heavy-duty diesel trucks contained very little to almost no H2 (FTP average CO/H2 ∼ 40 to 70) as compared to that of a gasoline car exhaust (FTP average CO/H2 ∼ 3). Two identical flow reactor experiments, one with H2 (at CO/H2 ∼ 3) and another with no H2 in the feed were designed to screen DOCs under simulated feed gas conditions that mimicked these two extremes in the exhaust H2 levels.

A thorough understanding of vehicle exhaust aftertreatment system performance requires time-resolved emissions measurements that accurately follow driving transients, and that are correctly time-aligned with exhaust temperature and flow measurements. The transient response of conventional gas analyzers is characterized by both a time delay and an attenuation of high-frequency signal components. The distortion that this imposes on transient emissions measurements causes significant errors in instantaneous calculations of aftertreatment system efficiency, and thus in modal mass analysis. This creates difficulties in mathematical modeling of emissions system performance and in optimization of powertrain control strategies, leading to suboptimal aftertreatment system designs. A mathematical method is presented which improves the response time of emissions measurements. This begins with development of a model of gas transport and mixing within the sampling and measurement system.

Since 1992, Toyota Motor Corporation (TMC) has been working on the development of fuel cell system technology. TMC is designing principal components in-house, including fuel cell stacks, high-pressure hydrogen storage tank systems, and hybrid systems. TMC developed the ‘02 model TOYOTA FCHV, the world-first market-ready fuel cell vehicle, and started limited lease of the vehicles in December 2002. In June 2008, TMC developed a new TOYOTA FCHV-adv which obtained vehicle type certification in Japan, and is currently available for leasing in Japan and the United States. In the development of the TOYOTA FCHV-adv, TMC has improved the cruising range and cold start/drive capability from the previous TOYOTA FCHV. The TOYOTA FCHV-adv has achieved an actual cruising range of over 500 km, which is equivalent to that of current gasoline vehicles. In addition, the TOYOTA FCHV-adv has proven starting/driving capability at -30°C temperature.

A Lunar habitat will be highly sensored and generate large amounts of data or telemetry. For this data to be useful to humans monitoring these systems and to automated algorithms controlling these systems it will need to be converted into more abstract data. This abstracted data will reflect the trends, states and characteristics of the systems and their environments. Currently this data abstraction process is manual and ad hoc. We are developing a Data Abstraction Architecture (DAA) that allows engineers to design software processes that iteratively convert habitat data into higher and higher levels of abstraction. The DAA is a series of mathematical or logical transformations of telemetry data to provide appropriate inputs from a hardware system to a hardware system controller, system engineer, or crew. The DAA also formalizes the relationships between data and control and the relationships between the data themselves.

Piezoelectric self-sensing allows to measure frequency response functions of dynamical systems with one single piezoelectric element. This piezoceramics is used as actuator and sensor simultaneously. In this study, a model-based piezoelectric self-sensing technique is presented to obtain potential squealing frequencies of an automotive disc brake. The frequency-response function of the brake system is obtained during operation by measuring the current flowing through the piezoelectric element while the piezoelectric element is driven by a harmonic voltage signal with constant amplitude. The current flow is composed of the part which is required to drive the piezoelectric element as an actuator and a second part which is the sensor signal that is proportional to the vibration amplitude of the attached mechanical system. Typically the first part is dominant and the influence of the mechanical system is marginal.

This paper describes the joint development by Tenneco and Pi Shurlok of a complete diesel engine aftertreatment system for controlling particulate matter emissions. The system consists of a DOC, DPF, sensors, controller and an exhaust fuel injection system to allow active DPF regeneration. The mechanical components were designed for flow uniformity, low backpressure and component durability. The overall package is intended as a complete PM control system solution for OEMs, which does not require any significant additions to the OEM's engine control strategies and minimizes integration complexity. Thus, to make it easier to adapt to different engine platforms, ranging from small off-road vehicle engines to large locomotive engines, model-based control algorithms were developed in preference to map-based controls.

The presented paper introduces the new software complex aimed at simulation of the riveting process as applied to aircraft parts. The software complex implements the novel mathematical model based on minimization of the potential energy. The paper gives the detailed description of the mathematical model and particularizes the main features of the software. The physical and numerical tests aimed at validation of the software are also described in the paper.

The electrical and mechanical failures (such as bearing and winding failures) combine to cause premature failures of the generators, which become a flight safety issue forcing the crew to land as soon as practical. Currently, diagnostic / prognostic technologies are not implemented for aircraft generators where repairs are time consuming and its costs are high. This paper presents the development of feature extraction and diagnostic algorithms to ultimately 1) differentiate between these failure modes and normal aircraft operational modes; and 2) determine the degree of damage of a generator. Electrical signature analysis based features were developed to distinguish between healthy and degraded generators while taking into account their operating conditions. The diagnostic algorithms were developed to have a high fault / high-hour detection rate along with a low false alarm rate.

Requirements analysis for aircraft simulators is often driven by photographs and videos of the actual aircraft. An engineer may gather and organize hundreds or even thousands of source photos of various instruments and devices unique to the aircraft. Managing all of this source information and referencing it to generate software requirements can be challenging and time-consuming. This paper explores Content Based Image Retrieval (CBIR) techniques to automatically process and search those images to generate basic requirements and to facilitate reuse. An unsupervised clustering algorithm groups source images based on minimal user input. Images processed in this way can also be queried by image similarity, thereby allowing project managers to find common source material among projects. The effectiveness of these techniques is demonstrated on an example cockpit.

Complexity and nonlinearity of engines makes precise first principle engine models often difficult to obtain, as for instance for emissions. System identification is a well known possible alternative, successfully used in several automotive applications. In most cases system identification is concerned with the estimation of the unknown parameters of a known set of equations. Unfortunately, for many engine subsystems, there is no sufficiently precise or real time suitable model. This paper presents a sequential algorithm which allows to derive real time suitable models on line by a combination of model structure hypothesis of increasing complexity and an associated optimal input design and selection process. This paper introduces the method and shows its use both for a rather simple and a very difficult engine identification task, a dynamical model of the airpath of a Diesel engine and a dynamical model of nitrogen oxides and particulate matter.

After launch and activation activities, the Columbus module started its operational life on February 2008 providing resources to the internal and external experiments. In March 2008 two US Payloads were successfully installed into Columbus Module: Microgravity Sciences Glovebox (MSG) and a US payload of the Express rack family, Express Rack 3, carrying the European Modular Cultivation System (EMCS) experiment. They were delivered to the European laboratory from the US laboratory and followed few months later by similar racks; Human Research Facility 1 (HRF1) and HRF2. The following paper provides an overview of US Payloads, giving their main features and experiments run inside Columbus on year 2008. Flight issues, mainly on the hydraulic side are also discussed. Engineering evaluations released to the flight control team, telemetry data, and relevant mathematical models predictions are described providing a background material for the adopted work-around solutions.

Aviation battery maintenance is trending toward on-condition maintenance. Nickel-Cadmium (NiCd), Valve Regulated Lead-Acid (VRLA), or prospective Li-ion batteries are used to start engines, provide emergency back-up power, and assure ground power capability for maintenance and pre-flight checkout. As these functions are mission essential, State of Health (SoH) recognition is critical. SoH includes information regarding battery energy, power and residual cycle life. This paper describes an SoH recognition technique for on-board aviation batteries and presents a passive diagnostic device (PDD). The PDD monitors on-board system battery current, voltage and ambient temperature and utilizes no active signals to the battery which can be restricted or even prohibited in order to avoid any interference with the vehicle electrical system.

The Cessna Citation CJ4, certified on March 12, 2010, is believed to be the first civil aircraft with a Lithium Ion main battery. The 26.4VDC, 44Ah Lithium Ion main battery weighs 54 lbs, a 35% weight saving over a Nickel-Cadmium battery. Using phosphate-based Lithium Ion cells, which have no positive feedback thermal runaway failure mode, system integration of the battery and aircraft architecture design is simpler. Electronics and software are needed to optimize life only, not to ensure safety. Emergency discharge with failed electronics is enabled with the selection of a less volatile chemistry, the use of an analog Module Management System for cell balancing and protection, and the use of a microcontroller-based digital Central Monitoring System that reports health. System safety failure hazard assessment is considered Major, and the battery software is certified to the requirements of RTCA DO-178B, Design Assurance Level C.

The focus of this research is to perform a detailed investigation of the tradeoffs between mass, efficiency, service factor (SF), power factor (PF), and cost of commercially available induction machines (IMs). To support this effort, data from a large number of IMs is used to establish Pareto-optimal fronts between these competing objectives. From the Pareto-optimal fronts, relatively straightforward models are formulated for the mass versus loss, cost versus loss, SF versus mass, PF versus cost. Parameters of the models are obtained using a genetic algorithm (GA).

This paper develops a novel integrated navigational system for autonomous vehicle motion control. Vehicle control is defined in terms of the required vehicle steering angle, rate of steering change and speed. This paper proposes predictive control in the image plane. The proposed predictive control enables the navigation on the desired path, reduces the control complexity and increases the application space for multiple types of vehicles. The paper investigates vehicle control stability; especially in scenarios containing varying curvature turns and variable vehicle speeds. The primary emphasis of this paper is on vehicle control rather than scene analysis. To demonstrate the proposed vehicle control, a computer vision based multi-lane detection algorithm is introduced. The control strategy is applied such that the vehicle maintains position within the lane boundaries. Stability of the control algorithm is tested and demonstrated in multiple scenarios using 3-D simulation results.

Lithium-ion (Li-ion) batteries are becoming widely used high-energy sources and a replacement of the Nickel Metal Hydride batteries in electric vehicles (EV), hybrid electric vehicles (HEV) and plug-in hybrid electric vehicles (PHEV). Because of their light weight and high energy density, Li-ion cells can significantly reduce the weight and volume of the battery packs for EVs, HEVs and PHEVs. Some materials in the Li-ion cells have low thermal stabilities and they may become thermally unstable when their working temperature becomes higher than the upper limit of allowed operating temperature range. Thus, the cell working temperature has a significant impact on the life of Li-ion batteries. A proper control of the cell working temperature is crucial to the safety of the battery system and improving the battery life. This paper outlines an approach for the thermal analysis of Li-ion battery cells and modules.

Electric vehicle development is at a crossroads. Consumers want vehicles that offer the same size, performance, range, reliability and cost as their current vehicles. OEMs must make a profit, and the government requires compliance with emissions standards. The result - low volume, compromised vehicles that consumers don't want, with questionable longevity and minimal profitability. In-wheel motor technology offers a solution to these problems; providing power equivalent to ICE alternatives in a package that does not invade chassis, passenger and cargo space. At the same time in-wheel motors can reduce vehicle part count, complexity and cost, feature integrated power electronics, give complete design freedom and the potential for increased regenerative braking (reducing battery size and cost, or increasing range).