Showing papers by "Ford Motor Company published in 2012"

MPC-Based Energy Management of a Power-Split Hybrid Electric Vehicle

Abstract: A power-split hybrid electric vehicle (HEV) combines the advantages of both series and parallel hybrid vehicle architectures by utilizing a planetary gear set to split and combine the power produced by electric machines and a combustion engine. Because of the different modes of operation, devising a near optimal energy management strategy is quite challenging and essential for these vehicles. To improve the fuel economy of a power-split HEV, we first formulate the energy management problem as a nonlinear and constrained optimal control problem. Then two different cost functions are defined and model predictive control (MPC) strategies are utilized to obtain the power split between the combustion engine and electrical machines and the system operating points at each sample time. Simulation results on a closed-loop high-fidelity model of a power-split HEV over multiple standard drive cycles and with different controllers are presented. The results of a nonlinear MPC strategy show a noticeable improvement in fuel economy with respect to those of an available controller in the commercial Powertrain System Analysis Toolkit (PSAT) software and the other proposed methodology by the authors based on a linear time-varying MPC.

Method and system for pre-ignition control

Abstract: Methods and systems are provided for mitigating engine pre-ignition based on a feed-forward likelihood of pre-ignition and feedback from a pre-ignition event. In response to an indication of pre-ignition, a cylinder may be enriched while an engine load is limited. The enrichment may be followed by an enleanment to restore exhaust catalyst feed-gas oxygen levels. The mitigating steps may be adjusted based on engine operating conditions, a pre-ignition count, as well as the nature of the pre-ignition.

Life Cycle Greenhouse Gas Emissions of Crystalline Silicon Photovoltaic Electricity Generation

Abstract: Published scientific literature contains many studies estimating life cycle greenhouse gas (GHG) emissions of residential and utility-scale solar photovoltaics (PVs). Despite the volume of published work, variability in results hinders generalized conclusions. Most variance between studies can be attributed to differences in methods and assumptions. To clarify the published results for use in decision making and other analyses, we conduct a meta-analysis of existing studies, harmonizing key performance characteristics to produce more comparable and consistently derived results. Screening 397 life cycle assessments (LCAs) relevant to PVs yielded 13 studies on crystalline silicon (c-Si) that met minimum standards of quality, transparency, and relevance. Prior to harmonization, the median of 42 estimates of life cycle GHG emissions from those 13 LCAs was 57 grams carbon dioxide equivalent per kilowatt-hour (g CO{sub 2}-eq/kWh), with an interquartile range (IQR) of 44 to 73. After harmonizing key performance characteristics, irradiation of 1,700 kilowatt-hours per square meter per year (kWh/m{sup 2}/yr); system lifetime of 30 years; module efficiency of 13.2% or 14.0%, depending on module type; and a performance ratio of 0.75 or 0.80, depending on installation, the median estimate decreased to 45 and the IQR tightened to 39 to 49. The median estimate and variabilitymore » were reduced compared to published estimates mainly because of higher average assumptions for irradiation and system lifetime. For the sample of studies evaluated, harmonization effectively reduced variability, providing a clearer synopsis of the life cycle GHG emissions from c-Si PVs. The literature used in this harmonization neither covers all possible c-Si installations nor represents the distribution of deployed or manufactured c-Si PVs.« less

Automatic targetless extrinsic calibration of a 3D lidar and camera by maximizing mutual information

Abstract: This paper reports on a mutual information (MI) based algorithm for automatic extrinsic calibration of a 3D laser scanner and optical camera system. By using MI as the registration criterion, our method is able to work in situ without the need for any specific calibration targets, which makes it practical for in-field calibration. The calibration parameters are estimated by maximizing the mutual information obtained between the sensor-measured surface intensities. We calculate the Cramer-Rao-Lower-Bound (CRLB) and show that the sample variance of the estimated parameters empirically approaches the CRLB for a sufficient number of views. Furthermore, we compare the calibration results to independent ground-truth and observe that the mean error also empirically approaches to zero as the number of views are increased. This indicates that the proposed algorithm, in the limiting case, calculates a minimum variance unbiased (MVUB) estimate of the calibration parameters. Experimental results are presented for data collected by a vehicle mounted with a 3D laser scanner and an omnidirectional camera system.

The Dysphagia Handicap Index: Development and Validation

Abstract: Quality-of-life indicators for dysphagia provide invaluable information to the treating clinician regarding the success or failure of swallowing therapy. The purpose of this study was to develop a clinically efficient, statistically robust patient-reported outcomes tool that measures the handicapping effect of dysphagia on emotional, functional, and physical aspects of individual’s lives. 60 statements describing the handicapping effect of dysphagia were collected from patient reports and divided into subscales of physical, emotional, and functional problems. The statements were presented to 77 individuals with dysphagia. Respondents replied never, sometimes, or always to each statement and rated their self-perceived dysphagia severity on a 7-point equal-appearing interval scale. Cronbach’s α was performed to assess the internal consistency validation of the items within the questionnaire. The final questionnaire was reduced to 25 items and administered to 214 individuals with dysphagia and 74 controls. Test–retest was performed on 63 individuals with dysphagia. Cronbach’s α for the initial and final versions was strong at r = 0.96 and r = 0.94, respectively. Significant differences occurred between the dysphagia and control groups. Test–retest reliability was strong. We present a new, easy-to-complete, statistically robust, patient-reported outcomes measure for assessing the handicapping effect of dysphagia.

Predictive control for agile semi-autonomous ground vehicles using motion primitives

Abstract: This paper presents a hierarchical control framework for the obstacle avoidance of autonomous and semi-autonomous ground vehicles. The high-level planner is based on motion primitives created from a four-wheel nonlinear dynamic model. Parameterized clothoids and drifting maneuvers are used to improve vehicle agility. The low-level tracks the planned trajectory with a nonlinear Model Predictive Controller. The first part of the paper describes the proposed control architecture and methodology. The second part presents simulative and experimental results with an autonomous and semi-autonomous ground vehicle traveling at high speed on an icy surface.

Proximity switch assembly and method having adaptive time delay

Abstract: A proximity switch assembly and method for detecting activation of the proximity switch assembly is provided. The assembly includes a plurality of proximity switches each providing a sense activation field and control circuitry processing the activation field of each proximity switch to sense activation. The control circuitry monitors the signal responsive to the activation field, determines a rate of change in signal amplitude for each signal, and generates an adaptive time delay based on the control circuitry. The control circuitry further detects a peak amplitude of the signal and determines activation of the switch after expiration of the time delay following the peak amplitude detection.

The development of Model Predictive Control in automotive industry: A survey

Abstract: Model Predictive Control (MPC) is an established control technique in chemical process control, due to its capability of optimally controlling multivariable systems with constraints on plant and actuators. In recent years, the advances in MPC algorithms and design processes, the increased computational power of electronic control units, and the need for improved performance, safety and reduced emissions, have drawn considerable interest in MPC from the automotive industry. In this paper we survey the investigations of MPC in the automotive industry with particular focus on the developments at Ford Motor Company. First, we describe the basic MPC techniques used in the automotive industry, and the early exploratory investigations. Then we present three applications that have been recently prototyped in fully functional production-like vehicles, highlighting the features that make MPC a good candidate strategy for each case. We finally present our perspectives on the next challenges and future applications of MPC in the automotive industry.

Occupant interaction with vehicle system using brought-in devices

Abstract: In a first illustrative embodiment, a computer readable storage medium for storing instructions that, when executed by a processor is configure to establish communication with at least one of a plurality of handheld computing devices connected to a vehicle computing system. The processor may receive input identifying a connected device as a non-driver handheld computing device. Once connected to the vehicle-based computing system, the processor may allow the non-driver handheld computing device to control infotainment features and functions. The non-driver handheld computing device control of certain features may be represented to other occupants in the vehicle with updates being shown on a core controls display usually located in the center stack of the vehicle.

An Energy Management Controller to Optimally Trade Off Fuel Economy and Drivability for Hybrid Vehicles

Abstract: Hybrid vehicle fuel economy performance is highly sensitive to the energy management strategy used to regulate power flow among the various energy sources and sinks. Optimal non-causal solutions are easy to determine if the drive cycle is known a priori. It is very challenging to design causal controllers that yield good fuel economy for a range of possible driver behavior. Additional challenges come in the form of constraints on powertrain activity, such as shifting and starting the engine, which are commonly called “drivability” metrics and can adversely affect fuel economy. In this paper, drivability restrictions are included in a shortest path stochastic dynamic programming (SP-SDP) formulation of the real-time energy management problem for a prototype vehicle, where the drive cycle is modeled as a stationary, finite-state Markov chain. When the SP-SDP controllers are evaluated with a high-fidelity vehicle simulator over standard government drive cycles, and compared to a baseline industrial controller, they are shown to improve fuel economy more than 11% for equivalent levels of drivability. In addition, the explicit tradeoff between fuel economy and drivability is quantified for the SP-SDP controllers.

Intelligent Hybrid Vehicle Power Control—Part I: Machine Learning of Optimal Vehicle Power

Abstract: In this series of two papers, we present our research on intelligent energy management for hybrid electric vehicles (HEVs). These two papers cover the modeling of power flow in HEVs, the mathematical background of optimization in energy management in HEVs, a machine learning framework that combines dynamic programming (DP) with machine learning to learn about roadway-type- and traffic-congestion-level-specific energy optimization, machine learning algorithms, and real-time quasi-optimal control of energy flow in an HEV. This first paper presents our research on machine learning for optimal energy management in HEVs. We will present a machine learning framework ML_EMO_HEV developed for the optimization of energy management in an HEV, machine learning algorithms for predicting driving environments, and the generation of an optimal power split for a given driving environment. Experiments are conducted based on a simulated Ford Escape Hybrid vehicle model provided by Argonne National Laboratory's Powertrain Systems Analysis Toolkit (PSAT). Based on the experimental results on the test data, we can conclude that the neural networks trained under the ML_EMO_HEV framework are effective in predicting roadway type and traffic congestion levels, predicting driving trends, and learning optimal engine speed and optimal battery power from DP.

The Impact of Ethanol Fuel Blends on PM Emissions from a Light-Duty GDI Vehicle

Abstract: This study explores the influence of ethanol on particulate matter (PM) emissions from gasoline direct injection (GDI) vehicles, a technology introduced to improve fuel economy and lower CO2 emissions, but facing challenges to meet next-generation emissions standards. Because PM formation in GDI engines is sensitive to a number of operating parameters, two engine calibrations are examined to gauge the robustness of the results. As the ethanol level in gasoline increases from 0% to 20%, there is possibly a small ( 30%, there is a statistically significant 30%–45% reduction in PM mass and number emissions observed for both engine calibrations. Particle size is unaffected by ethanol level. PM composition is primarily elemental carbon; the organic fraction increases from ∼5% for E0 to 15% for E45 fuel. Engine-out hydrocarbon and NOx emissions exhibit 10–20% decreases, consistent w...

Informed mobile prefetching

Abstract: Prefetching is a double-edged sword. It can hide the latency of data transfers over poor and intermittently connected wireless networks, but the costs of prefetching in terms of increased energy and cellular data usage are potentially substantial, particularly for data prefetched incorrectly. Weighing the costs and benefits of prefetching is complex, and consequently most mobile applications employ simple but sub-optimal strategies.Rather than leave the job to applications, we argue that the underlying mobile system should provide explicit prefetching support. Our prototype, IMP, presents a simple interface that hides the complexity of the prefetching decision. IMP uses a cost-benefit analysis to decide when to prefetch data. It employs goal-directed adaptation to try to minimize application response time while meeting budgets for battery lifetime and cellular data usage. IMP opportunistically uses available networks while ensuring that prefetches do not degrade network performance for foreground activity. It tracks hit rates for past prefetches and accounts for network-specific costs in order to dynamically adapt its prefetching strategy to both the network conditions and the accuracy of application prefetch disclosures. Experiments with email and news reader applications show that IMP provides predictable usage of budgeted resources, while lowering application response time compared to the oblivious strategies used by current applications.

Life Cycle Greenhouse Gas Emissions of Thin‐film Photovoltaic Electricity Generation

Abstract: Summary We present the process and the results of harmonization of greenhouse gas (GHG) emissions during the life cycle of commercial thin-film photovoltaics (PVs), that is, amorphous silicon (a-Si), cadmium telluride (CdTe), and copper indium gallium diselenide (CIGS). We reviewed 109 studies and harmonized the estimates of GHG emissions by aligning the assumptions, parameters, and system boundaries. During the initial screening we eliminated abstracts, short conference papers, presentations without supporting documentation, and unrelated analyses; 91 studies passed this initial screening. In the primary screening we applied rigorous criteria for completeness of reporting, validity of analysis methods, and modern relevance of the PV system studied. Additionally, we examined whether the product is a commercial one, whether the production line still exists, and whether the study's core data are original or secondary. These screenings produced five studies as the best representations of the carbon footprint of modern thin-film PV technologies. These were harmonized through alignment of efficiency, irradiation, performance ratio, balance of system, and lifetime. The resulting estimates for carbon footprints are 20, 14, and 26 grams carbon dioxide equivalent per kilowatt-hour (g CO2-eq/kWh), respectively, for a-Si, CdTe, and CIGS, for ground-mount application under southwestern United States (US-SW) irradiation of 2,400 kilowatt-hours per square meter per year (kWh/m2/yr), a performance ratio of 0.8, and a lifetime of 30 years. Harmonization for the rooftop PV systems with a performance ratio of 0.75 and the same irradiation resulted in carbon footprint estimates of 21, 14, and 27 g CO2-eq/kWh, respectively, for the three technologies. This screening and harmonization rectifies previous incomplete or outdated assessments and clarifies variations in carbon footprints across studies and amongst thin-film technologies.

Reliability of a new scale for essential tremor

Abstract: Objective To determine the reliability of a new scale for the clinical assessment of essential tremor.

Model Predictive Idle Speed Control: Design, Analysis, and Experimental Evaluation

Abstract: Idle speed control is a landmark application of feedback control in automotive vehicles that continues to be of significant interest to automotive industry practitioners, since improved idle performance and robustness translate into better fuel economy, emissions and drivability. In this paper, we develop a model predictive control (MPC) strategy for regulating the engine speed to the idle speed set-point by actuating the electronic throttle and the spark timing. The MPC controller coordinates the two actuators according to a specified cost function, while explicitly taking into account constraints on the control and requirements on the acceptable engine speed range, e.g., to avoid engine stalls. Following a process proposed here for the implementation of MPC in automotive applications, an MPC controller is obtained with excellent performance and robustness as demonstrated in actual vehicle tests. In particular, the MPC controller performs better than an existing baseline controller in the vehicle, is robust to changes in operating conditions, and to different types of disturbances. It is also shown that the MPC computational complexity is well within the capability of production electronic control unit and that the improved performance achieved by the MPC controller can translate into fuel economy improvements.

Vehicle maneuvering aids

Abstract: A vehicle 1 towing a trailer 4 is fitted with three video cameras 5, 6, 7 fitted to the rear of the vehicle and on each door mirror. A view from any camera can be presented to the driver on a display 11. A predicted trailer path, calculated in a computing unit 10, is also presented to the driver on the display 11 as guide lines overlaid on the camera view. The computing unit 10 is also configured to calculate a hitch angle by tracking the position of a trailer-mounted marker in the camera view.

Effect of Adsorption and Regeneration Temperature on Irreversible Adsorption of Organic Vapors on Beaded Activated Carbon

Abstract: This paper investigates the effect of adsorption and regeneration temperature on the irreversible adsorption of a mixture of organic compounds typically emitted from automobile painting operations. Adsorption of the organic vapors mixture onto microporous beaded activated carbon (BAC) and regeneration of the saturated BAC were completed under different conditions. Results indicated that increasing the adsorption temperature from 25 to 35 or 45 °C increased heel buildup on BAC by about 30% irrespective of the regeneration temperature due to chemisorption. The adsorption capacity (for the first cycle) of the mixture onto the BAC at these three temperatures remained almost unchanged indicating chemisorption of some of these compounds onto the BAC. Increasing the regeneration temperature from 288 to 400 °C resulted in 61% reduction in the heel at all adsorption temperatures, possibly due to desorption of chemicals from narrow micropores. BET area and pore volumes of the BAC decreased proportionally to the cumulative heel. Pore size distribution and pore volume reduction confirmed that the heel was mainly built up in narrow micropores which can be occupied or blocked by some of the adsorbates.

Improved hydrogen storage and thermal conductivity in high-density MOF-5 composites

Abstract: Porous adsorbents such as MOF-5 have low thermal conductivities which can limit the performance of adsorption-based hydrogen storage systems. To improve the thermal properties of these materials, we have prepared a series of high-density MOF-5 composites containing 0–10 wt % expanded natural graphite (ENG), which serves as a thermal conduction enhancer. The addition of 10 wt % ENG to MOF-5 and compaction to 0.5 g/cm3 was previously found to increase the thermal conductivity relative to neat MOF-5 of the same density by a factor of 5. In this study, detailed measurements of the hydrogen storage behavior of MOF-5/ENG composites between 77 and 295 K are reported. We find that MOF-5 pellets with 0 wt % ENG and a density of 0.5 g/cm3 have a total volumetric hydrogen storage density at 77 K and 100 bar that is 23% larger than powder MOF-5 and 41% larger than cryo-compressed hydrogen. The addition of 10% ENG to 0.5 g/cm3 MOF-5 pellets produces only a small decrease (6%) in the total volumetric hydrogen storage c...

Thermal Percolation in Stable Graphite Suspensions

Abstract: Different from the electrical conductivity of conductive composites, the thermal conductivity usually does not have distinctive percolation characteristics. Here we report that graphite suspensions show distinct behavior in the thermal conductivity at the electrical percolation threshold, including a sharp kink at the percolation threshold, below which thermal conductivity increases rapidly while above which the rate of increase is smaller, contrary to the electrical percolation behavior. Based on microstructural and alternating current impedance spectroscopy studies, we interpret this behavior as a result of the change of interaction forces between graphite flakes when isolated clusters of graphite flakes form percolated structures. Our results shed light on the thermal conductivity enhancement mechanisms in nanofluids and have potential applications in energy systems.

Virtual vehicle entry keypad and method of use thereof

Abstract: Keypad indicia are integral with a window of a vehicle. The keypad indicia are formed using a ultra-violet (UV) fluorescent dye that is nearly invisible to a human eye until exposed to UV light. A UV light emitting device of the vehicle is configured for outputting UV light. The light emitting device is mounted for enabling the keypad indicia to be exposed to the outputted UV light thereby causing the keypad indicia to become readily visible by the human eye. An imaging device of the vehicle captures user interaction with the keypad indicia while the keypad indicia is exposed to the outputted UV light. The keypad interaction processor determines if a sequence of body part movements with respect to the keypad indicia that is captured by the imaging device during exposure of the keypad indicia to the outputted light corresponds to an access code of the vehicle.

Acute Brain MRI Findings in 120 Malawian Children with Cerebral Malaria: New Insights into an Ancient Disease

Abstract: BACKGROUND AND PURPOSE: There have been few neuroimaging studies of pediatric CM, a common often fatal tropical condition. We undertook a prospective study of pediatric CM to better characterize the MRI features of this syndrome, comparing findings in children meeting a stringent definition of CM with those in a control group who were infected with malaria but who were likely to have a nonmalarial cause of coma. MATERIALS AND METHODS: Consecutive children admitted with traditionally defined CM (parasitemia, coma, and no other coma etiology evident) were eligible for this study. The presence or absence of malaria retinopathy was determined. MRI findings in children with ret+ CM (patients) were compared with those with ret− CM (controls). Two radiologists blinded to retinopathy status jointly developed a scoring procedure for image interpretation and provided independent reviews. MRI findings were compared between patients with and without retinopathy, to assess the specificity of changes for patients with very strictly defined CM. RESULTS: Of 152 children with clinically defined CM, 120 were ret+, and 32 were ret−. Abnormalities much more common in the patients with ret+ CM were markedly increased brain volume; abnormal T2 signal intensity; and DWI abnormalities in the cortical, deep gray, and white matter structures. Focal abnormalities rarely respected arterial vascular distributions. Most of the findings in the more clinically heterogeneous ret− group were normal, and none of the abnormalities noted were more prevalent in controls. CONCLUSIONS: Distinctive MRI findings present in patients meeting a stringent definition of CM may offer insights into disease pathogenesis and treatment.

Vehicle drive matching system and method

Abstract: A vehicle includes a route collection module that collects drive history data describing a plurality of routes traveled by the vehicle and associated departure and arrival times for each of the routes, and a vehicle computing system that sends the drive history data and, in response, receives contact information for at least one driver of at least one other vehicle based on a similarity between the collected drive history data and drive history data associated with the at least one other vehicle. The vehicle further includes an interface that displays or plays the contact information to facilitate ride sharing between a driver of the vehicle and the at least one driver of the at least one other vehicle.

Information display system and method

Abstract: A vehicle display may convey vehicle trip information and vehicle range information graphically to assist drivers in qualitatively visualizing and determining whether they can successfully make it to their destination before an on-board energy source is depleted. A trip gauge may include indicators corresponding to the relative locations of the vehicle, the destination, and a projected zero charge location associated with the vehicle's range or distance to empty value. The positions of the indicators relative to one another may indicate whether the excess energy is available for the vehicle to reach the destination or whether the energy available is insufficient. A battery gauge may also convey information associated with the vehicle range. Portions of the trip gauge and the battery gauge, as well as one or more of the associated indicators, may assigned various color values for display based upon energy consumption, vehicle range, and target distance information.