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Impact of driving patterns on fuel economy is significant in hybrid electric vehicles (HEVs). Driving patterns affect propulsion and braking power requirement of vehicles, and they play an essential role in HEV design and control optimization. Driving pattern conscious adaptive strategy can lead to further fuel economy improvement under real-world driving. This paper proposes a real-time driving pattern recognition algorithm for supervisory control under real-world conditions. The proposed algorithm uses reference real-world driving patterns parameterized from a set of representative driving cycles. The reference cycle set consists of five synthetic representative cycles following the real-world driving distance distribution in the US Midwestern region. Then, statistical approaches are used to develop pattern recognition algorithm. Driving patterns are characterized with four parameters evaluated from the driving cycle velocity profiles.

The development of PM and NOx reduction system with the combination of DOC included DPF and SCR catalyst in addition to the AOC sub-assembly for NH3 slip protection is described. DPF regeneration strategy and manual regeneration functionality are introduced with using ITH, HCI device on the EUI based EGR, VGT 12.3L diesel engine at the CVS full dilution tunnel test bench. With this system, PM and NOx emission regulation for JPNL was satisfied and DPF regeneration process under steady state condition and transient condition (JE05 mode) were successfully fulfilled. Manual regeneration process was also confirmed and HCI control strategy was validated against the heat loss during transient regeneration mode. Presenter Seung-il Moon

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.

The challenges of flex-fuel vehicle (FFV) emissions measurements have recently come to the forefront for the emissions testing community. The proliferation of ethanol blended gasoline in fractions as high as 85% has placed a new challenge in the path of accurate measures of NMHC and NMOG emissions. Test methods need modification to cope with excess amounts of water in the exhaust, assure transfer and capture of oxygenated compounds to integrated measurement systems (impinger and cartridge measurements) and provide modal emission rates of oxygenated species. Current test methods fall short of addressing these challenges. This presentation will discuss the challenges to FFV testing, modifications made to Ford Motor Company’s Vehicle Emissions Research Laboratory test cells, and demonstrate the improvements in recovery of oxygenated species from the vehicle exhaust system for both regulatory measurements and development measurements.

Selective Catalytic Reduction (SCR) catalysts have been designed to reduce NOx with the assistance of an ammonia-based reductant. Diesel Particulate Filters (DPF) have been designed to trap and eventually oxidize particulate matter (PM). Combining the SCR function within the wall of a high porosity particulate filter substrate has the potential to reduce the overall complexity of the aftertreatment system while maintaining the required NOx and PM performance. The concept, termed Selective Catalytic Reduction Filter (SCRF) was studied using a synthetic gas bench to determine the NOx conversion robustness from soot, coke, and hydrocarbon deposition. Soot deposition, coke derived from propylene exposure, and coke derived from diesel fuel exposure negatively affected the NOx conversion. The type of soot and/or coke responsible for the inhibited NOx conversion did not contribute to the SCRF backpressure.

Today's automotive and electronics technologies are evolving so rapidly that educators and industry are both challenged to re-educate the technological workforce in the new area before they are replaced with yet another generation. In early November 2009 Ford's Product Development senior management formally approved a proposal by the University of Detroit Mercy to transform 125 of Ford's “IC Engine Automotive Engineers” into “Advanced Electric Vehicle Automotive Engineers.” Two months later, the first course of the Advanced Electric Vehicle Program began in Dearborn. UDM's response to Ford's needs (and those of other OEM's and suppliers) was not only at the rate of “academic light speed,” but it involved direct collaboration of Ford's electric vehicle leaders and subject matter experts and the UDM AEV Program faculty.

The use of model-based software development in automotive applications has increased in recent years. Current vehicles contain millions of lines of code, and millions of dollars are spent each year fixing software issues. Most new features are software controlled and many times include distributed functionality, resulting in increased vehicle software content and accelerated complexity. To handle rapid change, OEMs and suppliers must work together to accelerate software development and testing. As development processes adapt to meet this challenge, model-based design can provide a solution. Model-based design is a broad development approach that is applied to a variety of applications in various industries. This paper reviews a project using the MATLAB/Simulink/Stateflow environment to complete a functional model of a low cost radio.

Engine and flow reactor experiments were conducted to determine the impact of biodiesel relative to ultra-low-sulfur diesel (ULSD) on inhibition of the selective catalytic reduction (SCR) reaction over an Fe-zeolite catalyst. Fe-zeolite SCR catalysts have the ability to adsorb and store unburned hydrocarbons (HC) at temperatures below 300°C. These stored HCs inhibit or block NOx-ammonia reaction sites at low temperatures. Although biodiesel is not a hydrocarbon, similar effects are anticipated for unburned biodiesel and its organic combustion products. Flow reactor experiments indicate that in the absence of exposure to HC or B100, NOx conversion begins at between 100° and 200°C. When exposure to unburned fuel occurs at higher temperatures (250°-400°C), the catalyst is able to adsorb a greater mass of biodiesel than of ULSD. Experiments show that when the catalyst is masked with ULSD, NOx conversion is inhibited until it is heated to 400°C.

High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

The regulations for mobile applications will become stricter in Euro 6 and further emission levels and require the use of active aftertreatment methods for NOX and particulate matter. SCR and LNT have been both used commercially for mobile NOX removal. An alternative system is based on the combination of these two technologies. Developments of catalysts and whole systems as well as final vehicle demonstrations are discussed in this study. The small and full-size catalyst development experiments resulted in PtRh/LNT with optimized noble metal loadings and Cu-SCR catalyst having a high durability and ammonia adsorption capacity. For this study, an aftertreatment system consisting of LNT plus exhaust bypass, passive SCR and engine independent reductant supply by on-board exhaust fuel reforming was developed and investigated. The concept definition considers NOX conversion, CO2 drawback and system complexity.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

Multiple-injection strategies are widely used in DI diesel engines. However, the interaction of the injection pulses is not yet fully understood. In this work, a split injection into a combustion vessel is studied by multiple optical imaging diagnostics. The vessel provides quiescent high-temperature, high-pressure ambient conditions. A common-rail injector which is equipped with a three-hole nozzle is used. The spray is visualized by Mie scattering. First and second stage of ignition are probed by formaldehyde laser-induced fluorescence (LIF) and OH* chemiluminescence imaging, respectively. In addition formation of soot is characterized by both laser-induced incandescence (LII) and natural luminosity imaging, showing that low-sooting conditions are established. These qualitative diagnostics yield ensemble-averaged, two-dimensional, time-resolved distributions of the corresponding quantities.

The most challenging part of the engine combustion development is the reduction of pollutants (e.g. CO, THC, NOx, soot, etc.) and CO2 emissions. In order to achieve this goal, new combustion techniques are required, which enable a clean and efficient combustion. For compression ignition engines, combustion rate shaping, which manipulates the injected fuel mass to control the in-cylinder pressure trace and the combustion rate itself, turned out to be a promising opportunity. One possibility to enable this technology is the usage of specially developed rate shaping injectors, which can control the injection rate continuously. A feasible solution with series injectors is the usage of multiple injections to control the injection rate and, therefore, the combustion rate. For the control of the combustion profile, a detailed injector model is required for predicting the amount of injected fuel. Simplified 0D models can easily predict single injection rates with low deviation.

Electrochemical models of lithium ion batteries are today a standard tool in the automotive industry for activities related to the computer-aided engineering design, analysis, and optimization of energy storage systems for electrified vehicles. One of the challenges in the development or use of such models is the need of detailed information on the cell and electrode geometry or properties of the electrode and electrolyte materials, which are typically unavailable or difficult to retrieve by end-users. This forces engineers to resort to “hand-tuning” of many physical and geometrical parameters, using standard cell-level characterization tests. This paper proposes a method to provide information and data on individual electrode performance that can be used to simplify the calibration process for electrochemical models.

Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

With Post Euro 6 emission standards in discussion, stricter particulate number (PN) targets as well as a decreased PN cut-off size from 23 to 10 nm are expected. Sub-23 nm particulates are considered particularly harmful to human health, but are not yet taken into account in the current vehicle certification process. Not considering sub-23 nm particulates during the development process could lead to significant additional efforts for Original Equipment Manufacturers (OEM) to comply with future Post Euro 6 PN emission limits. It is therefore essential to increase knowledge about the formation and filtration of particulates below 23 nm. In the present study, a holistic Gasoline Particulate Filter (GPF) characterization has been carried out on an engine test bench under varying boundary conditions and on a burner bench with a novel ash loading methodology.

This paper presents an evaluation of two different Vehicle to Infrastructure (V2I) applications, namely Red Light Violation Warning (RLVW) and Green Light Optimized Speed Advisory (GLOSA). The evaluation method is to first develop and use Hardware-in-the-Loop (HIL) simulator testing, followed by extension of the HIL testing to road testing using an experimental connected vehicle. The HIL simulator used in the testing is a state-of-the-art simulator that consists of the same hardware like the road side unit and traffic cabinet as is used in real intersections and allows testing of numerous different traffic and intersection geometry and timing scenarios realistically. First, the RLVW V2I algorithm is tested in the HIL simulator and then implemented in an On-Board-Unit (OBU) in our experimental vehicle and tested at real world intersections.

A wet clutch model is required in automotive propulsion system simulations for enabling robust design and control development. It commonly assumes Coulomb friction for simplicity, even though it does not represent the physics of hydrodynamic torque transfer. In practice, the Coulomb friction coefficient is treated as a tuning parameter in simulations to match vehicle data for targeted conditions. The simulations tend to deviate from actual behaviors for different drive conditions unless the friction coefficient is adjusted repeatedly. Alternatively, a complex hydrodynamic model, coupled with a surface contact model, is utilized to enhance the fidelity of system simulations for broader conditions. The theory of elastic asperity deformation is conventionally employed to model clutch surface contact. However, recent examination of friction material shows that the elastic modulus of surface fibers significantly exceeds the contact load, implying no deformation of fibers.

Exhaust manifold design is one of the more challenging tasks for the engine engineer due to the harsh thermal and severe vibration environment. Extremely high exhaust gas temperatures and dynamic loading combine to subject the manifold to high cyclic stress when the material has reduced fatigue strength due to the high temperature. A long service life before a fatigue failure is the objective in exhaust manifold design. Accumulation of fatigue damage can occur from dynamic loading and thermal loading combined. Thermal mechanical fatigue (TMF) is a primary mechanism for accumulating fatigue damage. TMF typically occurs when a vehicle driving cycle has operating conditions that repeatedly change the exhaust gas temperature between hot and cold. Another way to experience temperature cycling is through splash quenching. Splash quenching was analyzed and found to rapidly accumulate fatigue damage.

This work reports on measurement and analysis of the galvanic interaction between steel self-piercing rivets (SPRs) having several different surface conditions and magnesium alloy substrates under consideration for use in automotive structural assemblies. Rivet surface conditions included uncoated steel, conventional Zn-Sn barrel plating and variations of commercial aluminizing processes, including supplemental layers and sealants. Coating characteristics were assessed using open circuit potential (OCP) measurement, potentiodynamic polarization scanning (PDS), and electrochemical impedance spectroscopy (EIS). The degree of galvanic coupling was determined using zero-resistance ammeter (ZRA) and the scanning vibrating electrode technique (SVET), which also permitted characterization of galvanic current flows in situ.