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Biodiesel has been widely accepted as an alternative for fossil-derived diesel fuel for use in compression ignition (CI) engines. Poor oxidative stability and cold flow properties restrict the use of biodiesel beyond current B20 blend levels (20% biodiesel in 80% ULSD) for vehicle applications. Maintaining the properties of B20 as specified by ASTM D7476-08 is important because, once out of spec, B20 may cause injector coke formation, fuel filter plugging, increased exhaust emissions, and overall loss of engine performance. While the properties of fresh B20 may be within the specifications, under engine operating and longer storage conditions B20 could deteriorate. In a diesel engine, the fuel that goes to the injector and does not enter the cylinder is recycled back to the fuel tank. The re-circulated fuel returns to the fuel tank at an elevate temperature, which can cause thermal oxidation.

The use of butanol as an alternative biofuel blend component for conventional diesel fuel has been under extensive investigation. However, some fuel properties such as cetane number and lubricity fall below the accepted values as described by the ASTM D 975 diesel specifications. Blending 10% butanol with #2 ULSD decreases the cetane number by 7% (from 41.6 to 39.0). At higher butanol blend levels, i.e., 20% v/v, the cetane number decrease cannot be compensated for; even with the addition of a 2000 ppm level commercial cetane improver. The decreased cetane number, or in other words, increased ignition delay, can be attributed to the increased blend level of low cetane butanol as well as the critical physical properties for better atomization of fuels during auto ignition such as viscosity. The kinematic viscosity dropped sharply with increasing butanol blend level up to 25 % v/v, then increased with further increase of butanol blend level.

Fuel consumption reduction on medium-duty tactical truck has and continues to be a significant initiative for the U.S. Army. The Crankshaft-Integrated-Starter-Generator (C-ISG) is one of the parallel hybrid propulsions to improve the fuel economy. The C-ISG configuration is attractive because one electric machine can be used to propel the vehicle, to start the engine, and to be function as a generator. The C-ISG has been implemented in one M1083A1 5-ton tactical cargo truck. This paper presents the experimental assessments of the C-ISG hybrid truck characteristics. The experimental assessments include all electric range for on- and off-road mission cycles and fuel consumption for the high voltage battery charging. Stationary tests related to the charging profile of the battery pack and the silent watch time duration is also conducted.

This paper presents experimental investigations of determining and analyzing low-frequency, low-SNR (Signal to Noise Ratio) noise sources of an automobile by using a new technology known as Sound Viewer. Such a task is typically very difficult to do especially at low or even negative SNR. The underlying principles behind the Sound Viewer technology consists of a passive SODAR (Sonic Detection And Ranging) and HELS (Helmholtz Equation Least Squares) method. The former enables one to determine the precise locations of multiple sound sources in 3D space simultaneously over the entire frequency range consistent with a measurement microphone in non-ideal environment, where there are random background noise and unknown interfering signals. The latter enables one to reconstruct all acoustic quantities such as the acoustic pressure, acoustic intensity, time-averaged acoustic power, radiation patterns, etc.

This paper presents experimental investigations of diagnosing and analyzing the low-frequency, low- SNR (Signal to Noise Ratio) noise sources of three motorcycles using a hybrid technology that consists of a passive SODAR (Sonic Detection And Ranging) and modified HELS (Helmholtz Equation Least Squares) methods. The former enables one to determine the precise locations of multiple sound sources in 3D space simultaneously over the entire frequency range that is consistent with a measurement microphone in non-ideal environment, where there are random background noise and unknown interfering signals. The latter enables one to reconstruct all acoustic quantities such as the acoustic pressure, acoustic intensity, time-averaged acoustic power, radiation patterns, and sound transmission paths through arbitrarily shaped vibrating structures.

Use of ethanol as gasoline replacement can contribute to the reduction of nitrogen oxide (NOx) and carbon oxide (CO) emissions. Depending on ethanol production, significant reduction of greenhouse-gas emissions is possible. Concentration of certain species, such as unburned ethanol and acetaldehyde in the engine-out emissions are known to rise when ratio of ethanol to gasoline increases in the fuel. This research explores on hydrous ethanol fueled port-fuel injection (PFI) spark ignition (SI) engine emissions that contribute to photochemical formation of ozone, or so-called ozone precursors and the precursor of peroxyacetyl nitrates (PANs). The results are compared to engine operation on gasoline. Concentration obtained by FTIR gas analyzer, and mass-specific emissions of formaldehyde (HCHO), acetaldehyde (MeCHO) and methane (CH4) under two engine speed, four load and two spark advance settings are analyzed and presented.

The Hotelling multivariate control chart and the sample generalized variance |S| are used to monitor the mean and dispersion of vehicle build vision data including the pallet information to identify the non-conforming pallets that are used in body shops of FCA US LLC assembly plants. An iterative procedure and the Gaussian mixture model (GMM) are used to rank the non-conforming or bad pallets in the order of severity. The Hotelling multivariate T2 test statistic along with Mason-Tracy-Young (MYT) signal decomposition method is used to identify the features that are affected by the bad pallets. These algorithms were implemented in the Advanced Pallet Analysis module of the FCA US software Body Shop Analysis Toolbox (BSAT). The identified bad pallets are visualized in a scatter plot with a different color for each of the top bad pallets. The run chart of an affected feature confirms the bad pallet by highlighting data points from the bad pallet.

Fast and accurate characterization of stability regions and operational range with respect to pull-in voltage and displacement is critical in the design and development of MEMS resonators and switches. This paper presents a mathematical and computational procedure for modeling and analysis of static and dynamic instabilities of capacitive microdevices employing resonant microbeams. The mathematical model consists of a nonlinear microbeam under distributed electrostatic actuation and squeeze film damping. The coupled system is described by the nonlinear beam equation and a modified compressible Reynolds equation to account for the rarefied gas in the narrow gap between the microbeam and substrate. The Differential Quadrature Method (DQM) is used to discretize partial differential equations of motion and solve for static deflection, natural frequencies, static pull-in voltage, and quality factors for various encapsulation air pressures and applied DC voltages.

The increasing interest and requirement for improved electronic engine control during the last few decades, has led to the implementation of several different sensor technologies. The process of utilizing the spark plug as a combustion probe to monitor the different combustion related parameters such as knock, misfire, Ignition timing, and air-fuel ratio have been the subject of research for some time now. The air-fuel ratio is one of the most important engine operating parameters that has an impact on the combustion process, engine-out emissions, fuel economy, indicated mean effective pressure and exhaust gas composition and temperature. Furthermore, air-fuel ratio affects the ion produced during flame kernel initiation and post flame propagation. In this paper, an investigation is made to determine the effect of air-fuel ratio on ion current, using gasoline and methane under different spark plug designs and engine operating conditions.

Shell Elements based Parametric Frame Modeling is a powerful CAE tool, which can generate robust frame design concept optimized for NVH and durability quickly when combined with Taguchi Design of Experiments. The scalability of this modeling method includes cross members length/location/section/shape, frame rail segments length/section and kick in/out/up/down angle, and access hole location & size. In the example of the D. O. E. study, more than fifteen parameters were identified and analyzed for frequency and weight. The upper and lower bounds were set for each design parameter based on package and manufacturing constraints. Sixteen Finite Element frame were generated by parametrically updating the base model, which shows this modeling method is comparatively convenient. Sensitivity of these sixteen parameters to the frequency and weight was summarized through statics, so the favorable design alternative can be achieved with the major parameters' combination.

An iterative learning control (ILC) algorithm has been developed for a test cell electro-hydraulic, fully flexible valve actuation system to track valve lift profile under steady-state and transient operation. A dynamic model of the plant was obtained from experimental data to design and verify the ILC algorithm. The ILC is implemented in a prototype controller. The learned control input for two different lift profiles can be used for engine transient tests. Simulation and bench test are conducted to verify the effectiveness and robustness of this approach. The simple structure of the ILC in implementation and low cost in computation are other crucial factors to recommend the ILC. It does not totally depend on the system model during the design procedure. Therefore, it has relatively higher robustness to perturbation and modeling errors than other control methods for repetitive tasks.

Multidisciplinary Design Optimization (MDO) is of great significance in the lean design of vehicles. The present work is concerned with the objective of cross-functional optimization (i.e. MDO) of automotive body. For simplicity, the main goal adopted here is minimizing the weight of the body meeting NVH and crash safety targets. The stated goal can be achieved following either of two different ways: classic response surface method (RSM) and practical MDO methodology espoused recently. Even though RSM seems to be able to find a design point which satisfies the constraints, the problem is with the time associated with running such CAE algorithms that can provide a single optimal solution for multi-disciplinary areas such as NVH and crash safety.

Today’s advanced vehicles have high degree of interaction due to numerous sensors, actuators and also with complex communication within the control units. In order to hack a vehicle, it has to be within a certain range of communication. Here, we discuss the On-Board Diagnostic (OBD) regulations for next generation BEV/HEV, its vulnerabilities and cybersecurity threats that come with hacking. We propose three cybersecurity attack detection and defense methods: Cyber-Attack detection algorithm, Time-Based CAN Intrusion Detection Method and, Feistel Cipher Block Method. These control methods autonomously diagnose a cybersecurity problem in a vehicle’s onboard system using an OBD interface, such as OBD-II when a fault caused by a cyberattack is detected, All of this is achieved in an internal communication network structure. The results discussed here focus on the first detection method that is Cyber-Attack detection algorithm.

This study evaluates the performance of an indirect injection (IDI) diesel engine fueled with cotton seed biodiesel while assessing the engine's multi-fuel capability. Millions of tons of cotton seeds are available in the south of the US every year and approximately 10% of oil contained in the seeds can be extracted and transesterified. An investigation of combustion, emissions, and efficiency was performed using mass ratios of 20-50% cotton seed biodiesel (CS20 and CS50) in ultra-low sulfur diesel #2 (ULSD#2). Each investigation was run at 2400 rpm with loads of 4.2 - 6.3 IMEP and compared to the reference fuel ULDS#2. The ignition delay ranged in a narrow interval of 0.8-0.97ms across the blends and the heat release rate showed comparable values and trends for all fuel blends. The maximum volume averaged cylinder temperature increased by approximately 100K with each increase in 1 bar IMEP load but the maximum remained constants across the blends.

Experiments were conducted on a single cylinder engine to measure the ionization current across the spark plug electrodes as a function of key operating parameters including air/fuel ratio. A unique ignition circuit was adapted to measure the ion current as early as 300 microseconds after the initiation of spark discharge. A strong relationship between air/fuel ratio and features of the measured ion current was observed. This relationship can be exploited via relatively simple algorithms in a wide range of electronic engine control strategies. Measurements of spark plug ion current for approximating air/fuel ratio may be especially useful for use with low cost mixture control in small engine applications. Cylinder-to-cylinder mixture balancing in conjunction with a global exhaust gas oxygen sensor is another promising application of spark plug ion current measurement.

The piston secondary motion is an important phenomenon in internal combustion (IC) engine. It occurs due to the piston transverse and rotational motion during piston reciprocating motion. The piston secondary motion results in engine friction and engine noise. There has been lot of research activities going on in piston secondary motion using both analytical models and experimental studies. These studies are aimed at reducing the engine friction as well as the noise generated due to piston secondary motion. The aim of this paper is to compile the research actives carried out on the piston secondary motion and discuss the possible research opportunities for reducing the IC engine piston secondary motion.

The focus of this study is to determine the effect of using B-20 (a blend of 20% soybean methyl ester biodiesel and 80% ultra low sulfur diesel fuel) on the combustion process, performance and exhaust emissions in a High Speed Direct Injection (HSDI) diesel engine equipped with a common rail injection system. The engine was operated under simulated turbocharged conditions with 3-bar indicated mean effective pressure and 1500 rpm engine speed. The experiments covered a wide range of injection pressures and EGR rates. The rate of heat release trace has been analyzed in details to determine the effect of the properties of biodiesel on auto ignition and combustion processes and their impact on engine out emissions. The results and the conclusions are supported by a statistical analysis of data that provides a quantitative significance of the effects of the two fuels on engine out emissions.

In a frontal automotive crash, the driver's foot is usually stepping on the brake pedal as an instinctive response to avoid a collision. The tensile force generated in the Achilles tendon produces a compressive preload on the tibia. If there is intrusion of the toe board after the crash, an additional external force is applied to the driver's foot. A series of dynamic impact tests using human cadaveric specimens was conducted to investigate the combined effect of muscle preloading and external force. A constant tendon force was applied to the calcaneus while an external impact force was applied to the forefoot by a rigid pendulum. Preloading the tibia significantly increased the tibial axial force and the combination of these forces resulted in five tibial pylon fractures out of sixteen specimens.

As diesel emission regulations continue to increase, the use of exhaust aftertreatment systems containing, for example the diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) will become necessary in order to meet these stringent emission requirements. The addition of a DOC and DPF in conjunction with utilizing biodiesel fuels requires extensive research to study the implications that biodiesel blends have on emissions as well as to examine the effect on aftertreatment devices. The proceeding work discusses results from a 2006 VM Motori four-cylinder 2.8L direct injection diesel engine coupled with a diesel oxidation catalyst and catalyzed diesel particulate filter. Tests were done using ultra low sulfur diesel fuel blended with 20% choice white grease biodiesel fuel to evaluate the effects of biodiesel emission products on the performance and effectiveness of the aftertreatment devices and the effect of low temperature combustion modes.

The effects of different blends of Soybean Methyl Ester (biodiesel) and ultra low sulfur diesel (ULSD) fuel: B-00 (ULSD), B-20, B-40, B-60, B-80 and B-100 (biodiesel); on autoignition, combustion, performance, and engine out emissions of different species including particulate matter (PM) in the exhaust, were investigated in a single-cylinder, high speed direct injection (HSDI) diesel engine equipped with a common rail injection system. The engine was operated at 1500 rpm under simulated turbocharged conditions at 5 bar IMEP load with varied injection pressures at a medium swirl of 3.77 w ithout EGR. Analysis of test results was done to determine the role of biodiesel percentage in the fuel blend on the basic thermodynamic and combustion processes under fuel injection pressures ranging from 600 bar to 1200 bar.