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Under the borderline autoignition conditions experienced during cold-starting of diesel engines, the amount and composition of residual gases may play a deterministic role. Among the intermediate species produced by misfiring and partially firing cycles, formaldehyde (HCHO) is produced in significant enough amounts and is sufficiently stable to persist through the exhaust and intake strokes to kinetically affect autoignition of the following engine cycle. In this work, the effect of HCHO addition at various phases of autoignition of n-heptane-air mixtures is kinetically modeled. Results show that HCHO has a retarding effect on the earliest low-temperature heat release (LTHR) phase, largely by competition for hydroxyl (OH) radicals which inhibits fuel decomposition. Conversely, post-LTHR, the presence of HCHO accelerates the occurrence of high-temperature ignition.

Fuel wall impingement commonly occurs in small-bore diesel engines. Particularly during engine starting, when wall temperatures are low, the evaporation rate of fuel film remaining from previous cycles plays a significant role in the autoignition process that is not fully understood. Pre-injection chemiluminescence (PIC), resulting from low-temperature oxidation of evaporating fuel film and residual gases, was measured over 3200 μsec intervals at the end of the compression strokes, but prior to fuel injection during a series of starting sequences in an optical diesel engine. These experiments were conducted to determine the effect of this parameter on combustion phasing and were conducted at initial engine temperatures of 30, 40, 50 and 60°C, at swirl ratios of 2.0 and 4.5 at 1000 RPM. PIC was determined to increase and be highly correlated with combustion phasing during initial cycles of the starting sequence.

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.

Path planning and re-planning for serial 6 degree of freedom (DOF) robotic systems is challenging due to complex kinematic structure and application conditions which affects the robot's tool frame position, orientation and singularity avoidance. These three characteristics represent the key elements for production planning and layout design of the automated manufacturing systems. The robot trajectory represents series of connected points in 3D space. Each point is defined with its position and orientation related to the robot's base frames or predefined user frame. The robot will move from point to point using the desired motion type (linear, arc, or joint). The trajectory planning requires first to check if robot can reach the selected part(s). This can be simply done by placing the part(s) inside the robot's work envelope. The robot's work envelope represents a set of all robots' reachable points without considering their orientation.

Lithium-ion polymer battery has been widely used for vehicle onboard electric energy storage ranging from 12V SLI (Starting, Lighting, and Ignition), 48V mild hybrid electric, to 300V battery electric vehicle. Formulation on cell parameters acquired from minimum numbers of experiments, the modeling and simulation could be an effective approach in predicting battery performance, thermal effectiveness, and degradation. This paper describes the modeling, simulation, and validation of Lithium-Nickel-Manganese-Cobalt-Oxide (LiNiMnCoO2) based cell with 3.6V nominal voltage and 20Ah capacity. Constant current 20A, 40A, 60A, and 80A discharge tests are conducted in the computer-controlled cycler and temperature chamber. Discharging voltage curves and cell surface temperature distributions are recorded in each discharging test. A three-dimensional cell model is constructed in the COMSOL multi-physics platform based on the cell parameters.

With the mass movement toward electrification and renewable technologies, the scope of innovation of electrification has gone beyond the automotive industry into areas such as electric motorcycle applications. This paper provides a discussion of the methodology and complexities of converting an internal combustion motorcycle to an electric motorcycle. In developing this methodology, performance goals including, speed limits, range, weight, charge times, as well as riding styles will be examined and discussed. Based on the goals of this paper, parts capable of reaching the performance targets are selected accordingly. Documentation of the build process will be presented along with the constraints, pitfalls, and difficulties associated with the process of the project. The step-by-step process that is developed can be used as a guideline for future build and should be used as necessary.

Hat-sections, single and double, made of steel are frequently encountered in automotive body structural components. These components play a significant role in terms of impact energy absorption during vehicle crashes thereby protecting occupants of vehicles from severe injury. However, with the need for higher fuel economy and for compliance to stringent emission norms, auto manufacturers are looking for means to continually reduce vehicle body weight either by employing lighter materials like aluminum and fiber-reinforced plastics, or by using higher strength steel with reduced gages, or by combinations of these approaches. Unlike steel hat-sections which have been extensively reported in published literature, the axial crushing behavior of hat-sections made of fiber-reinforced composites may not have been adequately probed.

When performing trajectory planning for robotic applications, there are many aspects to consider, such as the reach conditions, joint and end-effector velocities, accelerations and jerk conditions, etc. The reach conditions are dependent on the end-effector orientations and the robot kinematic structure. The reach condition feasibility is the first consideration to be addressed prior to optimizing a solution. The ‘functional’ work space or work window represents a region of feasible reach conditions, and is a sub-set of the work envelope. It is not intuitive to define. Consequently, 2D solution approaches are proposed. The 3D travel paths are decomposed to a 2D representation via radial projections. Forward kinematic representations are employed to define a 2D boundary curve for each desired end effector orientation.

Natural fiber-reinforced composites are currently gaining increasing attention as potential substitutes to pervasive synthetic fiber-reinforced composites, particularly glass fiber-reinforced plastics (GFRP). The advantages of the former category of composites include (a) being conducive to occupational health and safety during fabrication of parts as well as handling as compared to GFRP, (b) economy especially when compared to carbon fiber-reinforced composites (CFRC), (c) biodegradability of fibers, and (d) aesthetic appeal. Jute fibers are especially relevant in this context as jute fabric has a consistent supply base with reliable mechanical properties. Recent studies have shown that components such as tubes and plates made of jute-polyester (JP) composites can have competitive performance under impact loading when compared with similar GFRP-based structures.

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.

Accident statistics have shown that older and obese occupants are less adaptable to existing vehicle occupant restraint systems than ordinary middle-aged male occupants, and tend to have higher injury risk in vehicle crashes. However, the current research on injury mechanism of aging and obese occupants in vehicle frontal impacts is scarce. This paper focuses on the optimization design method of occupant restraint system parameters for specific body type characteristics. Three parameters, namely the force limit value of the force limiter in the seat belt, pretensioner preload of the seat belt and the proportionality coefficient of mass flow rate of the inflator were used for optimization. The objective was to minimize the injury risk probability subjected to constraints of occupant injury indicator values for various body regions as specified in US-NCAP frontal impact tests requirements.

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.

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.

Speed and accuracy are the critical needs in software for the modeling and simulation of vehicle cooling systems. Currently, there are two approaches used in commercially available thermal analysis software packages: 1) detailed modeling using complex and sophisticated three-dimensional (3D) heat transfer and computational fluid dynamics, and 2) rough modeling using one-dimensional (1D) simplistic network solvers (flow and thermal) for quick prediction of flow and thermal fields. The first approach offers accuracy at the cost of speed, while the second approach provides the simulation speed, sacrificing accuracy and can possibly lead to oversimplification. Therefore, the analyst is often forced to make a choice between the two approaches, or find a way to link or couple the two methods. The linking between one-dimensional and three-dimensional models using separate software packages has been attempted and successfully accomplished for a number of years.

As a result of recent focus on the control of Low Temperature Combustion (LTC) modes, dual-fuel combustion strategies such as Reactivity Controlled Compression Ignition (RCCI) have been developed. Reactivity stratification of the auto-igniting mixture is thought to be responsible for the increase in allowable engine load compared to other LTC combustion modes such as Homogenous Charge Compression Ignition (HCCI). The current study investigates the effect of ethanol intake fuel injection on in-cylinder formaldehyde formation and stratification within an optically accessible engine operated with n-heptane direct injection using optical measurements and zero-dimensional chemical kinetic models. Images obtained by Planar Laser Induced Fluorescence (PLIF) of formaldehyde using the third harmonic of a pulsed Nd:YAG laser indicate an increase in formaldehyde heterogeneity as measured by the fluorescence signal standard deviation.

Up to now, there is no standard methodology that addresses how driver distraction is affected by perceptual demand and working memory demand - aside from visual allocation. In 2009, the Peripheral Detection Task (PDT) became a NHTSA recommended measure for driver distraction [1]. Then the PDT task was renamed as the Detection Response Task (DRT) because the International Standards Organization (ISO) has identified this task as a potential method for assessing selective attention in detection of visual, auditory, tactile and haptic events while driving. The DRT is also under consideration for adoption as an ISO standard surrogate test for driver performance for new telematics designs. The Wayne State University (WSU) driver imaging group [2, 3] improved the PDT and created the Enhanced Peripheral Detection Task I (EPDT-I) [4]. The EPDT-I is composed of a simple visual event detection task and a video of a real-world driving scene.

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.

Due to the single fuel concept implemented by the US military, the soot production of diesel engines fueled with JP-8 has important implications for military vehicle visual signature and survivability. This work compares in-cylinder soot formation and oxidation of JP-8 and ULSD in a small-bore, optical diesel engine. Experimental engine-out soot emission measurements are compared to crank-angle resolved two-color measurements of soot temperature and optical thickness, KL. A 3-D chemical kinetic-coupled CFD model with line of sight integration is employed in order to investigate the soot distribution in a 2-D projection associated with the imaging plane, as well as to aid in interpreting the third dimension along the optical depth which is not available within the experimental work. The study also examines the effect of volatility on soot emission characteristics by CFD simulation.