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Existing gasoline DI injection equipment has been modified to generate single hole pulsed gas jets. Injection experiments have been performed at combinations of 3 different pressure ratios (2 of which supercritical) respectively 3 different hole geometries (i.e. length to diameter ratios). Injection was into a pressure chamber with optical access. Injection pressures and injector hole geometry were selected to be representative of current and near-future DI natural gas engines. Each injector hole design has been characterized by measuring its discharge coefficient for different Re-levels. Transient jets produced by these injectors have been visualized using planar laser sheet Mie scattering (PLMS). For this the injected gas was seeded with small oil droplets. The corresponding flow field was measured using particle image velocimetry (PIV) laser diagnostics.

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.

The incorporation of detailed chemistry models in internal combustion engine simulations is becoming mandatory as local, globally lean, low-temperature combustion strategies are setting the path towards a more efficient and environmentally sustainable use of energy resources in transportation. In this paper, we assessed the computational efficiency of a recently developed sparse analytical Jacobian chemistry solver, namely ‘SpeedCHEM’, that features both direct and Krylov-subspace solution methods for maximum efficiency for both small and large mechanism sizes. The code was coupled with a high-dimensional clustering algorithm for grouping homogeneous reactors into clusters with similar states and reactivities, to speed-up the chemical kinetics solution in multi-dimensional combustion simulations.

This paper discusses the development and subsequent validation process of generic multi-body models for commercial vehicle combinations. The model is intended for performance assessment and improving of current and future combinations for the European road network. A second goal is to employ the model for the development of driver support systems and active steering strategies for both low speed manoeuvrability and high speed stability. The model is developed in SimMechanics, which is part of the MATLAB/Simulink software. Due to its modularity, one can quickly modify the model to the desired configuration and dimensions; therefore various multi articulation vehicle models can be created. The paper further illustrates the simplified and generic modelling methods used to build particular components such as chassis, tyres or suspension in the multibody domain.

The tradeoff between NOx emissions and combustion instability in an engine operating in the dual-fuel Reactivity Controlled Compression Ignition (RCCI) combustion mode was investigated using a combination of engine experiments and detailed CFD modeling. Experiments were performed on a single cylinder version of a General Motors/Fiat JTD 1.9L four-cylinder diesel engine. Gasoline was injected far upstream of the intake valve using an air assisted injector and fuel vaporization system and diesel was injected directly into the cylinder using a common rail injector. The timing of the diesel injection was swept from −70° ATDC to −20° ATDC while the gasoline percentage was adjusted to hold the average combustion phasing (CA50) and load (IMEPg) constant at 0.5° ATDC and 7 bar, respectively. At each operating point the variation in IMEP, peak PRR, and CA50 was calculated from the measured cylinder pressure trace and NOx, CO, soot and UHC were recorded.

The combustion timing in internal combustion engines affects the fuel consumption, in-cylinder peak pressure, engine noise and emission levels. The combination of an in-cylinder pressure sensor together with a direct injection fuel system lends itself well for cycle-to-cycle control of the combustion timing. This paper presents a method of controlling the combustion timing by the use of a cycle-to-cycle injection-timing algorithm. At each cycle the currently estimated heat-release rate is used to predict the in-cylinder pressure change due to a combustion-timing shift. The prediction is then used to obtain a cycle-to-cycle model that relates combustion timing to gross indicated mean effective pressure, max pressure and max pressure derivative. Then the injection timing that controls the combustion timing is decided by solving an optimization problem involving the model obtained.

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.

Partially premixed combustion (PPC) is a promising way to achieve high thermal efficiency and low emissions, especially by using multiple injection strategies. The mechanisms behind PPC efficiency are still to be explained and explored. In this paper, multiple injections have been used to affect the gross indicated efficiency in an optical PPC engine modified from a Volvo MD13 heavy-duty diesel engine. The aim is both to improve and impair the gross indicated efficiency to understand the differences. The combustion natural luminosity is captured by a high-speed camera, and the distribution of fuel, oxygen, and temperature during the combustion process has been further explored by CFD simulation. The results show that with the right combination of the pilot, main, and post injection the gross indicated efficiency can be improved.

An experimental investigation of non-intrusive combustion sensing was performed using a tri-axial accelerometer mounted to the engine block of a small-bore high-speed 4-cylinder compression-ignition direct-injection (CIDI) engine. This study investigates potential techniques to extract combustion features from accelerometer signals to be used for cycle-to-cycle engine control. Selection of accelerometer location and vibration axis were performed by analyzing vibration signals for three different locations along the block for all three of the accelerometer axes. A magnitude squared coherence (MSC) statistical analysis was used to select the best location and axis. Based on previous work from the literature, the vibration signal filtering was optimized, and the filtered vibration signals were analyzed. It was found that the vibration signals correlate well with the second derivative of pressure during the initial stages of combustion.

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.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

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.

Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

The modeling of fuel sprays under well-characterized conditions relevant for heavy-duty Diesel engine applications, allows for detailed analyses of individual phenomena aimed at improving emission formation and fuel consumption. However, the complexity of a reacting fuel spray under heavy-duty conditions currently prohibits direct simulation. Using a systematic approach, we extrapolate available spray models to the desired conditions without inclusion of chemical reactions. For validation, experimental techniques are utilized to characterize inert sprays of n-dodecane in a high-pressure, high-temperature (900 K) constant volume vessel with full optical access. The liquid fuel spray is studied using high-speed diffused back-illumination for conditions with different densities (22.8 and 40 kg/m3) and injection pressures (150, 80 and 160 MPa), using a 0.205-mm orifice diameter nozzle.

In a previous study, in order to investigate the effect of charge stratification on combustion behavior such as combustion efficiency and combustion phasing which also largely affects the emissions, an experiment was conducted in a heavy-duty compression ignition (CI) metal engine. The engine behavior and emission characteristics were studied in the transition from HCCI mode to PPC mode by varying the start of injection (SOI) timing. To gain more detailed information of the mixing process, in-cylinder laser diagnostic measurements, namely fuel-tracer planar laser induced fluorescence (PLIF) imaging, were conducted in an optical version of the heavy-duty CI engine mentioned above. To the authors’ best knowledge, this is the first time to perform fuel-tracer PLIF measurements in an optical engine with a close to production bowl in piston combustion chamber, under transition conditions from HCCI to PPC mode.

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.

The partially premixed combustion (PPC) concept is regarded as an intermediate process between the thoroughly mixed Homogeneous charge compression ignition (HCCI) combustion and compression ignition (CI) combustion. It’s a combination of auto-ignition mode, a fuel-rich premixed combustion mode, and a diffusion combustion mode. The concept has both high efficiency and low soot emission due to low heat losses and less stratified fuel and air mixtures compared to conventional diesel CI. The mechanisms behind the combustion process are not yet very well known. This work focuses on the efficiency and the in-cylinder process in terms of fuel distribution and the initial phase of the combustion. More specifically, double injection strategies are compared with single injection strategies to achieve different levels of stratification, ranging from HCCI to PPC like combustion as well as poor (43%) to good (49%) of gross indicated efficiency.