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Honda has developed a new next-generation 3.5 L V6 gasoline engine using our latest Earth Dreams Technology. The overall design objective for the engine was to reduce CO₂ emissions and provide driving exhilaration. The Earth Dreams Technology concept is to increase fuel economy while reducing emissions. To achieve this and provide an exhilarating driving experience, 3-stage Variable Valve Timing and Lift Electronic Control (VTEC) was combined with the Variable Cylinder Management (VCM) system. This valve train technology in conjunction with Direct Injection (DI), resulted in dramatic improvements in output (a 3.3% increase) and combined mode fuel economy (20% reduction). Helping to achieve Midsize Luxury Sedan level NV, a new mount system was developed to reduce engine vibrations during three-cylinder-mode operation. In this paper, we will explain the 3-stage VTEC with VCM + DI system, friction reducing technology, and the structure and benefit of the new engine mount system.

The identification of the dominant noise sources in diesel engines and the assessment of their contribution to far-field noise is a process that can involve both fired and motored testing. In the present work, the cross-spectral densities of signals from cylinder pressure transducers, accelerometers mounted on the engine surface, and microphones (in the near and far fields), were used to identify dominant noise sources and estimate the transfer paths from the various “inputs” (i.e., the cylinder pressures, the accelerometers and the near field microphones) to the far field microphones. The method is based on singular value decomposition of the input cross-spectral matrix to relate the input measurements to independent virtual sources. The frequencies at which a particular input is strongly affected by an independent source are highlighted, and with knowledge of transducer locations, inferences can be drawn as to possible noise source mechanisms.

In computational fluid dynamic (CFD) and computational aeroacoustics (CAA) simulations, the wall surface is normally treated as a purely reflective wall. However, some surface treatments are usually applied in experiments. Thus, the acoustic simulations cannot be validated by experimental results. One of the major challenges is how to define acoustically boundary conditions in a well-posed way. In aeroacoustics analysis, impedance is a quantity to characterize reflectivity and absorption of an acoustically treated surface, which may be introduced into the numerical models as a frequency-domain boundary condition. However, CFD and CAA simulations are time-domain computations, meaning the frequency-domain impedance boundary condition cannot be adopted directly. Several methods, including the three-parameter model, the z-transform method and the reflection coefficient model, were developed.

Experimental measurements of tire tread band vibration have provided direct evidence that higher order structural-acoustic modes exist in tires, not just the well-known fundamental acoustical mode. These modes display both circumferential and radial pressure variations within the tire's air cavity. The theory governing these modes has thus been investigated. A brief recapitulation of the previously-presented coupled structural-acoustical model based on a tensioned string approach will be given, and then an improved tire-acoustical model with a ring-like shape will be introduced. In the latter model, the effects of flexural and circumferential stiffness are considered. This improved model accounts for propagating in-plane vibration in addition to the essentially structure-borne flexural wave and the essentially airborne longitudinal wave accounted for in the previous model. The longitudinal structure-borne wave “cuts on” at the tire's circumferential ring frequency.

Component sound quality is an important factor in the design of competitive diesel engines. One component noise that causes complaints is the gear rattle that originates in the front-of-engine gear train which drives the fuel pump and other accessories. The rattle is caused by repeated tooth impacts resulting from fluctuations in differential torsional acceleration of the driving gears. These impacts generate a broadband, impulsive noise that is often perceived as annoying. In most previous work, the overall sound quality of diesel engines has been considered without specifically focusing on predicting the perception of gear rattle. Gear rattle level has been quantified based on angular acceleration measurements, but those measurements can be difficult to perform. Here, the emphasis was on developing a metric based on subjective testing of the perception of gear rattle.

Over the last decade, a number of hybrid architectures have been proposed with the main goal of minimizing energy consumption of off-highway vehicles. One of the architecture subsets which has progressively gained attention is hydraulic hybrids for earth-moving equipment. Among these architectures, hydraulic hybrids with secondary-controlled drives have proven to be a reliable, implementable, and highly efficient alternative with the potential for up to 50% engine downsizing when applied to excavator truck-loading cycles. Multi-input multi-output (MIMO) robust linear control strategies have been developed by the authors' group with notable improvements on the control of the state of charge of the high pressure accumulator. Nonetheless, the challenge remains to improve the actuator position and velocity tracking.

An experiment has been developed to investigate the ignition characteristics of ultra-lean premixed H2/air mixtures by a supersonic hot jet. The hot jet is generated by combustion of a stoichiometric mixture in a small prechamber. The apparatus adopted a dual-chamber design in which a small-volume (1% of the main chamber by volume) prechamber was installed within a large-volume main chamber. A small orifice (nozzle) connects the two chambers. Spark initiated combustion inside the prechamber causes a pressure rise and pushes the gases though the nozzle, resulting in a hot jet that would ignite the lean mixture in the main chamber. Simultaneous high-speed Schlieren photography and OH* Chemiluminescence were applied to visualize the jet penetration and the ignition processes inside the main chamber. Hot Wire Pyrometry (HWP) was used to measure temperature distribution of the transient hot jet.

Green Light Optimized Speed Advisory (GLOSA) systems have the objective of providing a recommended speed to arrive at a traffic signal during the green phase of the cycle. GLOSA has been shown to decrease travel time, fuel consumption, and carbon emissions; simultaneously, it has been demonstrated to increase driver and passenger comfort. Few studies have been conducted using historical cycle-by-cycle phase probabilities to assess the performance of a speed advisory capable of recommending a speed for various traffic signal operating modes (fixed-time, semi-actuated, and fully-actuated). In this study, a GLOSA system based on phase probability is proposed. The probability is calculated prior to each trip from a previous week’s, same time-of-day (TOD) and day-of-week (DOW) period, traffic signal controller high-resolution event data.

The most common and lethal weapons against military vehicles are the improvised explosive devices (IEDs). In an explosion, critical cabin’s penetrations and high accelerations can cause serious injuries and death of military personnel. This investigation uses single and multi-fidelity Bayesian optimization (BO) to design sandwich composite armors for blast mitigation. BO is an efficient methodology to solve optimization problems that involve black-box functions. The black-box function of this work is the finite element (FE) simulation of the armor subjected to blast. The main two components of BO are the surrogate model of the black-box function and the acquisition function that guides the optimization. In this investigation, the surrogate models are Gaussian Process (GP) regression models and the acquisition function is the multi-objective expected improvement (MEI) function. Information from low and high fidelity FE models is used to train the GP surrogates.

Nowadays, the increasing number of structural high pressure die casting (HPDC) aluminum parts need to be joined with high strength steel (HSS) parts in order to reduce the weight of vehicle for fuel-economy considerations. Self-Pierce Riveting (SPR) has become one of the strongest mechanical joining solutions used in automotive industry in the past several decades. Joining HPDC parts with HSS parts can potentially cause joint quality issues, such as joint button cracks, low corrosion resistance and low joint strength. The appropriate heat treatment will be suggested to improve SPR joint quality in terms of cracks reduction. But the heat treatment can also result in the blister issue and extra time and cost consumption for HPDC parts. The relationship between the microstructure of HPDC material before and after heat treatment with the joint quality is going to be investigated and discussed for interpretation of cracks initiation and propagation during riveting.

The transportation sector is facing three revolutions: shared mobility, electrification, and autonomous driving. To inform decision making and guide smart transportation system development at the city-level, it is critical to model and evaluate how travelers will behave in these systems. Two key components in such models are (1) individual travel demands with high spatial and temporal resolutions, and (2) travelers’ sociodemographic information and trip purposes. These components impact one’s acceptance of autonomous vehicles, adoption of electric vehicles, and participation in shared mobility. Existing methods of travel demand generation either lack travelers’ demographics and trip purposes, or only generate trips at a zonal level. Higher resolution demand and sociodemographic data can enable analysis of trips’ shareability for car sharing and ride pooling and evaluation of electric vehicles’ charging needs.

Considerable improvements can be obtained in battery performance for hybrid electric vehicles (HEVs) by employing an electrochemistry-transport model based on a multi-physics modeling framework and ultrafast numerical algorithms. One important advantage of this approach over the lumped equivalent circuit (or look-up table) approach is the ability of the former to adapt to changes in design and control. In this work, we present mathematical and numerical details of our approach, and demonstrate the robustness of this battery model in simulation of short-pulse charge/discharge characteristic of HEV driving cycles under room and low temperatures.

The pressure of the combustion gas in a diesel engine is higher than that in a gasoline engine, so the cylinder head gasket that seals the combustion chamber is exposed to a severe environment. The sealability of the gaskets is affected not only by the gasket specifications, but also by the cylinder head, cylinder block, and the head bolts that clamp them. Consequently, in order to improve the performance of these gaskets, it is essential to enhance their material characteristics. Because the necessary characteristics of a gasket material are high strength and high fatigue strength, methods of realizing these enhancements were studied, and a new material was developed. It was confirmed that a gasket made using the newly developed material withstood high combustion pressure, and the gasket was used in a high performance diesel engine.

A simulation tool has been developed for predicting steering effort of a vehicle during steering power-assist system failure. The vehicle system is modeled with the inclusion of a system-level vehicle model and a steering system model that are linked together through the steering moment at the kingpin and front road wheel angle. A driver model has also been designed to provide closed-loop steering angular input to make the car follow a certain target path. The simulation model is correlated well with actual vehicle tests under various steering input and lateral acceleration conditions. Also illustrated are some examples of comparison between measured and simulated sensitivity study for selected factors.

The following computational study examines the structure of sonic hydrogen jets using inlet conditions similar to those encountered in direct-injection hydrogen engines. Cases utilizing the same mass and momentum flux while varying exit-to-chamber pressure ratios have been investigated in a constant-volume computational domain. Furthermore, subsonic versus sonic structures have been compared using both hydrogen and ethylene fuel jets. Finally, the accuracy of scaling arguments to characterize an underexpanded jet by a subsonic “equivalent jet” has been assessed. It is shown that far downstream of the expansion region, the overall jet structure conforms to expectations for self-similarity in the far-field of subsonic jets. In the near-field, variations in fuel inlet-to-chamber pressure ratios are shown to influence the mixing properties of sonic hydrogen jets. In general, higher pressure ratios result in longer shock barrel length, though numerical resolution requirements increase.

Driveline torque distribution has long been a research topic, and in the last several decades research has been directed towards enhancing on-road vehicle stability and agility through application of controllable driveline systems. This paper discusses the impact of Direct Yaw Control AWD systems (DYC AWD Systems) on the combined acceleration and turning performance as it pertains to maneuverability and stability on all road surfaces. To achieve higher levels of both safety and performance, the application of a controllable DYC AWD system capable of applying direct yaw moment to the vehicle chassis serves as a key goal to achieve the optimal result. A classification of existing driveline systems is discussed and compared to these optimal requirements. Representative on-vehicle scenarios are discussed to illustrate the impact of AWD control on the vehicle stability and maneuverability and to highlight the effects to the vehicle operator.

Vehicle-to-Vehicle (V2V) safety application research based on short range real-time communication has been researched for over a decade. Examples of V2V applications include Electronic Emergency Brake Light, Do Not Pass Warning, Lane Departure Warning, and Intersection Movement Assist. It is hoped that these applications, whether present as warning or intervention, will help reduce the incidence of traffic collisions, fatalities, injuries, and property damage. The safety benefits of these applications will likely depend on many factors, such as usability, market penetration, driver acceptance, and reliability. Some applications, such as DNPW and IMA, require a longer communication range to be effective. In addition, Dedicated Short Range Communications (DSRC) may be required to communicate without direct line of sight. The signal needs to overcome shadowing effects of other vehicles and buildings that are in the way.

Deep-hole drilling is among the most critical precision machining processes for production of high-performance discrete components. The effects of drilling with superimposed, controlled low-frequency modulation - Modulation-Assisted Machining (MAM) - on the surface textures created in deep-hole drilling (ie, gun-drilling) are discussed. In MAM, the oscillation of the drill tool creates unique surface textures by altering the burnishing action typical in conventional drilling. The effects of modulation frequency and amplitude are investigated using a modulation device for single-flute gun-drilling on a computer-controlled lathe. The experimental results for the gun-drilling of titanium alloy with modulation are compared and contrasted with conventional gun-drilling. The chip morphology and surface textures are characterized over a range of modulation conditions, and a model for predicting the surface texture is presented. Implications for production gun-drilling are discussed.

Conventional hydraulic steering systems keep improving performance and driving comfort by introducing advanced features via mechanical design. The ever increasing mechanical complexity requires the advanced modeling and simulation technology to mitigate the risks in the early stage of the development process. In this paper, we focus on advanced modeling tools environment with an example of a load sensing hydraulic steering system. The complete system architecture is presented. Analytical equations are developed for a priority valve and a steering control unit as the foundation of modeling. The full version of hydraulic steering system model is developed in Dymola platform. In order to capture interaction between steering and vehicle, the co-simulation platform between the hydraulic steering system and vehicle dynamics is established by integrating Dymola, Carsim and Simulink.

Technology is continuously being developed to prevent self-driving vehicles from crashing. That technology could also be considered for other autonomous products. Collision avoidance in automated guided systems using a light detection and ranging (LIDAR) scanner has been studied for application in low-speed autonomous Honda Power Equipment products, such as self-driving lawn mowers. The automotive application of a LIDAR scanner for autonomous driving is used for obstacle detection and offline local area. Such delineations do not exist in areas where power equipment is used, such as grass fields; therefore, identifying object height and distance is a relatively new area. For this study, a small LIDAR scanner with a resolution of 0.01 m and a measurement range of 0.05 to 40.00 m was used on a Honda self-driving lawn mower. The measurement distance data was directly processed in the scanner, enabling the drive unit to obtain distance information during actual operation.