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As the piston pin works under significant mechanical load, it is susceptible to wear, seizure, and structural failure, especially in heavy duty internal combustion engines. It has been found that the friction loss associated with the pin is comparable to that of the piston, and can be reduced when the interface geometry is properly modified. However, the mechanism that leads to such friction reduction, as well as the approaches towards further improvement, remain unknown. This work develops a piston pin lubrication model capable of simulating the interaction between the pin, the piston, and the connecting rod. The model integrates dynamics, solid contact, oil transport, and lubrication theory, and applies an efficient numerical scheme with second order accuracy to solve the highly stiff equations. As a first approach, the current model assumes every component to be rigid.

The increasing use of diesel and gasoline particulate filters requires advanced on-board diagnostics (OBD) to prevent and detect filter failures and malfunctions. Early detection of upstream (engine-out) malfunctions is paramount to preventing irreversible damage to downstream aftertreatment system components. Such early detection can mitigate the failure of the particulate filter resulting in the escape of emissions exceeding permissible limits and extend the component life. However, despite best efforts at early detection and filter failure prevention, the OBD system must also be able to detect filter failures when they occur. In this study, radio frequency (RF) sensors were used to directly monitor the particulate filter state of health for both gasoline particulate filter (GPF) and diesel particulate filter (DPF) applications.

The adoption of electric vehicles (EVs) has been announced worldwide with the aim of reducing CO2 emissions. However, a significant increase in electricity demand by EVs might impact the stable operation of the existing power grid. Meanwhile, EV charging is acceptable to most users if it is completed by the time of the next driving event. From the viewpoint of power grid operators, flexibility for shifting the timing of EV charging would be advantageous, including making effective use of renewable energy. In this work, an EV model and simulation tool were developed to make clear how the total charging demand of all EVs in use will be influenced by future EV specifications (e.g., charge power) and installation of charging infrastructure. Among the most influential factors, EV charging behavior according to use cases and regional characteristics were statistically analyzed based on the real-world usage data of over 14, 000 EVs and incorporated in the simulation tool.

This paper proposes a method of estimating road friction and tire slip angle in a cornering maneuver. The method can estimate front tire road friction accurately at low lateral acceleration because it is based on the tire self-aligning torque (SAT) that exhibits high sensitivity to road friction at low slip angles. Road friction and tire slip angle, which are mutually interdependent, are estimated simultaneously using an extended Kalman filter designed around a model describing the relationship between road friction and SAT and a vehicle lateral dynamic model. The front tire SAT is calculated with a mathematical model that describes the torque transmission characteristics from the electric power steering torque to SAT. Therefore, the proposed method is readily applicable to production vehicles. Results of an experimental study show that the change in road friction is instantaneously estimated at low lateral acceleration.

A robotic driver has been designed on the basis of an analysis of a human driver's action in following a given driving schedule. The self-learning algorithm enables the robot to learn the vehicle characteristics without human intervention. Based on learned relationships, the robotic driver can determine an appropriate accelerator position and execute other operations through sophisticated calculations using the future scheduled vehicle speed and vehicle characteristics data. Compensation is also provided to minimize vehicle speed error. The robotic driver can reproduce the same types of exhaust emission and fuel economy data obtained with human drivers with good repeatability. It doesn't require long preparation time. Thereby making it possible to reduce experimentation work in the vehicle development process while providing good accuracy and reliability.

The thermal fatigue resistance of engine exhaust system parts has conventionally been evaluated in thermal fatigue tests conducted with a restrained specimen. However, the test results have not always been consistent with data obtained in engine endurance tests. Two new evaluation methods have been developed to overcome this problem. One is a method of predicting thermal fatigue life on the basis of nonlinear elastic and plastic thermal analyses performed with a finite element model and the ABAQUS program. The other is a method of evaluating exhaust system parts using an exhaust system simulator. This paper describes the concepts underlying the two methods and their relative advantages.

This study focused on European NCAP activities of introducing a new head protection evaluation procedure, as proposed by BASt (Federal Highway Research Institute - GERMANY). Various kinds of E-bikes are available in the market, ranging from E-bikes that have a small motor to assist the rider’s pedal-power i.e., pedelecs to somewhat more powerful E-bikes which is similar to a moped-style scooter. This paper focused on identifying the factors influencing bicyclist head kinematics during bicycle vs. passenger vehicle (PV) collisions at the intersection. Two AM50 bicyclist FE models are developed using i) GHBMC Human Body Model (HBM) and ii) WorldSID (WS) side impact dummy. Head kinematics of bicyclists of pedal-assist E-bike and normal bike were compared using CAE simulation. It is found that the vehicle’s impact velocity, type of bicycle, the mass of E-bike and bicycle traveling speed will influence the head kinematics.

Many studies have been reported concerning fundamental tribological research aimed at reducing the severe valve train wear that occurs in internal combustion engines. In this paper, cam follower wear was theoretically and experimentally analyzed at the material development stage. Statistical methods have been applied to practical use in determining the material properties quantitatively. Based on the results, a method for predicting cam follower wear has been derived which has made it possible to develop new valve train systems more efficiently. Further, a guideline for developing new wear resistant materials was also clarified. Finally, the precision high chrominum cast iron rocker arm is described, along with its application to a new NISSAN high-performance 4-cylinder DOHC engine, as an example of the use of this method to develop new wear-resistant materials.

With SUVs and minivans accounting for a larger share of the US market in the past decade, rollover accidents have drawn greater attention, leading to more active research from different perspectives. This ranges from investigations for elucidating the basic causes and mechanisms of rollover accidents to studies of more advanced occupant protection measures. As the phenomenon of a rollover accident is longer in duration than frontal, side or rear impacts, it is relatively difficult [1] to simulate such accidents for experimental verification and also for proper evaluation of occupant restraint system performance. In this work, we focused on the trip-over type, which occurs most frequently, and performed simulations to reproduce real-world rollover accidents by combining PC-Crash and FEA.

The probability or risk of traffic accidents must be estimated quantitatively in order to implement effective traffic safety measures. In this study, various statistical data and probability theory were used to examine a method for predicting the risk of crossing-collisions, representing a typical type of accident at intersections in Japan. Crossing-collisions are caused by a variety of factors, including the road geometry and traffic environment at intersections and the awareness and intentions of the drivers of the striking and struck vehicles. Bayes' theorem was applied to find the accident probability of each factor separately. Specifically, the probability of various factors being present at the time of a crossing-collision was estimated on the basis of traffic accident data and observation survey data.

This paper presents a new method for calculating optical flow using data from a high frame-rate camera. We focused on a feature of image data captured with a high frame-rate camera in which objects do not move more than one pixel between successive frames. This approach eliminates repetitive processing for object identification among frames taken at different sampling times. High-speed processing hardware architecture was designed with sequential processing only, and the algorithm was implemented in a field programmable gate array. The resultant unit can calculate optical flow for a 640×120 pixel size image with a 480-Hz processing cycle and 0.5-μsec processing latency.

An extravehicular activity (EVA) path-planning and navigation tool, called the Mission Planner, has been developed to assist with pre-mission planning, scenario simulation, real-time navigation, and contingency replanning during astronaut EVAs, The Mission Planner calculates the most efficient path between user-specified waypoints. Efficiency is based on an exploration cost algorithm, which is a function of the estimated astronaut metabolic rate. Selection of waypoints and visualization of the generated path are realized within a 3D mapping interface through terrain elevation models. The Mission Planner is also capable of computing the most efficient path back home from any point along the path.

This paper describes the method used to design the basic control algorithm of a lane-keeping support system that is intended to assist the driver's steering action. Lane-keeping control has been designed with steering torque as the control input without providing a minor loop for the steering angle. This approach was taken in order to achieve an optimum balance of lane-keeping control, ease of steering intervention by the driver and robustness. The servo control system was designed on the basis of H2 control theory. Robustness against disturbances, vehicle nonlinearity and parameter variation was confirmed by μ - analysis. The results of computer simulations and driving tests have confirmed that the control system designed with this method provides the intended performance.

Recently tailored blank sheets are widely and very often applied to car body's panels in order to reduce weight and number of automobile parts. The tailored blank sheets are produced by welding more than two metal sheets. The gap between edges of blank sheets before laser welding should be controlled for obtaining good quality tailored blank sheets. Therefore control of gap within 0.1mm between batting two blank sheets for production is one of main subjects for producing tailored blank sheets. This report presents not only a new mechanism on gap control but also a development of Finite Element Method (FEM) analysis for prediction of gap. The new mechanism has been applied successfully to produce good quality tailored blank sheets. The gap prediction simulation can reduce the time for gap control apparatus design.

Various prediction methods have been proposed for evaluating the fatigue life of welded joints by combining finite element analysis (FEA) with an experimental database. However, to obtain more universal and accurate fatigue life predictions, it is necessary to have criteria for making integrated evaluations of the fatigue strength of welded joints. This paper presents a study that focuses on the local cyclic plastic zone size (ω*) as the criterion of fatigue strength and investigates its validity. The definition of ω* was given by the relationship between the stress state at the notch tip and the elastic strain which was defined along the strain-life fatigue curve (ε - N diagram) of a base metal. As a result of using ω*, it was found that an integrated fatigue life prediction was possible to a certain extent for notch and arc-welded joint specimens.

This paper presents the results of a strength analysis of a newly developed steel structure featuring a special cross section achieved with the hydroforming process that minimizes the influence of springback. This structure has been developed in pursuit of further weight reductions for the steel body in white. A steel tube with tensile strength of 590 MPa was fabricated in a low-pressure hydroforming operation, resulting in thicker side walls. The results of a three-point bending test showed that the bending strength of the new steel structure with thicker side walls was substantially increased. A finite element crush analysis based on the results of a forming analysis was shown to be effective in predicting the strength of the structure, including the effect of work hardening.

Hydrofrorming is an efficient forming process to produce automotive parts for reducing weight of cars. In order to reduce the period of development of hydrofoming parts, numerical simulation using FEM is applied to evaluate formability. A pipe needs to be bent before hydroforming for forming complicated shape parts. A pipe bending process is also necessary to FEM simulation. In this paper, a highly effective method to create a bent pipe FEM model based on geometrical changing between a pipe before and after bending is proposed. The widely used draw bending process is supposed to be applied. The method can construct the model in a short time. Therefore total computation time can be reduced drastically. The effects of number of integration points and elements to the computed results and springback prediction after bending are also investigated. The proposed method are applied to a actual part, the computed results are in good agreement with the experimental results.

For the purpose of protecting the driver from injury in a crash, a safety standard has been established that specifies the allowable impact force when the driver hits the steering wheel as a result of an impact. In this work, an investigation was lade of steering column collapse behavior in which the steering column was constructed such that the crash energy was absorbed by the bending and tearing of a thin steel plate. As a result, a finite element analysis method has been developed for conducting an impact analysis using a ductile fracture model of the thin plate. This method makes it possible to predict the collapse behavior of the steering column and the deceleration that develops on the body block of the safety standard test model.

Variable flux permanent magnet synchronous machines (VFPMSMs) have been designed by using finite element analysis (FEA) to evaluate speed-torque capability considering requirement for magnetization state (MS) manipulation. However, due to its unique characteristic to change the MS, numerous combinations of design parameters need to be evaluated to achieve a final design. To accelerate the design process, this paper presents a method that consists of an equivalent magnetic circuit model and a process to obtain magnet width and thickness that satisfy target maximum torque and power factor (P.F.) capability. This model includes magnet operating point analysis under given magnet width and thickness condition to achieve target MS and avoid demagnetization at full load. This analysis provides desired stator magnetomotive force, magnet and stator induced flux linkage. Therefore, expected torque and P.F. capability is calculated.

The combustion process after auto-ignition is investigated. Depending on the non-uniformity of the end gas, auto-ignition could initiate a flame, produce pressure waves that excite the engine structure (acoustic knock), or result in detonation (normal or developing). For the “acoustic knock” mode, a knock intensity (KI) is defined as the pressure oscillation amplitude. The KI values over different cycles under a fixed operating condition are observed to have a log-normal distribution. When the operating condition is changed (over different values of λ, EGR, and spark timing), the mean (μ) of log (KI/GIMEP) decreases linearly with the correlation-based ignition delay calculated using the knock-point end gas condition of the mean cycle. The standard deviation σ of log(KI/GIMEP) is approximately a constant, at 0.63. The values of μ and σ thus allow a statistical description of knock from the deterministic calculation of the ignition delay using the mean cycle properties