Effects of end coils on the natural frequency of automotive engine valve springs

In this paper, we present a method for estimating the natural frequencies of various engine valve springs such as constant pitch, two-step variable pitch, three-step variable pitch, and progressive springs. Since a valve spring’s surging amplitude is magnified when the spring’s natural frequency coincides with the frequency of the cam profile harmonic components, estimating the natural frequency of the spring is the first step in predicting valve spring surging phenomena. A new method for calculating the valve spring’s natural frequency is proposed in this paper that considers the end coil effect. This method predicts not only the natural frequency of a helical spring at a fixed number of active turns, but also the change in the natural frequency as the spring is compressed. The experimental results demonstrate that nonlinear characteristics of engine valve springs can be predicted from the given initial pitch curves.     

Prediction of vibrating forces on meshing gears for a gear rattle using a new multi-body dynamic model

An efficient multibody dynamic model was developed to predict the vibrating transmitted gear forces of loaded and unloaded pairs of helical gears simultaneously at all speeds. The model can also calculate the bearing forces of a manual transmission that, in turn, may be converted to rattling noises. The bending of meshing gear teeth and torsional flexibility of transmission shafts were considered and embodied effectively in the multibody dynamic model by calculating the tooth bending stiffness and adding a torsion spring on a shaft section between two gears, respectively. The reactive forces on teeth and bearings were calculated and compared using three different models that were developed for this study — an equivalent model, a rigid-body model, and a frequency-based model. The equivalent model took only 58% computation time, compared to the frequency-based method, even though the two showed very similar results.     

Improved method for analyzing automotive transmission parts (shaft/gear) manufactured using the warm shrink fitting process

There are three sub-processes associated with the assembly of an automobile transmission: heat fitting, shrink fitting, and combination fitting. In the heat fitting stage, the gear is heated to a specified temperature and then squeezed towards the outer diameter of the shaft. The stress of the heat-fitted gear depends on the yield strength of the gear. In the shrink fitting process, the gear is typically squeezed towards the shaft at room temperature using a press. An alternate method, known as warm shrink fitting, heats the already warm gear and safely squeezes it toward the shaft. The warm shrink fitting process for automobile transmission parts is becoming more commonplace, but the additional heating can cause the dimensions of the assembled parts (shaft/gear) to change with respect to both the outer diameter and the profile of the gear. As a result, there may be additional noise and vibration between gears. To address these problems, we analyzed the warm shrink fitting process using the contact pressure caused by fitting interference between the outer diameter of the shaft and the inner diameter of the gear, fitting temperature, and the profile tolerance of the gear as design parameters. In this study, a closed form equation for predicting the contact pressure and fitting load is proposed. This equation is used to develop an optimization technique for the warm shrink fitting process. The reliability of the model was verified using experimental results measured in the field, and FEM with thermal-structural coupled field analysis. Actual loads measured in the field showed good agreement with the results obtained by theoretical and finite element analysis, and expansion of the outer diameters of the gears agreed well with the results.     

Motor control of input-split hybrid electric vehicles

A motor control strategy for an input-split hybrid electric vehicle (HEV) is proposed. From a power characteristic analysis, it is found that the powertrain efficiency decreases for speed ratios at which power circulation occurs. Using dynamic models of an input-split HEV powertrain, a motor-generator control algorithm for obtaining high system efficiency is designed by inversion-based control. The performance of the control algorithm is evaluated by the simulator which is developed based on PSAT, and simulation results are compared with the test results. It is found that, even if the engine thermal efficiency is sacrificed by moving the engine operation point from the OOL for the control strategy, improved overall powertrain system efficiency can be achieved by the engine operation that gives a relatively high efficiency from the viewpoint of the overall powertrain efficiency. The control algorithm developed can be used in design of future electric vehicles.     

Sensor fusion-based lane detection for LKS+ACC system

This paper discusses the market trends and advantages of a safety system integrating LKS (Lane Keeping System) and ACC (Adaptive Cruise Control), referred to as the LKS+ACC system, and proposes a method utilizing the range data from ACC for the sake of lane detection. The overall structure of lane detection is the same as the conventional method using monocular vision: EDF (Edge Distribution Function)-based initialization, sub-ROI (Region Of Interest) for left/right and distance-based layers, steerable filter-based feature extraction, and model fitting in each sub-ROI. The proposed method adds only the system for confining lane detection ROI to free space that is established by range data. Experimental results indicate that such a simple adaptive ROI can overcome occlusion of lane markings and disturbance of neighboring vehicles.     

Driving environment assessment using fusion of in- and out-of-vehicle vision systems

Because the overall driving environment consists of a complex combination of the traffic Environment, Vehicle, and Driver (EVD), Advanced Driver Assistance Systems (ADAS) must consider not only events from each component of the EVD but also the interactions between them. Although previous researchers focused on the fusion of the states from the EVD (EVD states), they estimated and fused the simple EVD states for a single function system such as the lane change intent analysis. To overcome the current limitations, first, this paper defines the EVD states as driver’s gazing region, time to lane crossing, and time to collision. These states are estimated by enhanced detection and tracking methods from in- and out-of-vehicle vision systems. Second, it proposes a long-term prediction method of the EVD states using a time delayed neural network to fuse these states and a fuzzy inference system to assess the driving situation. When tested with real driving data, our system reduced false environment assessments and provided accurate lane departure, vehicle collision, and visual inattention warning signals.     

Origin-destination trip table estimation based on subarea network OD flow and vehicle trajectory data

Identifying accurate origin-destination (O-D) travel demand is one of the most important and challenging tasks in the transportation planning field. Recently, a wide range of traffic data has been made available. This paper proposes an O-D estimation model using multiple field data. This study takes advantage of emerging technologies – car navigation systems, highway toll collecting systems and link traffic counts – to determine O-D demand. The proposed method is unique since these multiple data are combined to improve the accuracy of O-D estimation for an entire network. We tested our model on a sample network and found great potential for using multiple data as a means of O-D estimation. The errors of a single input data source do not critically affect the model’s overall accuracy, meaning that combining multiple data provides resilience to these errors. It is suggested that the model is a feasible means for more reliable O-D estimation.     

Determining locations of charging stations for electric taxis using taxi operation data

The adequate provision of charging infrastructure is critical for the effective deployment of electric taxis. This study attempts to locate charging stations for electric taxis reflecting real-world taxi travel patterns identified from taxis equipped with digital tachographs. Data for one week are processed in order to estimate their charge demand. The estimated temporal distribution of charge demand indicates that it varies day-by-day and hour-by-hour. The maximum set covering model is applied for determining the locations of charging stations. The results show that the pre-specified service distance and service coverage rate (defined by the proportion of total demand served) can be critical factors for determining the number and location of charging stations. These factors should be carefully specified by considering the tradeoff between operational efficiency of charging facilities and user convenience.     

探查水下矿物资源的AUV动力控制系统开发

Valuable mineral resources are widely distributed throughout the seabed. autonomous underwater vehicles (AUVs) are preferable to remotely-operated vehicles (ROVs) when probing for such mineral resources as the extensive exploration area makes it difficult to maintain contact with operators. AUVs depend on batteries, so their power consumption should be reduced to extend exploration time. Power for conventional marine instrument systems is incorporated in their waterproof sealing. External intermittent control of this power source until termination of exploration is challenging due to limitations imposed by the underwater environment. Thus, the AUV must have a power control system that can improve performance and maximize use of battery capacity. The authors developed such a power control system with a three-step algorithm. It automatically detects underwater operational states and can limit power, effectively decreasing power consumption by about 15%.     

Spatial and temporal variability in the pelagic ecosystem of the East Sea (Sea of Japan): A review

The East Sea (Sea of Japan) is a unique marginal sea because it exhibits features of oceanic dynamics of much larger ocean basins. This semi-enclosed basin may be considered as a model or microcosm for understanding of how biological processes and distributions in pelagic ecosystem are interacting with physical processes in highly dynamic ocean regions. This overview summarizes the recent progresses concerning spatial and temporal variability of pelagic ecosystem components form an interdisciplinary point of view. Spatial characteristics of physical environments and biogeography in the region are distinguished mainly by the subpolar front. It was also found that long-term changes in biomass and community structure as well as those in the physical and biological environments are associated with climate variability in the region. We conclude by identifying main needs for the information and researches, particularly regular and long-term sampling, and permanent monitoring if possible.