Digital human body model for seat comfort simulation

Using the recent anthropometry of the North American population, human body models were developed for seat comfort simulation. The external geometry of the models was acquired from the three-dimensional whole body laser scan of recruited volunteers in a driving position. The selection criteria for volunteers with standard size and shape were derived from a statistical factor analysis of the Size USA database. As a practical application of the model in a design process, comfortable driving postures were constructed by adopting the cascade prediction model (CPM), which takes into account both interior package layout and the driver’s anthropometry. The detail modeling process of finite element modeling and its validation results against volunteer measurements are introduced.     

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.     

Experimental study on performance of automotive air conditioning system using R-152a refrigerant

Recently, as climate changes have manifested worldwide, every country is making efforts to prevent ozone depletion and global warming. In the automotive industry, R-134a refrigerant is widely used in air conditioning systems because it has zero ozone depletion potential (ODP). Unfortunately, its global warming potential (GWP) is high. Therefore, alternative refrigerants are needed as a replacement for R-134a. R-152a is considered to be one of the better alternative refrigerants due to zero ODP and low GWP. In this paper, the performance of an automotive air conditioning system using R-134a and one using R-152a are compared experimentally at the bench level. The experimental apparatus simulated a real automotive air conditioning system consisting of a cabin and engine room structure. The cooling capacity, condensing capacity, coefficient of performance (COP) and power consumption characteristics of the automotive air conditioning system are evaluated by changing the air velocity entering the condenser and the compressor rotation speed with the optimized refrigerant charge amount. Also, the performance of the R-152a system was investigated by changing the thermostatic expansion valve which is set of values. The results of this study show that the R-152a system is slightly better than the R-134a system, not only under driving conditions but also under idling condition. R-152a refrigerant thus shows promise as an alternative refrigerant to replace the current standard, R-134a, in automotive air conditioning systems.     

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.     

Physical-chemical properties of ethanol-diesel blend fuel and its effect on the performance and emissions of a turbocharged diesel engine

This paper deals with the main physical-chemical properties of ethanol-diesel blend and the effects of ethanoldiesel blends (up to 15% volume) on engine performance (full load torque vs. engine speed, BSEC vs. torque at 1400 r/min and 2300 r/min, and effect of start of injection angle) and emissions in ECE R49 tests (steady 13 points) using a 6.6 L inline 6-cylinder turbocharged direct injection diesel engine. The results show that an increase in ethanol fraction results in decreased viscosity of the blend fuel and very high distillation characteristics in the low temperature range. Solvents can improve the solubility of ethanol-diesel blends. The engine power was degraded proportional to the ethanol content (10% and 15%) due to the LHV (low heating value) of the blends. The higher latent heat of vaporization and lower CN (cetane number) of ethanol, which results from the steady state emissions of CO, HC, and SOF (soluble organic fraction), were much higher in the ECE R49 tests at low loads. Soot (solid mass) emissions were improved. The particulate matter emissions were significantly increased with higher blend volumes, and NOx emissions slightly increased with higher ethanol volumes. By increasing the injection angle properly, the performance parameters of the diesel engine were improved, but NOx emissions were deteriorated slightly.     

基于移动数据的用户出行方式识别研究

为研究智能手机所采集到的位置数据在识别用户出行方式领域的应用,首先,比选出速度、速度的百分位数、轨迹点数量占比、出行距离、停止率这5 个适用于移动终端定位数据区分出行方式的特征变量,并对各特征变量的判别阈值进行了定义。然后,针对基站分布导致的数据偏差和位置信息漂移等问题,采用扇形定位结合地图匹配技术对数据进行了修正,进而在对时间阈值和距离阈值分割的基础上提出了移动终端用户出行链的获取方法。接着,建立C4.5 决策树模型,以此判别移动终端用户的出行方式。最后,基于在某地区采集的7 000 部移动终端的位置数据（包含：终端编号、定位时刻、经度、纬度） 来对用户的出行方式进行研究。结果表明,模型在区分机动车和非机动车时准确率较高,达到了90%以上;在进一步区分中,如区分步行与自行车以及公交车和小汽车的出行上准确率相对较低,但也达到了80%以上的精度。