Simulation of flow in diesel particulate filter system using metal fiber filter media

Metal fiber is introduced as a new filter media in wall-flow Diesel Particulate Filter (DPF) system. This technology has high temperature durability which is required for filter regeneration, and can maintain the mechanical strength even in the extreme exhaust-related vibrations of vehicles. However, the regeneration near the wall (outer layer) is more difficult because of the heat loss and reduced gas flow near the wall. In this study, a flow is simulated to determine the flow control method for the more uniform flow in all filter layer. By using Star CCM+ commercial software, we obtain local velocity, streamline, and pressure distributions in the filter, which are typically difficult to obtain from measurements. The major control factors are the filter porosity, size and location of the distribution plate, and the number of blades of the swirler. By placing the distribution plate in front of the filter, the flow velocity near the wall was increased. The optimum location and size of the flat plate were chosen. By attaching the blade on the plate the flow velocity near the wall was increased more. Therefore, the regeneration efficiency is increased by using the swirler-type metal fiber DPF system.     

Realization of pmp-based control for hybrid electric vehicles in a backward-looking simulation

Optimal control is generally not possible without information about the future coming up, and it is not easy to obtain an optimal solution even though the information is given a priori. In this paper, a control concept based on Pontryagin’s Minimum Principle (PMP) is introduced as an efficient solution to generate an optimal control trajectory for Hybrid Electric Vehicles (HVEs) when the performance of the vehicles is evaluated on scheduled driving cycles at a simulation level. The main idea of the control concept is to minimize Hamiltonian, which is interpreted as equivalent fuel consumption, and the Hamiltonian is characterized by a co-state, which is interpreted as a weighting factor for the electrical usage. A key aspect of the control problem is that an appropriate initial condition of the co-state is required to satisfy the boundary condition of the problem. In this study, techniques to calculate the Hamiltonian in different hybrid configurations are introduced, and a methodology to look for the initial condition of the co-state is studied, so that the controller is able to realize a desired State Of Charge (SOC) trajectory. To address the issue, we utilize a shooting method with multiple initial conditions based on the concept of the Newton-Raphson method, and all these techniques are realized in a backward looking simulator. The simulation results show that the PMP-based control is a very efficient approach to produce the optimal control trajectory, and the performance is compared to the optimal solution solved by Dynamic Programming (DP).     

Road boundary detection and tracking for structured and unstructured roads using a 2D lidar sensor

Road boundaries can give useful information for evaluating safe vehicle paths in intelligent vehicles. Much previous research has studied road boundary detection, using different types of sensors such as vision, radar, and lidar. Lidar sensors, in particular, show advantages for road boundary extraction including high resolution and wide field of view. However, none of the previous studies examined the problem of detecting road boundaries when roads could be either structured or unstructured. In this study, we developed a road boundary detection and tracking algorithm using lidar sensing for both structured and unstructured roads. The algorithm extracts road features as line segments in polar coordinates relative to the lidar sensor. The extracted road features are then tracked with respect to a vehicle’s local coordinates using a nearest neighbor filter. The proposed algorithm accurately detected the road boundaries regardless of the road type.     

Durability prediction for automobile aluminum front subframe using nonlinear models in virtual test simulations

This research work presents fatigue life evaluation techniques for an automotive vehicle aluminum front subframe using virtual test simulation technology with nonlinear suspension components model. The technology was used for improving the accuracy of the polynomial model used in conventional analysis. The proposed nonlinear suspension components models were developed using direct approach. The effects of the nonlinear elements on the prediction of the fatigue life were also analyzed. Actual aluminum front subframe was tested using half-car road test simulator to verify the accuracy of the models. It was found that the proposed nonlinear models yield more accurate results than conventional polynomial models. The proposed virtual test simulation technology with nonlinear suspension components model can be used to predict fatigue life for vehicle chassis structures more accurately.     

Improvement of long-term lives of rubber gaskets of polyacrylate (ACM) by employing carboxyl cure sites

Rubber gaskets are used widely in many industries. An evaluation of the material properties and an accurate lifetime prediction of rubber are very important in the design process to ensure the durability and reliability of rubber components. The properties of rubber-like materials are sensitive to ambient conditions, such as temperature, environment and mechanical load. Moreover, the initial properties of rubber gaskets must be sustained under working conditions to maintain its sealing function. To perform tests within a reasonable time, the highly accelerated life test (HALT) is generally used to predict the long-term lifetime of rubber materials. Polyacrylate (ACM) with chlorine cure sites is generally used for engine head gaskets. An ACM with carboxyl cure sites was developed to improve the lifetime of the gaskets. A four-parameter method representing the recovery behavior of the gaskets was published recently, and two revised methods for obtaining the recovery were proposed. The mean squared errors (MSEs) of the regression methods and experimental data were compared. The life of a gasket for the target recovery (60%) of a compressed gasket was calculated somewhat differently depending on the selected regression model to predict a considerably different long-term life. The parameters in the regression models were obtained using the successive zooming genetic algorithm (SZGA), and the lives of ACM with a carboxyl cure site and ACM with a chlorine cure site were compared.     

Exploring the role of individual attitudes and perceptions in predicting the demand for cycling: a hybrid choice modelling approach

Cycling is often promoted as a means of reducing urban congestion and improving health, social and environmental outcomes. However, the quantification of these potential benefits is not well established. This is due in part to practical difficulties in estimating cycling demand and a lack of sound methodologies to appraise cycling initiatives. In this paper we attempt to address this need by developing predictive models of cycle demand, relative to other transport modes, that capture not only the impacts of observed characteristics such as age and travel time but also the role of attitudes and perceptions. Using data from a stated preference survey, we estimate a hybrid choice model for cycle use that incorporates the role of attitudes towards cycling, perceptions of the image associated with cycling, and the stress arising from safety concerns. Model results indicate that the latent attitudes and perceptions explain an important part of the non-observable utility in a simple multinomial logit choice model. We also demonstrate policy analysis using the hybrid choice model, which allows comparisons of ‘hard’ policies such as the provision of parking facilities against ‘soft’ measures such as cycle promotion schemes.     

Repetitions in individual daily activity–travel–location patterns: a study using the Herfindahl–Hirschman Index

Using Herfindahl–Hirschman Index and the Mobidrive and Thurgau six-week travel diary datasets this paper examines the degree of repetition of individuals’ choices of their daily activity–travel–location combinations. The results show that the repetitiveness of individual activity–travel–mode–location combinations is highly influenced by the individuals’ out-of-home commitments, the intra-household conditions and the availability and the accessibility of the activity locations. Different types of activity have different pattern of repetition. The level of repetition of individual’s daily activity–travel pattern is less correlated to travel mode choice, but more to the individuals’ commitments and obligations. The repetitiveness of mode choices is more related to the conditions or the accessibilities of the activity location, but not directly to the activity itself.     

Construction Risk Management for Deep Excavation Adjacent to In operation Bored Tunnels

营运中的盾构隧道在邻近施工时周围地盘的应力可能因扰动而重新分布,使得盾构隧道暴露在因变形或位移衍生的结构损坏或营运中断等高风险下。为降低相关风险发生的可能性或后果的严重性,高雄计划将高雄车站段地下化工程捷运-R11永久站施工纳入风险管理,通过风险辨识、分析、评估以及以监测、巡检及沟通为基础的风险追踪查核等手段执行风险管理。依本计划执行成果,位于基地两侧营运中的盾构隧道在永久站主体工程开挖施工期间,各项风险均受到妥善的追踪、管控及处置。