Integrated approach to an optimal automotive timing chain system design

Ensuring engine efficiency is a crucial issue for automotive manufacturers. Several manufacturers focus on reducing the time taken to develop and introduce brand new vehicles to the market. Thus, a synergic approach including various simulations is generally adopted to achieve a development schedule and to reduce the cost of physical tests. This study involved proposing a design process that is very useful in the preliminary development stage through effective support from simulations. This type of simulation-based design process is effective in developing timing chain drives; the use of this process, based on results from multiple trials, showed improvements in performance including low friction and vibration, improved durability, and cost-effective part design when compared to conventional processes. This study proposes an integrated approach to the preliminary design of an automotive timing chain system. The approach involves structural and dynamic analyses. The details of the design process are described by using the case of a virtual engine. This study conducted and summarized a dynamic and structural analysis as well as topological optimization to describe a process to obtain optimal results. The results of this study indicated the following improvements in overall performance factors: 12.1 % improvement in transmission error, 10.1 % reduction in chain tension, 46 % reduction in tensioner arm weight, and 11 % reduction in transversal displacement.     

Vibration reduction of H/Shaft using an electromagnetic damper with mode change

The objective of this study is to develop a damper that can reduce the amplitude of vibration in various frequency ranges. Previous H/Shaft vibration reduction methods work in a passive way. A dynamic damper reduces the amplitude of vibration at its first mode, but vibration still appears at the second mode. A mass damper or hollow shaft can shift the natural frequency to a lower or higher region. The fixed operating frequency prevents vibration from being reduced outside the operating frequency range. The proposed damper uses electromagnets as either masses or actuators to change the damper mode between dynamic damper mode and mass damper mode. The electromagnetic damper (EMD) can change its mode to respond to the vibration excitation at both low and high frequencies. The vibration reduction performance was evaluated by FRF tests in laboratory and vehicle conditions. The results were compared with those of a dynamic damper and indicate that the amplitude of vibration is reduced by 95.6 % when the EMD is implemented on an H/Shaft, whereas only 61.9 % vibration reduction is achieved by the dynamic damper.     

A receding horizon sliding control approach for electric powertrains with backlash and flexible half-shafts

Active control of electric powertrains is challenging, due to the fact that backlash and structural flexibility in transmission components can cause severe performance degradation or even instability of the control system. Furthermore, high impact forces in transmissions reduce driving comfort and possibly lead to damage of the mechanical elements in contact. In this paper, a nonlinear electric powertrain is modelled as a piecewise affine (PWA) system. The novel receding horizon sliding control (RHSC) idea is extended to constrained PWA systems and utilised to systematically address the active control problem for electric powertrains. Simulations are conducted in Matlab/Simulink in conjunction with the high fidelity Carsim software. RHSC shows superior jerk suppression and target wheel speed tracking performance as well as reduced computational cost over classical model predictive control (MPC). This indicates the newly proposed RHSC is an effective method to address the active control problem for electric powertrains.     

Insights into vehicle trajectories at the handling limits: analysing open data from race car drivers

Race car drivers can offer insights into vehicle control during extreme manoeuvres; however, little data from race teams is publicly available for analysis. The Revs Program at Stanford has built a collection of vehicle dynamics data acquired from vintage race cars during live racing events with the intent of making this database publicly available for future analysis. This paper discusses the data acquisition, post-processing, and storage methods used to generate the database. An analysis of available data quantifies the repeatability of professional race car driver performance by examining the statistical dispersion of their driven paths. Certain map features, such as sections with high path curvature, consistently corresponded to local minima in path dispersion, quantifying the qualitative concept that drivers anchor their racing lines at specific locations around the track. A case study explores how two professional drivers employ distinct driving styles to achieve similar lap times, supporting the idea that driving at the limits allows a family of solutions in terms of paths and speed that can be adapted based on specific spatial, temporal, or other constraints and objectives.     

山区峡谷非均匀风场下大跨度斜拉桥静风稳定性分析

为研究山区峡谷地形下非均匀风场对大跨度桥梁静风稳定性的影响,以一座跨越典型山区峡谷地形的大跨度斜拉桥为工程背景,首先,采用计算流体动力学（CFD）软件Fluent对桥址区地形的风场特性进行分析,计算出沿主梁方向的非均匀风速和非均匀风攻角分布;然后,采用ANSYS APDL技术实现能考虑非均匀风速和非均匀风攻角下大桥静风稳定性的非线性分析方法。在此基础上,综合考察非均匀风攻角分布、非均匀风速分布、非均匀风速非均匀风攻角分布等风场条件对大桥静风稳定性的影响,分析各工况下主梁的静风变形与跨中处拉索刚度变化。研究结果表明：与均匀风场条件下的静风响应不同,非均匀风攻角或非均匀风速下主梁静风响应最大值点位于风荷载峰值点与跨中之间,在针对非均匀风场下大桥的静风稳定性分析时,应更注重静风响应最大值点而不是跨中处;非均匀风攻角下大桥的静风失稳临界风速要远低于均匀风攻角的静风失稳临界风速,且其静风稳定性能主要受最大风攻角而不是主跨部分非均匀风攻角的平均值来控制;非均匀风速下大桥的静风失稳临界风速主要由主跨部分的风速平均值和最大值共同影响;主梁的竖向位移和扭转角形状主要由风攻角因素来控制,而横向位移的变化规律相对较独立,其形状基本上以跨中线对称,且其值主要由风速因素来决定。     

CFD Analysis of Ship-to-Ship Hydrodynamic Interaction

A numerical study of ship-to-ship interaction forces is performed using a commercial CFD code, and the results are compared with experimental data and with the results of a panel method analysis. Two ship models have been used in the interaction forces analysis: a tug and a tanker, advancing parallel to each other with different lateral distances and two different values of the fluid depth. Computations are carried out with four different flow models: inviscid and viscous flow with the free surface modeled as a rigid wall and inviscid and viscous flow with the deformable free surface. A fair agreement was obtained with available experimental data and results obtained by panel method. The influence of viscosity in the computations is found to be comparatively weak, while the wavemaking effects may be important, at small magnitude of the horizontal clearance.     

Are we ready to embrace connected and self-driving vehicles? A case study of Texans

While connected, highly automated, and autonomous vehicles (CAVs) will eventually hit the roads, their success and market penetration rates depend largely on public opinions regarding benefits, concerns, and adoption of these technologies. Additionally, the introduction of these technologies is accompanied by uncertainties in their effects on the carsharing market and land use patterns, and raises the need for tolling policies to appease the travel demand induced due to the increased convenience. To these ends, this study surveyed 1088 respondents across Texas to understand their opinions about smart vehicle technologies and related decisions. The key summary statistics indicate that Texans are willing to pay (WTP) $2910, $4607, $7589, and $127 for Level 2, Level 3, and Level 4 automation and connectivity, respectively, on average. Moreover, affordability and equipment failure are Texans’ top two concerns regarding AVs. This study also estimates interval regression and ordered probit models to understand the multivariate correlation between explanatory variables, such as demographics, built-environment attributes, travel patterns, and crash histories, and response variables, including willingness to pay for CAV technologies, adoption rates of shared AVs at different pricing points, home location shift decisions, adoption timing of automation technologies, and opinions about various tolling policies. The practically significant relationships indicate that more experienced licensed drivers and older people associate lower WTP values with all new vehicle technologies. Such parameter estimates help not only in forecasting long-term adoption of CAV technologies, but also help transportation planners in understanding the characteristics of regions with high or low future-year CAV adoption levels, and subsequently, develop smart strategies in respective regions.     

How household transportation expenditures have evolved in Canada: a long term perspective

In recent years, increasing recognition of the challenges associated with global climate change and inequity in developed countries have revived researcher’s interest towards analyzing transportation related expenditure of households. The current research contributes to travel behaviour literature by developing an econometric model of household budgetary allocations with a particular focus on transportation expenditure. Towards this end, we employ the public-use micro-data extracted from the Survey of Household Spending (SHS) for the years 1997–2009. The proposed econometric modeling approach is built on the multiple discrete continuous extreme value model (MDCEV) framework. Specifically, in our analysis, the scaled version of the MDCEV model outperformed its other counterparts. Broadly, the model results indicated that a host of household socio-economic and demographic attributes along with the residential location characteristics affect the apportioning of income to various expenditure categories and savings. We also observed a relatively stable transportation spending behaviour over time. Additionally, a policy analysis exercise is conducted where we observed that with increase in health expenses and reduction in savings results in adjustments in all expenditure categories.     

Robust network pricing and system optimization under combined long-term stochasticity and elasticity of travel demand

Network pricing serves as an instrument for congestion management, however, agencies and planners often encounter problems of estimating appropriate toll prices. Tolls are commonly estimated for a single-point deterministic travel demand, which may lead to imperfect policy decisions due to inherent uncertainties in future travel demand. Previous research has addressed the issue of demand uncertainty in the pricing context, but the elastic nature of demand along with its uncertainty has not been explicitly considered. Similarly, interactions between elasticity and uncertainty of demand have not been characterized. This study addresses these gaps and proposes a framework to estimate nearest optimal first-best tolls under long-term stochasticity in elastic demand. We show first that the optimal tolls under the deterministic-elastic and stochastic-elastic demand cases coincide when cost and demand functions are linear, and the set of equilibrium paths is constant. These assumptions are restrictive, so three larger networks are considered numerically, and the subsequent pricing decisions are assessed. The results of the numerical experiments suggest that in many cases, optimal pricing decisions under the combined stochastic-elastic demand scenario resemble those when demand is known exactly. The applications in this study thus suggest that inclusion of demand elasticity offsets the need of considering future demand uncertainties for first-best congestion pricing frameworks.     

Factors associated with home-based e-working and e-shopping in Nanjing,China

The widespread adoption of information and communication technology has facilitated frequent e-activities in people’s daily life. From the perspective of individual’s time use on e-working and e-shopping at home, this paper aims to enhance our understanding of the function of home beyond a living space for family life. Using a household survey of 608 full-time paid employees who conducted e-activities at home in Nanjing, China, we investigated the characteristics and patterns of home-based e-working and e-shopping. Only 7.9% of the respondents neither e-shopped nor e-worked at home. We find that the socio-demographic context, Internet use habits, attitudes towards e-working/e-shopping, and geographical accessibility have influenced the patterns of home-based e-working and e-shopping. The results indicate that the rich e-activities taking place at home have changed the time use at home and reinforced the function of home as a multifunctional hub.