双离合自动变速器电控电动换挡执行机构仿真优化与试验对比

为了提高双离合变速器在车辆上的换挡品质,提升电气化换挡执行机构的工作效率,给出执行机构性能与换挡品质评价准则;通过两种不同双离合变速器电控电动执行机构的工作原理与性能分析,基于MATLAB数值仿真方法优化出最高效率进行试验.基于车辆6个维度的换挡工况对二者所搭载的变速器分别进行试验与CAN线数据采集,对比研究两种机构优缺点,通过雷达图的方式进行优劣说明.结果表明,两种执行机构传动效率可达70％且换挡品质相当.可见Tip in tip out工况对二者要求最为严格.     

We Eat First with Our (Digital) Eyes: Enhancing Mental Simulation of Eating Experiences via Visual-Enabling Technologies

This research examines how consumers’ intentions to purchase food change depending on the visualisation mode (3D vs. AR) and product format (served vs. packaged). In three studies, we demonstrate that mental simulation of eating experiences (process and outcome) mediate these effects. Study 1 shows that AR visualisation of a served food improves simulation of the eating process over 3D visualisation, with a positive effect on purchase intention. Study 2 reveals that 3D visualisation improves purchase intention for packaged products (high instrumental properties) over served products (low instrumental properties) while the opposite is true for AR visualisation. In addition, interactivity and immersion mediate the effects of 3D (vs. AR) on mental simulation of the eating process for packaged products. Study 3 extends these results by showing that 3D increases purchase intention by eliciting mental simulation of the eating outcome, when the food is visible due to transparent (vs. opaque) packaging (displaying both sensory and instrumental properties), but that no such differences emerge for AR. This research highlights the importance of using different visualisation modes to promote food depending on the product format. The findings have important implications for both offline and online retailers.     

Personal Income Tax Reform in China in 2018 and Its Impact on Income Distribution

In the context of personal income tax (PIT) reform in China in 2018, this paper examines some of the major issues of concern regarding the reform and income distribution. Using the China Personal Income Tax Micro‐simulation model, the paper compares the differences between the 2011 and 2018 PIT systems, and finds that residents relying on different income sources may face a large degree of real tax rate change. Once the tax system is altered to PIT 2018, the coverage of PIT for wage earners will decrease from 46.9 to 23.4 percent, the income redistributive effect will drop from 1.95 to 1.22 percent and the PIT's role in fiscal revenue will also be negatively affected. Nevertheless, if individual income continues to grow, the share of PIT in fiscal revenue is expected to return to the 2018 level in 2022, but its income redistribution function is difficult to recover in the short term. The paper finds that the effect of PIT on income distribution depends on the tax structure. Gradual transition to an “entirely comprehensive” tax system when conditions are appropriate will achieve better income redistribution results at a lower average tax rate.     

When and why do countries break their national fiscal rules?

This paper identifies determinants of compliance with various types of national numerical fiscal rules. Based on 51 fiscal rules in force in EU member states from 1995 to 2015, the analysis identifies determinants among specific rule characteristics and their fiscal frameworks, as well as their political, (socio-)economic and supranational environments. While the average compliance across all rules and countries is around 50%, compliance with rules constraining stock (rather than flow) variables, set out in coalitional agreements, as well as rules covering larger parts of general government finances is significantly higher. Furthermore, independent monitoring and enforcement bodies (issuing real-time alerts) turn out to be significantly associated with a higher probability of compliance. Several theories of the deficit bias of governments due to government fragmentation, decentralization and political budget cycles are also significant with regards to compliance with fiscal rules. However, neither the economic environment or business cycle, nor forecast errors (except for an unexpectedly higher primary balance) on average seem to play a significant role.     

EMPIRICAL PERFORMANCE OF GARCH MODELS WITH HEAVY‐TAILED INNOVATIONS

We introduce a new type of heavy‐tailed distribution, the normal reciprocal inverse Gaussian distribution (NRIG), to the GARCH and Glosten‐Jagannathan‐Runkle (1993) GARCH models, and compare its empirical performance with two other popular types of heavy‐tailed distribution, the Student's t distribution and the normal inverse Gaussian distribution (NIG), using a variety of asset return series. Our results illustrate that there is no overwhelmingly dominant distribution in fitting the data under the GARCH framework, although the NRIG distribution performs slightly better than the other two types of distribution. For market indexes series, it is important to introduce both GJR‐terms and the NRIG distribution to improve the models’ performance, but it is ambiguous for individual stock prices series. Our results also show the GJR‐GARCH NRIG model has practical advantages in quantitative risk management. Finally, the convergence of numerical solutions in maximum‐likelihood estimation of GARCH and GJR‐GARCH models with the three types of heavy‐tailed distribution is investigated.     

Estimating emissions based on the integration of microscopic traffic simulation and vehicle dynamics model

This study proposes an integrated simulation approach, which consists of a microscopic traffic simulation model, a vehicle dynamics model, and an emission estimation model, in order to estimate emissions based on more reliable vehicle performance measures. The vehicle performance measures such as engine power and engine speed significantly relate to the amount of emissions, and road curvatures and inclinations are the core inputs affecting these vehicle performance measures. Therefore, providing reliable vehicle performance measures reflecting the road geometric attributes is critical for a reliable emission estimation. This study proposes to use the microscopic traffic simulation model for generating vehicle trajectories, which is advantageous in modeling various traffic situations, and the vehicle dynamics model for producing the vehicle performance measures based on the vehicle trajectories. Finally, the outputs from the vehicle dynamics model are fed into the emission estimation model to compute emission measures. This study conducted a case-study using two road sections, one is a hypothesized road section, including various curvatures and inclinations with regular variations, and the other is a Kesselberg road section, which is an actual geometry in Bayern, Germany. The emission measures are estimated in these case-study road sections using both an existing simulation approach and the proposed integrated simulation approach. The difference between these two emission estimation approaches is discussed in terms of the emission measures, including fuel consumption, nitrogen oxides, and particulate matters.     

Analysis of the effect of charging infrastructure design on electric taxi driving profiles: A case study approach on the example of Singapore

Replacing conventional vehicle taxis with electric vehicles would be an efficient measure to reduce greenhouse gas emissions. Due to the limited range and long charging times of current battery electric vehicles, it is of utmost importance to provide sufficient charging facilities. This article analyses the impact of the placement and charging power of charging stations on potential mileage and revenue of electric taxis on the example of Singapore. Therefore, we developed an agent-based electric taxi simulation model to investigate electric taxis’ driving profiles with respect to different vehicle types and charging infrastructure designs. This model is also capable of simulating conventional taxi driving profiles. The validation of these simulation results with real taxi data showed that the model is reproducing taxi driving profiles with high accuracy in great detail. We found out that electric taxis could reach the same mileage and revenue as conventional taxis if charging with a power of 160?kW is possible. Furthermore, we discovered that waiting times for available charging stations have a stronger effect on revenue than the length of detours to reach charging stations. Based on these findings, we concluded that it is more important to reduce waiting times by placing sufficient numbers of charging stations at each location before expanding the charging network by installing small numbers of charging stations at many locations.     

Economic Impacts of the Possible China–US Trade War

This article uses a multi-country global general equilibrium (GE) model to numerically simulate the effects of possible China–US trade wars. We introduce an endogenous trade imbalance structure with trade cost into the model which helps to explore both tariff and non-tariff trade war effects. Our simulation results show that China will be significantly hurt by the China–US trade war, but negative impacts are affordable. The US can gain under unilateral sanction measures to China, but will lose if China takes retaliation measures. Comparing the effects under mutual trade war, China will lose more than the US. Introducing non-tariff barrier trade wars will intensify the negative effects, and comparatively negative effects to China are larger than to the US. Mexico’s involvement in trade war with the US will strengthen the negative effects and comparatively hurt the US more. Under non-cooperative and cooperative Nash bargaining equilibrium, the US can gain more than China in trade war negotiation, which means the US has stronger bargaining power than China. Additionally, trade wars between China and the US will hurt most countries and the world especially in GDP and manufacturing employment, but benefit their welfare and trade.     

Application of collective knowledge diffusion in a social network environment

ABSTRACT

We present a group dynamics model that shows knowledge integration as a process occurring over time. As each individual in the group contact others, his own knowledge changes, and over time the collective knowledge is obtained. This allows modeling knowledge diffusion in a social network and while the models presented in this paper are not competitive in that area, they approach the problem from previously unconsidered direction. We test the behavior of the model in a multi-agent simulation and we test a simple advertisement campaign in a social network. We provide discussion of elements needed for making model more competitive.     

基于多软件平台的机电液一体化虚拟试验方法

提出一种针对复杂机电液系统的虚拟仿真试验方法,分别在ADAMS、AMESim、MATLAB/Simulink软件中建立机械子系统、液压子系统和控制子系统模型,并基于软件间接口技术,建立动态数据共享通道,实现系统的全面仿真分析,为系统设计与优化、控制策略选择等提供依据.该方法对于复杂机电液系统仿真分析具有普遍适用性,对缩短产品开发周期、降低产品研发成本、减轻仿真工作复杂性具有重要意义.