轿车覆盖件成型过程动态仿真有限元建模技术研究

研究了轿车覆盖件冲压成型过程动态仿真中的有限元建模问题，比较了可用于覆盖件成型分析的几类单元；讨论了单元的选取和单元划分的若干原则。并结合Santana2000型轿车侧框和NUMISHEET’96的S－Rail标准考题，说明了有限元仿真模型对成型仿真结果的影响。     

车辆行驶工况滚动阻力系数的测定

分析了车辆滚动阻力系数的影响因素，论述了车辆行驶速度对滚阻力系数的影响。依据车辆行驶的功率平衡原理，提出了滚动阻力系数的测试方法及测试时应注意的问题。并对实车测试值与经验公式估算值进行了比较。     

汽车发动机气道内的流动模拟计算

本文介绍了汽车发动机气道内三维定常可压缩流动数值模拟的模型、算法及算例。为达到能定量分析并应用于实际设计的目的,提出了一种新的计算网格划分法,并开发了计算软件,对提高计算精度、加速收敛等关键问题进行了探索。     

汽车主动悬架的最优预见控制

本文针对1/2车辆模型,应用最优预见控制理论对汽车主动悬架进行控制系统的设计和研究。计算机仿真结果表明,所提出的系统能有效改善汽车乘坐舒适性。     

我国汽车金融业的发展现状及趋势展望

首先分析了国内外汽车金融业的发展状况，并从当前我国汽车金融业存在的问题入手，着重从内部和外部环境2个方面进行了分析，从而有针对性地提出了我国汽车金融服务的改革思路和解决相关问题的政策建议，并对未来发展趋势作出理性预测和判断，制度设计上更趋于合理、完善；服务质量和水平逐步与国际接轨；竞争推动下的具有中国特色的金融创新渐趋活跃。在此基础上笔者设想了一种银行一体化的营销模式，权当为未来银行汽车金融业务的开展作一有益尝试。     

关于集成化汽车故障诊断系统及其支持技术研究

集成化汽车故障诊断系统有两种不同的体系结构,可由状态检测、信息融合、故障诊断、网络信息获取以及网络通讯等模块构成。在系统分析各模块功能得基础上,论述了检测设备仪器通讯的标准化、故障诊断专家系统的通用化、故障诊断推理方法的多元化和故障诊断知识获取的网络化是实现集成化汽车故障诊断系统的关键性支持技术。     

汽车操纵稳定性的广义汽车转向稳态响应模型

针对传统汽车操纵稳定性理论的线性二自由度模型的不足,构建了一个新的广义汽车转向稳态响应模型,并说明了该模型的广泛适用性。以某不足转向轿车模型的有关参数为例,仿真计算并比较了应用两种模型时该轿车等速圆周行驶时的稳态响应状况,验证了广义模型的正确性,同时得到了一条有别于传统汽车操纵稳定性理论的重要结论。     

Implementation and application of a stochastic aircraft boarding model

The aircraft turnaround processes is mainly controlled by the ground handling, airport or airline staff, except the aircraft boarding, which is driven by the passengers’ experience and willingness or ability to follow the proposed boarding procedures. The paper uses a prior developed, calibrated, stochastic aircraft boarding model, which is applied to different boarding strategies (chronological order of passenger arrival, hand luggage handling), group constellations and innovative infrastructural changes (Flying Carpet, Side-Slip Seat, Foldable Passenger Seat). In this context, passenger boarding is assumed to be a stochastic, agent-based, forward-directed, one-dimensional and discrete process. The stochastic model covers individual passenger behavior as well as operational constraints and deviations. A comprehensive assessment using one model allows for efficient comparison of current research approaches and innovative operational solutions for efficient passenger boarding.     

Spatiotemporal influence of land use and household properties on automobile travel demand

Understanding the patterns of automobile travel demand can help formulate policies to alleviate congestion and pollution. This study focuses on the influence of land use and household properties on automobile travel demand. Car license plate recognition (CLPR) data, point-of-interest (POI) data, and housing information data were utilized to obtain automobile travel demand along with the land use and household properties. A geographically and temporally weighted regression (GTWR) model was adopted to deal with both the spatial and temporal heterogeneity of travel demand. The spatial-temporal patterns of GTWR coefficients were analyzed. Also, comparative analyses were carried out between automobile and total person travel demand, and among travel demand of taxis, heavily-used private cars, and total automobiles. The results show that: (I) The GTWR model has significantly higher accuracy compared with the Ordinary Least Square (OLS) model and the Geographically Weighted Regression (GWR) model, which means the GTWR model can measure both the spatial and temporal heterogeneity with high precision; (II) The influence of built environment and household properties on automobile travel demand varies with space and time. In particular, the temporal distribution of regression coefficients shows significant peak phenomenon; and (III) Comparative analyses indicate that residents’ preference for automobiles over other travel modes varies with their travel purpose and destination. The above findings indicate that the proposed method can not only model spatial-temporal heterogeneous travel demand, but also provide a way to analyze the patterns of automobile travel demand.     

Predicting the adoption of connected autonomous vehicles: A new approach based on the theory of diffusion of innovations

On the grounds that individuals heavily rely on the information that they receive from their peers when evaluating adoption of a radical innovation, this paper proposes a new approach to forecast long-term adoption of connected autonomous vehicles (CAVs). The concept of resistance is employed to explain why individuals typically tend to defer the adoption of an innovation. We assume that there exists a social network among individuals through which they communicate based on certain frequencies. In addition, individuals can be subject to media advertisement based on certain frequencies. An individual’s perceptions are dynamic and change over time as the individual is exposed to advertisement and communicates with satisfied and dissatisfied adopters. We also explicitly allow willingness-to-pay (WTP) to change as a result of peer-to-peer communication. An individual decides to adopt when (i) there is a need for a new vehicles; (ii) his/her WTP is greater than CAV price; and (iii) his/her overall impression about CAVs reaches a cutoff value. Applicability of the proposed approach is shown using a survey of employees of the University of Memphis. Our results show that the automobile fleet will be near homogenous in about 2050 only if CAV prices decrease at an annual rate of 15% or 20%. We find that a 6-month pre-introduction marketing campaign may have no significant impact on adoption trend. Marketing is shown to ignite CAV diffusion but its effect is capped. CAV market share will be close to 100% only if all adopters are satisfied with their purchases; therefore, the probability that an individual becomes a satisfied adopter plays an important role in the trend of adoption. The effect of the latter probability is more pronounced as time goes by and is also more prominent when CAV price reduces at greater rates. Some caveats may be inserted when considering the study results as the findings are subject to sample bias and data limitations.