Driving cycle prediction model based on bus route features

Bus fuel economy is deeply influenced by the driving cycles, which vary for different route conditions. Buses optimized for a standard driving cycle are not necessarily suitable for actual driving conditions, and, therefore, it is critical to predict the driving cycles based on the route conditions. To conveniently predict representative driving cycles of special bus routes, this paper proposed a prediction model based on bus route features, which supports bus optimization. The relations between 27 inter-station characteristics and bus fuel economy were analyzed. According to the analysis, five inter-station route characteristics were abstracted to represent the bus route features, and four inter-station driving characteristics were abstracted to represent the driving cycle features between bus stations. Inter-station driving characteristic equations were established based on the multiple linear regression, reflecting the linear relationships between the five inter-station route characteristics and the four inter-station driving characteristics. Using kinematic segment classification, a basic driving cycle database was established, including 4704 different transmission matrices. Based on the inter-station driving characteristic equations and the basic driving cycle database, the driving cycle prediction model was developed, generating drive cycles by the iterative Markov chain for the assigned bus lines. The model was finally validated by more than 2 years of acquired data. The experimental results show that the predicted driving cycle is consistent with the historical average velocity profile, and the prediction similarity is 78.69%. The proposed model can be an effective way for the driving cycle prediction of bus routes.     

船舶低硫柴油系统设计的分析与优化

就新辟航线首制船“汉亚直达”集装箱船的低硫柴油系统,叙述了船舶低硫柴油系统的设计经验,从当前国内外对船用燃油硫含量的要求、应对方案到船舶低硫柴油冷却方式选择、低硫柴油冷却系统设计、高/低硫柴油转换、使用低硫柴油风险分析及处理等方面进行详细叙述,为业内同行提供参考。     

A systematic analysis of multimodal transport systems with road space distribution and responsive bus service

A smart design of transport systems involves efficient use and allocation of the limited urban road capacity in the multimodal environment. This paper intends to understand the system-wide effect of dividing the road space to the private and public transport modes and how the public transport service provider responds to the space changes. To this end, the bimodal dynamic user equilibrium is formulated for separated road space. The Macroscopic Fundamental Diagram (MFD) model is employed to depict the dynamics of the automobile traffic for its state-dependent feature, its inclusion of hypercongestion, and its advantage of capturing network topology. The delay of a bus trip depends on the running speed which is in turn affected by bus lane capacity and ridership. Within the proposed bimodal framework, the steady-state equilibrium traffic characteristics and the optimal bus fare and service frequency are analytically derived. The counter-intuitive properties of traffic condition, modal split, and behavior of bus operator in the hypercongestion are identified. To understand the interaction between the transport authority (for system benefit maximization) and the bus operator (for its own benefit maximization), we examine how the bus operator responds to space changes and how the system benefit is influenced with the road space allocation. With responsive bus service, the condition, under which expanding bus lane capacity is beneficial to the system as a whole, has been analytically established. Then the model is applied to the dynamic framework where the space allocation changes with varying demand and demand-responsive bus service. We compare the optimal bus services under different economic objectives, evaluate the system performance of the bimodal network, and explore the dynamic space allocation strategy for the sake of social welfare maximization.     

营运大客车正面碰撞乘员伤害的研究

客车发生正面碰撞事故约占客车碰撞事故的50%~60%。利用LS-DYNA软件,建立了包括假人、安全带和安全气囊在内的大客车车体有限元模型,对不同速度下营运大客车的正面碰撞特性进行了模拟仿真计算,分析了无任何保护措施、佩戴安全带及佩戴安全带且安全气囊起爆三种事故形态下乘员头部HPC值、胸部压缩量和大腿骨轴向接触力等伤害值。研究结果表明,安全带对于驾驶员的保护意义重大,为营运大客车乘员保护设计以及合理制定营运大客车正面碰撞法规提供数据参考。     

Tyre/road noise damping characteristics using nomographs and fundamental vibroacoustical relationships

Several studies have successfully developed laboratory and field measurement techniques to estimate tyre/road noise damping characteristics. However, laboratory–field noise correlations of pavement types in the form of nomographs is essential to cognize the pavements’ acoustical properties from a practical perspective. A toolkit that readily provides field tyre/road noise intensity of different pavement materials is needed. Thus, the main objective of this study was to develop nomographs with relationships for tyre/road noise versus pavement materials’ viscoelastic–vibroacoustical properties. Isothermal and isochronal nomographs of phase angle–tyre/road noise as toolkits were developed based upon well-established phase angle and noise intensities typical of mixtures, making the nomograph correlations very authentic, realistic, and novel along with benefit to predict tyre/road noise at any desired temperature and traffic speed (or frequency) combination. This study is envisaged to benefit in the discernment of road materials’ damping capabilities from vibroacoustical and field noise–viscoelastic relation aspects.     

船舶推进同步电机PTI/PTO模式研究

PTI/PTO推进是最近发展起来的一种新型船舶推进方式,兼具传统柴油机推进和电力推进优点,可实现多种船舶工作模式,具有操控性好、安全、经济等特点,将是未来船舶推进方式发展方向之一.本文介绍了PTI/PTO推进模式理论和工作模式,便于理解该推进方式,希望有助于船舶推进技术的发展.     

STAAD/CHINA在搭架设计及强度校核中的应用

搭架作业是船舶修造日常工作中比较普通、常见的工程,合理、快速地设计和校验脚手架的强度,直接影响生产施工的安全性、经济性和效率。文章介绍了如何使用有限元软件STAAD/CHINA对搭架方案进行建模计算及校验,计算结果接近实际,提高了强度校验的效率。     

基于多源数据的公交车能耗碳排放测算模型

公交车能耗碳排放强度与车辆、线路和驾驶员有显著相关关系，为精准刻画其能耗碳排放强度特征，整合OBD监测数据、加油(气)数据、运营排班数据等多源数据资源. OBD监测数据和加油(气)数据呈显著的线性关系，证明修正后的OBD监测数据可满足分析要求. 搭建“速度-能耗碳排放强度曲线”测算模型，幂函数关系的拟合优度R2 =0.972 6 为最高. 实证研究发现，平均速度在10~60 km/h 变化时，液化天然气(LNG)车比柴油车能耗碳排放强度高 3.3%~33.7%，双层车比铰接车高2.4%~13.3%；LNG铰接车在不同线路、相同速度下的强度相差9.6%；不同驾驶员在相同线路的能耗碳排放强度可相差24.2%. 模型为各城市基于多源数据开展公交能耗碳排放目标设定提供数据支撑.     

A cost-competitiveness analysis of charging infrastructure for electric bus operations

This study investigates the cost competitiveness of different types of charging infrastructure, including charging stations, charging lanes (via charging-while-driving technologies) and battery swapping stations, in support of an electric public transit system. To this end, we first establish mathematical models to investigate the optimal deployment of various charging facilities along the transit line and determine the optimal size of the electric bus fleet, as well as their batteries, to minimize total infrastructure and fleet costs while guaranteeing service frequency and satisfying the charging needs of the transit system. We then conduct an empirical analysis utilizing available real-world data. The results suggest that: (1) the service frequency, circulation length, and operating speed of a transit system may have a great impact on the cost competitiveness of different charging infrastructure; (2) charging lanes enabled by currently available inductive wireless charging technology are cost competitive for most of the existing bus rapid transit corridors; (3) swapping stations can yield a lower total cost than charging lanes and charging stations for transit systems with high operating speed and low service frequency; (4) charging stations are cost competitive only for transit systems with very low service frequency and short circulation; and (5) the key to making charging lanes more competitive for transit systems with low service frequency and high operating speed is to reduce their unit-length construction cost or enhance their charging power.     

Dynamic demand estimation and prediction for traffic urban networks adopting new data sources

Nowadays, new mobility information can be derived from advanced traffic surveillance systems that collect updated traffic measurements, both in fixed locations and over specific corridors or paths. Such recent technological developments point to challenging and promising opportunities that academics and practitioners have only partially explored so far.The paper looks at some of these opportunities within the Dynamic Demand Estimation problem (DDEP). At first, data heterogeneity, accounting for different sets of data providing a wide spatial coverage, has been investigated for the benefit of off-line demand estimation. In an attempt to mimic the current urban networks monitoring, examples of complex real case applications are being reported where route travel times and route choice probabilities from probe vehicles are exploited together with common link traffic measurements.Subsequently, on-line detection of non-recurrent conditions is being recorded, adopting a sequential approach based on an extension of the Kalman Filter theory called Local Ensemble Transformed Kalman Filter (LETKF).Both the off-line and the on-line investigations adopt a simulation approach capable of capturing the highly nonlinear dependence between the travel demand and the traffic measurements through the use of dynamic traffic assignment models. Consequently, the possibility of using collected traffic information is enhanced, thus overcoming most of the limitations of current DDEP approaches found in the literature.