新型温差能驱动水下滑翔器系统设计

温差能驱动水下滑翔器使用海洋温差能作为驱动能源,只使用少部分电能用于控制和传感系统,其巡航范围和工作时间远远大于其它种类的水下航行器,与电能驱动水下滑翔器相比也具有明显优势.文章给出了温差能驱动水下滑翔器各功能模块设计和试验,并进行了总体系统的水域试验,验证了系统设计的有效性.     

基于自适应模型预测的智能汽车轨迹跟踪控制研究

针对车辆纵、横向跟踪的强耦合、非线性特性,设计了基于自适应模型预测控制理论的轨迹跟踪控制器.同时考虑纵、横向跟踪控制,并引入线性变参数模型(LPV),把纵向速度对横向跟踪的影响转化为LPV模型中调度参数的变化,把纵、横向跟踪的高度非线性动力学模型转化为LTI模型的插值队列,以用于自适应纵向速度的改变.基于预测控制理论,...     

广西内河流域的港口现代物流发展探讨

为了适应广西经济发展和中国一东盟自由贸易区的建立,在广西发展港口现代物流,尤其是内河港口物流是至关重要的。阐述了现代物流对港口的关键性作用和广西内河物流发展的重要意义。分析了影响广西内河流域物流发展的因素,提出了促进广西内河港口物流发展的措施。     

关于不同类型农村社区治理模式的思考

新农村建设的关键在于农村社区的建设,而治理模式的选择决定了农村社区建设的效果,从社区治理理论分析着手,结合我国各地农村的不同特点,提出治理模式的三种进路选择,为理论研究与政府决策提供相关参考。     

提高水泥混凝土钻孔灌注桩施工质量的基本控制措施

结合钻孔灌注桩施工工序较多,工艺流程相互衔接,主要工序都在水下或地下进行,水文地质条件复杂,影响因素较多,施工质量难以控制的特点,提出了搞好水泥混凝土灌注桩的施工质量,防止发生质量事故的基本控制措施。     

我国汽车营销模式演变趋势的系统动力学研究

在对营销模式内部要素和环境因素分析的基础上,构建汽车营销模式格局演变的系统动力学模型,研究未来几年内我国汽车营销模式的格局在各种内外部因素的共同影响下发展变化的趋势,得出未来5~10年特许经营模式将在我国汽车市场占主导地位,同时其它营销模式将呈现不同的发展态势,并认为营销模式受互联网发展和政策因素影响最显著。     

网络背景下的高职化学自主学习探析

基于网络环境下的自主学习对学生来说,是一种全新的学习方式。文章围绕自主学习的内涵、心理机制和网络自主学习的特点,分析了高职化学课程开展网络环境下自主学习的优势和特征,并对高职化学教学开展基于网络环境下的自主学习提出了要求。     

Smart charging management for shared autonomous electric vehicle fleets: A Puget Sound case study

Increasingly, experts are forecasting the future of transportation to be shared, autonomous and electric. As shared autonomous electric vehicle (SAEV) fleets roll out to the market, the electricity consumed by the fleet will have significant impacts on energy demand and, in turn, drive variation in energy cost and reliability, especially if the charging is unmanaged. This research proposes a smart charging (SC) framework to identify benefits of active SAEV charging management that strategically shifts electricity demand away from high-priced peak hours or towards renewable generation periods. Time of use (TOU), real time pricing (RTP), and solar generation electricity scenarios are tested using an agent-based simulation to study (1) the impact of battery capacity and charging infrastructure type on SAEV fleet performance and operational costs under SC management; (2) the cost reduction potential of SC considering energy price fluctuation, uncertainty, and seasonal variation; (3) the charging infrastructure requirements; and (4) the system efficiency of powering SAEVs with solar generation. A case study from the Puget Sound region demonstrates the proposed SC algorithm using trip patterns from the regional travel demand model and local energy prices. Results suggest that in the absence of electricity price signals, SAEV charging demand is likely to peak the evening, when regional electricity use patterns already indicate high demand. Under SC management, EVs with larger battery sizes are more responsive to low-electricity cost charging opportunities, and have greater potential to reduce total energy related costs (electricity plus charging infrastructure) for a SAEV fleet, especially under RTP structure.     

一种AMT用离合器推杆长度的计算方法

本文针对某AMT用离合器执行机构自身的结构特点,给出了一种计算离合器推杆长度的方法,并列出了计算公式。使用该方法确定的离合器推杆长度可保证离合器在整个寿命周期内离合器执行机构都能可靠工作。     

Eliciting preferences for adoption of fully automated vehicles using best-worst analysis

Autonomous mobility is one of the rapidly evolving aspects of smart transportation which carries the potential of reshaping both demand and supply sides of transportation systems. While understanding public opinions about autonomous vehicles (AVs) is a compelling step towards their successful implementation, still little is known about to which extent people will embrace this new technology and how the vehicle features will affect their adoption decision. This study presents a new approach for modeling the adoption behavior of fully AVs using the profile-case best-worst scaling model. In this approach, an AV profile which is characterized in terms of the main vehicle attributes and their associated levels is presented to the decision maker and he/she is asked to select the most and the least attractive attributes. Further, a binary adoption question at the end of the choice task inquires if the respondent is willing to purchase the described AV. Utilizing this method, we can recognize the difference between the intrinsic impacts of the vehicle attributes and the impact of the attribute levels on the adoption decision. Results of the analysis indicate that people are much more sensitive to the purchase price and incentive policies such as taking liability away from the “driver” in case of accidents and provision of exclusive lanes for AVs compared to other factors such as fuel efficiency, safety, or environmental friendliness. Further, it is found that millennials with higher income, those who live in the downtown area, and the majority of people who have experienced an accident in the past have greater interests in adopting this technology.