智能汽车专业校企合作模式及人才培养方式的探究

智能汽车已经成为未来汽车领域的发展方向,且高校逐渐与企业合作,建立智能汽车人才培养模式。但是现阶段,校企合作深度以及人才培养方式仍然存在一定的不足,不利于为智能汽车领域输送更多的人才。基于此,本文主要探究智能汽车专业校企合作模式以及人才培养模式,详细阐述智能汽车专业校企合作模式及人才培养模式中存在的问题,进而提出针对性的建议。     

一种高铁CTC进路数据自动测试方法的设计与实现

调度集中系统与计算机联锁接口中的进路数据的测试存在工作量繁重、耗时长以及人为因素易出错等问题,针对该问题提出一种自动测试方法,可有效的解决进路数据的自动测试及测试结果的自动分析,多条高铁线路实践表明,能显著提高调度集中系统与计算机联锁接口的测试效率及数据正确率,使CTC系统产品更安全可靠。     

泰国三机场高铁列控系统方案研究

对泰国三机场高铁项目的列控系统选择要求进行分析,提出列控系统方案并进行综合比选,最后提出泰国三机场高铁项目的列控系统推荐方案,研究成果可以为海外项目列控系统方案选择提供一定的参考。     

ROV attitude control based on multi-motor cooperative propulsion北大核心CSCD

[目的]为了提高遥控水下航行器(ROV)在复杂水下环境中的姿态控制性能,开展多电机协同推进的ROV姿态控制研究。[方法]首先,针对多电机系统的结构和算法,分别提出一种基于PID速度补偿器的偏差耦合结构和一种新型非奇异终端滑模控制(SMC)算法,并设计一种新颖的基于多电机协同推进的ROV姿态控制方法;然后,建立ROV的运动学和动力学模型,开展推进器组推力建模分析、解耦简化ROV动力学模型研究;最后,设计一种ROV滑模姿态控制器。[结果]仿真结果表明,所提的结构和算法可提高多电机系统的抗干扰性、同步性和快速响应能力,进而提高ROV姿态控制系统的稳定性与鲁棒性。[结论]所提方法可为ROV姿态控制提供一种新的可用方案。     

引水隧洞突涌段变形特征及控制关键技术研究

深埋引水隧洞突泥突水洞段注浆固结圈与初期支护结构作为协同承载结构,其荷载分担与变形控制对结构和施工安全有重要作用。为研究深埋引水隧洞突涌洞段围岩与支护体系稳定性,以滇中引水狮子山隧洞为工程依托,通过现场对围岩-支护监控量测与第二层型钢拱架受力监测,结合施工工况动态分析围岩-支护体系受力与变形,研究总结突涌段施工变形控制关键技术。研究结论:(1)深埋隧洞突涌洞段拱顶累计沉降17.4 mm,达预留值的17%左右;拱肩、拱腰累计收敛106.6 mm、98.1 mm,达预留值100%左右。(2)突涌洞段理论预测极限位移150 mm;现场监测评价设定阈值uo=100 mm,当达到2/3时,应采取加强措施。(3)最佳开挖方法为微台阶法。各级台阶长度控制在3 m左右,按“快挖、快支、快封闭”原则组织施工。(4)超前预支护管棚结构起到提高固结体刚度作用,较固结体提高约13倍。(5)双层支护结构强度、刚度增加,承载能力明显提高,施工安全性也得以提高。     

Economic and ecological optimization of electric bus charging considering variable electricity prices and CO2eq intensities

In many cities, diesel buses are being replaced by electric buses with the aim of reducing local emissions and thus improving air quality. The protection of the environment and the health of the population is the highest priority of our society. For the transport companies that operate these buses, not only ecological issues but also economic issues are of great importance. Due to the high purchase costs of electric buses compared to conventional buses, operators are forced to use electric vehicles in a targeted manner in order to ensure amortization over the service life of the vehicles. A compromise between ecology and economy must be found in order to both protect the environment and ensure economical operation of the buses.In this study, we present a new methodology for optimizing the vehicles’ charging time as a function of the parameters CO_2eq emissions and electricity costs. Based on recorded driving profiles in daily bus operation, the energy demands of conventional and electric buses are calculated for the passenger transportation in the city of Aachen in 2017. Different charging scenarios are defined to analyze the influence of the temporal variability of CO_2eq intensity and electricity price on the environmental impact and economy of the bus. For every individual day of a year, charging periods with the lowest and highest costs and emissions are identified and recommendations for daily bus operation are made. To enable both the ecological and economical operation of the bus, the parameters of electricity price and CO₂ are weighted differently, and several charging periods are proposed, taking into account the priorities previously set. A sensitivity analysis is carried out to evaluate the influence of selected parameters and to derive recommendations for improving the ecological and economic balance of the battery-powered electric vehicle.In all scenarios, the optimization of the charging period results in energy cost savings of a maximum of 13.6% compared to charging at a fixed electricity price. The savings potential of CO_2eq emissions is similar, at 14.9%. From an economic point of view, charging between 2 a.m. and 4 a.m. results in the lowest energy costs on average. The CO_2eq intensity is also low in this period, but midday charging leads to the largest savings in CO_2eq emissions. From a life cycle perspective, the electric bus is not economically competitive with the conventional bus. However, from an ecological point of view, the electric bus saves on average 37.5% CO_2eq emissions over its service life compared to the diesel bus. The reduction potential is maximized if the electric vehicle exclusively consumes electricity from solar and wind power.     

新冠肺炎交通防控政策对长沙市人口流动的影响

为探究新冠肺炎疫情下交通防控政策对长沙市人口流动的影响，本文根据长沙市在新冠 肺炎疫情期间颁布的交通防控政策和疫情实时防控情况划分防控阶段，基于百度迁徙大数据，利 用双重差分模型，识别长沙市不同阶段的交通防控政策以及量化防控效果，分析交通防控政策对 长沙市人口流动的影响。结果显示，长沙市在交通管制阶段，平均人口迁出强度、平均人口迁入 强度及城市内部出行强度分别下降了83.68%、69.24%及59.74%，有效地控制了人口流动，降低了 疫情扩散危险。在交通恢复阶段，长沙市人口流动强度逐渐反弹，城市内部出行强度基本恢复到 2019年同期水平。本文研究结果显示了交通管制对疫情扩散限制的有效性，为常态化疫情防控 下精准防控政策和复工复产政策制定提供参考。     

面向新型混合交通流的智能交叉口网络布局优化

考虑网联自动驾驶车辆(Connected Autonomous Vehicle, CAV)应用先进的车联网与自动驾驶技术，可以采用智能交叉口的组织形式，大幅提升交叉口的通行效率，为降低CAV与人工驾驶车辆(Human-driven Vehicle, HV)混行条件下城市交通系统的整体出行成本，提出智能交叉口在城 市交通网络中的布局优化问题，建立数学优化模型并求解。首先，基于对两类车辆行驶特性的分析，建立混合用户均衡模型，描述CAV与HV的路径选择行为；其次，从交通规划者的角度，以系统最优为目标，整合混合用户均衡模型，建立面向新型混合交通流的智能交叉口网络布局优化模型，并利用改进的遗传算法求解；最后，选取Sioux-Falls交通网络作为案例分析，验证模型与算法的有效性，并研究CAV渗透率变化对优化结果的影响。研究表明，智能交叉口在城市路网中的合理规划极大地提高了新型混行场景下城市交通系统的出行效率，同时，大幅降低了由于网联自动 驾驶单方面技术优势带来的CAV与HV的出行效率差距，增进了出行公平性。     

改善地铁列车运行舒适度方案探讨

通过分析轨道交通信号系统的基本控车原理,结合车辆牵引制动系统的特点,找出信号与车辆配合控车存在的难点,提出改善列车运行舒适度的可行性方案,并进行探讨。     

某款商用汽车电堆散热系统方案设计

从商用汽车电堆散热系统设计要求的实际角度出发设计系统原理图,从而进行计算匹配及选型零部件,对所选零部件进行仿真校核是否满足最初的设计要求,保证商用汽车电堆散热系统的正常工作。