基于多属性决策运输车编配方案研究

在信息化战争中,后勤运输保障举足轻重。根据部队运输需求,制定出科学合理的运输车编配结构对于提高部队公路运输保障能力具有重要的指导意义。分析了我军运输车编配存在的问题,介绍了基于最大离差化的多属性决策模型,为运输车编配方案评价提供了一种合理的研究方法。并以某摩步师直属汽车营为例,对运输车的备选方案进行了排序和选优,得到了...     

商业银行国际贸易融资及其风险防范问题研究

分析了我国商业银行国际贸易融资的发展现状以及出现的问题,将定性分析与定量分析相结合,建立了风险评估的模型,为商业银行进行授信提供了操作工具。最后对我国商业银行国际贸易融资的发展提出了综合性建议。     

城市商业广场地下停车场交通设计若干理念

通过调查,分析了大型商业广场地下停车场的主要特征与使用特点.结合实例,从商业广场地下停车场内外部交通组织、车库内部分区、出口引导标识和人性化交通设施设计等方面出发,论述了大型商业广场地下停车场交通设计的若干理念与具体实现形式,为城市大型商业建筑地下停车场交通设计提供了必要的理念支撑.     

商用车底盘线控技术研究现状及应用进展

底盘线控技术是实现商用车自动驾驶和辅助驾驶功能的关键基础技术,是当今汽车行业的研发热点。底盘线控技术包括线控执行系统和线控集成控制技术两大部分。分别对商用车的线控转向、线控制动、线控悬架、线控驱动和线控换挡等线控执行系统,以及自动紧急制动 （Autonomous Emergency Braking,AEB） 系统、自适应巡航 （Adaptive Cruise Control,ACC） 系统和车道保持辅助 （Lane Keeping Assist,LKA） 系统等线控集成控制技术的构成、控制原理与研究应用现状进行了概述,重点分析了商用车各类构型的线控转向和线控制动系统及其应用场景。结合最新发布的国家智能底盘技术路线框架图和商用车未来的客户需求,给出了商用车线控底盘各技术方向的发展趋势,为商用车线控底盘技术发展提供了参考。     

网联环境下混合交通流偶发拥堵演化机理研究

针对混合交通流中智能网联车辆(Connected and Autonomous Vehicles, CAVs)和人工驾驶车辆的交织干涉问题,本文在传统交通流统计理论模型和一阶连续介质模型的基础上,通过引入智能驾驶员跟驰模型(Intelligent driver model, IDM)和协同自适应巡航控制模型(Cooperative Adaptive Cruise Control, CACC),构建人工驾驶车辆和CAVs的混合交通流偶发拥堵演化模型,探索CAVs混入和诱导干涉措施对混合交通流偶发性拥堵传播规律的影响。实验选取重庆市华陶立交至巴南立交路段为路网原型,对CAVs不同渗透率( Pc )下的路段拥堵演化情况进行仿真。实验结果表明：CAVs渗透率越高,混合流流量、占有率和速度的改善情况越显著,但只有当 Pc ≥ 0.2 时,网联车辆对拥堵消散的改善效果才较为明显;Pc ≤ 0.8 时,干涉措施下,拥堵消散状态的持续时间约为不采用干涉措施的 50%;当 Pc = 1.0 时,网联车辆的通行能力是纯人工驾驶交通流的2.34倍;分别在非干涉措施和干涉措施下计算拥堵评价指标,与仿真结果进行对比,最大相对误差在5.38%之内,验证了模型的准确性。研究成果对疏散交通拥堵具有重要意义。     

嵌入式计算机系统在水下航行器的应用

针对小型水下航行器航行和工作特点,论述了采用嵌入式ＭＣＵ与ＥＤＳＰ器件和Ｉ＾２Ｃ总线技术构成的监测与控制系统。     

城市快速公交专用道道路线形设计分析

以汽车的动力特性和通过特性为理论依据,根据目前快速公交专用车辆大都采用低地板大型铰接底地板车辆的现状,结合其容量比一般普通公交大得多的特点,对快速公交专用道的道路线形设计进行分析,提出设计方法。     

On the equivalent wheelbase of a three-axle vehicle

The steady-state handling properties of a rigid vehicle with a tandem rear axle configuration are developed. This work uses conventions resulting in a parsimonious characterisation of steady-state handling of such three-axle vehicles that is shown to be a simple extension of the well-known two-axle bicycle model. Specifically the concepts of understeer and wheelbase are developed for a three-axle vehicle, and shown to play the same role in characterising vehicle handling as they do in the well-known two-axle vehicle model. An equivalent wheelbase of a three-axle vehicle is expressed in terms of vehicle geometry and cornering stiffness of each axle. The model developed in this work is reconciled with previous models that make use of simplifying assumptions found in the literature.     

Design of safety-oriented control allocation strategies for overactuated electric vehicles

The new vehicle platforms for electric vehicles (EVs) that are becoming available are characterised by actuator redundancy, which makes it possible to jointly optimise different aspects of the vehicle motion. To do this, high-level control objectives are first specified and solved with appropriate control strategies. Then, the resulting virtual control action must be translated into actual actuator commands by a control allocation layer that takes care of computing the forces to be applied at the wheels. This step, in general, is quite demanding as far as computational complexity is considered. In this work, a safety-oriented approach to this problem is proposed. Specifically, a four-wheel steer EV with four in-wheel motors is considered, and the high-level motion controller is designed within a sliding mode framework with conditional integrators. For distributing the forces among the tyres, two control allocation approaches are investigated. The first, based on the extension of the cascading generalised inverse method, is computationally efficient but shows some limitations in dealing with unfeasible force values. To solve the problem, a second allocation algorithm is proposed, which relies on the linearisation of the tyre–road friction constraints. Extensive tests, carried out in the CarSim simulation environment, demonstrate the effectiveness of the proposed approach.     

Fault classification method for the driving safety of electrified vehicles

A fault classification method is proposed which has been applied to an electric vehicle. Potential faults in the different subsystems that can affect the vehicle directional stability were collected in a failure mode and effect analysis. Similar driveline faults were grouped together if they resembled each other with respect to their influence on the vehicle dynamic behaviour. The faults were physically modelled in a simulation environment before they were induced in a detailed vehicle model under normal driving conditions. A special focus was placed on faults in the driveline of electric vehicles employing in-wheel motors of the permanent magnet type. Several failures caused by mechanical and other faults were analysed as well. The fault classification method consists of a controllability ranking developed according to the functional safety standard ISO 26262. The controllability of a fault was determined with three parameters covering the influence of the longitudinal, lateral and yaw motion of the vehicle. The simulation results were analysed and the faults were classified according to their controllability using the proposed method. It was shown that the controllability decreased specifically with increasing lateral acceleration and increasing speed. The results for the electric driveline faults show that this trend cannot be generalised for all the faults, as the controllability deteriorated for some faults during manoeuvres with low lateral acceleration and low speed. The proposed method is generic and can be applied to various other types of road vehicles and faults.