Integrated models of land use and transportation for the autonomous vehicle revolution

ABSTRACT

The advent of the autonomous vehicle (AV) will affect not only the transportation system, but also future patterns of land development. Integrated land use and transportation models will be critical tools in assessing the path forward with this technology. Key questions with respect to land use impacts of AVs arise from potential changes in sensitivity to travel and reduced demand for parking. It is an open question whether AVs will induce urban sprawl, or whether spatial economies of agglomeration will mitigate any reductions in travel time sensitivity. The deployment of shared fleets of AVs would likely reduce parking demand, producing yet to be explored impacts on property development within existing urban footprints. We perform a critical assessment of currently operational models and their ability to represent the adoption of AVs. We identify the representation of time in such models as a vital component requiring additional development to model this new technology. Existing model applications have focused on the discrete addition of new infrastructure or policy at a fixed point in time, whereas AV adoption will occur incrementally through time. Stated adaptation surveys are recommended as tools to quantify preferences and develop relevant model inputs. It is argued that existing models that assume comparatively static equilibrium have been convenient in the past, but are insufficient to model technology adoption. In contrast, dynamic model frameworks lack sufficient structure to maintain reasonability under large perturbations from base conditions. The ongoing advancement of computing has allowed models to move away from being mechanistic aggregate tools, towards behaviourally rich depictions of individual persons and firms. However, much work remains to move from projections of existing conditions into the future, to the evolution of the spatial economy as it evolves through time in response to new technologies and exogenous stresses. Principles from complex and evolutionary systems theory will be important in the development of models with the capacity to consider such dynamics.     

轨道交通车辆抗侧滚结构形式的选型分析

介绍了抗侧滚刚度对轨道交通车辆性能的影响。通过对车辆的控制方式、抵抗侧风能力、动力学性能和柔度系数4个方面的分析研究来确定轨道交通车辆的抗侧滚结构形式,为车辆抗侧滚结构形式的选择提供了理论依据。研究表明:当车辆采用两点控制时必须设置抗侧滚扭杆来提高车辆的抗侧滚能力;当车辆采用四点控制时可考虑增大空气弹簧的跨距和设置抗侧滚扭杆来提高车辆的抗侧滚能力。     

A design methodology for mechatronic vehicles: application of multidisciplinary optimization,multibody dynamics and genetic algorithms

A design methodology for mechatronic vehicles is presented. With multidisciplinary optimization (MDO) methods, strongly coupled mechanical, control and other subsystems are integrated as a synergistic vehicle system. With genetic algorithms (GAs) at the system level, the mechanical, control and other relevant parameters can be optimized simultaneously. To demonstrate the feasibility and efficacy of the proposed design methodology for mechatronic vehicles, it is used to resolve the conflicting requirements for ride comfort, suspension working spaces and unsprung mass dynamic loads in the optimization of half-vehicle models with active suspensions. Both deterministic and random road excitations, both rigid and flexible vehicle bodies and both perfect measurement of full state variables and estimated limited state variables are considered. Numerical results show that the optimized vehicle systems based on the methodology have better overall performance than those using the linear quadratic Gaussian (LQG) controller. It is shown that the methodology is suitable for complex design optimization problems where: (1) there is interaction between different disciplines or subsystems; (2) there are multiple design criteria; (3) there are multiple local optima; (4) there is no need for sensitivity analysis for the optimizer at the system level; and (5) there are multiple design variables.     

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.     

Real-time model predictive control of connected electric vehicles

ABSTRACT

Electric Vehicles (EVs) motors develop high torque at low speeds, resulting in a high rate of acceleration with the added advantage of being fitted with smaller gearboxes. However, a rapid rise of torque in EVs fitted with central drive powertrains can create undesired torsional oscillations, which are influenced by wheel slip and flexibility in the halfshaft. These torsional oscillations in the halfshaft lead to longitudinal oscillations in the vehicle, thus creating problems with regard to comfort and drivability. The significance of using wheel slip in addition to halfshaft torsion for design of anti-jerk controllers for EVs has already been highlighted in our previous research. In this research, we have designed a look-ahead model predictive controller (LA-MPC) that calculates the required motor torque demand to meet the dual objectives of increased traction and anti-jerk control. The designed LA-MPC will improve drivability and energy consumption in connected EVs. The real-time capability of the LA-MPC has been demonstrated through hardware-in-the-loop experiments. The performance of the LA-MPC has been compared to other controllers presented in the literature. A validated high-fidelity longitudinal-dynamics model of the Rav4EV, which is the test vehicle of our research has been used to evaluate the controller.     

轻型不锈钢车体结构研究

介绍了不锈钢车体的性能,分析了不锈钢车体结构设计的关键技术,讨论了轻型不锈钢车体结构.我国应首先解决不锈钢型材的配套问题,并制定相应的技术规范,发展不锈钢车体的生产.     

高速列车横向悬挂主动、半主动控制技术的研究

针对铁路机车车辆横向悬挂系统存在的振动问题,提出了一种基于力和加速度反馈的旨在抑制振动的主动、半主动控制方案。介绍了主动、半主动控制原理,相应的执行机构和控制器的构成,整车试验的试验方法和部分试验结果。试验表明:采用主动、半主动控制技术以后,机车车辆的运行平稳性指标得到了较大的提高,列车的运行品质得到了明显改善。     

地铁车辆辅助逆变器的设计与仿真

以地铁车辆用DC1500V/160kVA辅助逆变器为例,阐述了采用IGBT作为主要开关元件的主电路及其控制系统,并利用MATLAB/SIMULINK进行仿真验证其可行性,最后给出了采用电压空间矢量控制的仿真结果。     

轨道车辆微动塞拉门

针对现行城市轨道车辆上使用塞拉门系统“关门难”的现象,分析了乘客拥挤情况下门系统的受力状况。提出了一种新型的按照欧洲及国际标准进行设计和制造的微动塞拉门:在最大防挤压力相同的前提下,微动塞拉门关门时门系统能够承受的人体阻力接近现行塞拉门的4倍;且由于微动塞拉门的塞拉距离减小,拥挤的乘客作用在门板上的人体阻力显著降低,约为现行塞拉门的1/5。从而解决了塞拉门“关门难”的问题。     

CANoe和CAPL语言在整车级故障测试中的应用

故障测试是零件的重要测试之一,但在整车上故障测试则存在极大的限制.文章基于CANoe及CAPL语言实现的复杂报文发送功能,讨论CANoe和CAPL语言在纯电动汽车整车级故障测试的应用.