Real-time traffic state estimation in urban corridors from heterogeneous data

In recent years, rapid advances in information technology have led to various data collection systems which are enriching the sources of empirical data for use in transport systems. Currently, traffic data are collected through various sensors including loop detectors, probe vehicles, cell-phones, Bluetooth, video cameras, remote sensing and public transport smart cards. It has been argued that combining the complementary information from multiple sources will generally result in better accuracy, increased robustness and reduced ambiguity. Despite the fact that there have been substantial advances in data assimilation techniques to reconstruct and predict the traffic state from multiple data sources, such methods are generally data-driven and do not fully utilize the power of traffic models. Furthermore, the existing methods are still limited to freeway networks and are not yet applicable in the urban context due to the enhanced complexity of the flow behavior. The main traffic phenomena on urban links are generally caused by the boundary conditions at intersections, un-signalized or signalized, at which the switching of the traffic lights and the turning maneuvers of the road users lead to shock-wave phenomena that propagate upstream of the intersections. This paper develops a new model-based methodology to build up a real-time traffic prediction model for arterial corridors using data from multiple sources, particularly from loop detectors and partial observations from Bluetooth and GPS devices.     

Estimating travel time functions for urban roads: options and issues

Travel time functions specify the relationship between the travel time on a road and the volume of traffic on the road. Until recently, the parameters of travel time functions were rarely estimated in practice; however, a compelling case can be made for the empirical examination of these functions. This paper reviews, and qualitatively evaluates, a range of options for developing a set of travel time functions. A hierarchy of travel time functions is defined based on four levels of network detail: area, corridor, route and link. This hierarchy is illustrated by considering the development of travel time functions for Adelaide. Alternative sources of data for estimating travel time functions are identified.

In general, the costs and benefits increase as the travel time functions are estimated at finer levels of network detail. The costs of developing travel time functions include data acquisition costs and analysis costs. The benefits include the potential for reducing prediction errors, the degree of application flexibility and the policy sensitivity of the travel time functions.     

电动汽车动力电池低温性能研究与应用

电动汽车锂离子动力电池在低温条件下工作时,电池的内阻明显升高、功率和能量急剧下降,导致整车低温下动力性能不足、续驶里程不足、充电受限等问题。通过试验进行了动力电池的低温特性研究,提出了适合整车低温工作的解决方案,通过实车验证,达到了很好的效果。     

Observer-based clutch disengagement control during gear shift process of automated manual transmission

A clutch disengagement strategy is proposed for the shift control of automated manual transmissions. The control strategy is based on a drive shaft torque observer. With the estimated drive shaft torque, the clutch can be disengaged as fast as possible without large driveline oscillations, which contributes to the reduction of total shift time and shift shock. The proposed control strategy is tested on a complete powertrain simulation model. It is verified that the system is robust to the variations of driving conditions, such as vehicle mass and road grade. It is also demonstrated that the revised system with switched gain can provide satisfactory performance even under large estimation error of the engine torque.     

A model-based traction control strategy non-reliant on wheel slip information

A traction control system (TCS) for two-wheel-drive vehicles can conveniently be realised by means of slip control. Such a TCS is modified in this paper in order to be applicable to four-wheel-drive vehicles and anti-lock braking systems, where slip information is not readily available. A reference vehicle model is used to estimate the vehicle velocity. The reference model is excited by a saw-tooth signal in order to adapt the slip for maximum tyre traction performance. The model-based TCS is made robust to vehicle modelling errors by extending it with (i) a superimposed loop of tyre static curve gradient control or (ii) a robust switching controller based on a bi-directional saw-tooth excitation signal. The proposed traction control strategies are verified by experiments and computer simulations.     

Flexible long range planning using low cost information

Contemporary transport planning requires a flexible modelling approach which can be used to monitor the implementation of a long term plan checking regularly its short term performance with easily available data; the original model is periodically updated using low cost information and this allows the evaluation of the changes to the plan which may be required. Such an approach requires models suited to regular updating and to the use of data from different sources. Models to update trip matrices from traffic counts have been available for some time; however, the estimation and/or updating of other model stages with low cost data has escaped analytical treatment. The paper discusses this idea and formulates the updating problem for an example involving a joint destination/mode choice model under various assumptions about the nature of the available data. Analytical solutions are proposed as well as some general conclusions.requests for offprints     

Efficient multiple model particle filtering for joint traffic state estimation and incident detection

This article proposes an efficient multiple model particle filter (EMMPF) to solve the problems of traffic state estimation and incident detection, which requires significantly less computation time compared to existing multiple model nonlinear filters. To incorporate the on ramps and off ramps on the highway, junction solvers for a traffic flow model with incident dynamics are developed. The effectiveness of the proposed EMMPF is assessed using a benchmark hybrid state estimation problem, and using synthetic traffic data generated by a micro-simulation software. Then, the traffic estimation framework is implemented using field data collected on Interstate 880 in California. The results show the EMMPF is capable of estimating the traffic state and detecting incidents and requires an order of magnitude less computation time compared to existing algorithms, especially when the hybrid system has a large number of rare models.     

新能源汽车电池管理方法综述

电池管理系统作为电动汽车的重要组成部分,其中准确估测荷电状态(SOC)和电池均衡管理是电池管理系统的核心功能,也是优化系统能量管理,提高动力电池的使用效率,延长电池使用寿命的关键,对电池的储能至关重要。详细介绍主要SOC的估测方法和电池均衡管理方法,并对其优劣性进行分析与阐述,通过文献综述与对比分析为电池组在使用时提出理论依据与维护措施,为未来的研究提供便捷研究方法。     

某款纯电动车OCV修正致SOC跳变问题的优化

SOC估算有如开路电压法、安时积分法、神经网络法、卡尔曼滤波法等多种方法[1]。江淮某轻型纯电物流车磷酸铁锂电池SOC估算采用较为成熟、稳定的安时积分策略、充电末端Vmax校准及放电末端OCV修正策略[2]。市场车辆在环境14℃~16℃时,放电末端常出现修正导致SOC5~8%幅度的跳变,文章通过对比分析,细化不同温度SOC-OCV矩阵,较好的解决上述问题。     

基于工作电压的动力电池剩余容量动态估算

以单体蓄电池为研究对象，为解决电动汽车动力电池在工作状态下的剩余容量（SOC）进行实时估算的难题，提出了一种新的动力电池剩余容量估算方法。通过外接一个处于工作状态下电池周期性的恒定电流负载，测得一系列的电池工作电压，这些工作电压采用阶段斜率的计算方法求电池该时刻的剩余时间，从而推算出电池的SOC。证明了动态工作点折算到静态工作点的可行性。该方法的相对误差最大不超过7％，通过软件可实施对温度、老化等因素的补偿。误差分析结果表明，该方法误差小，测量精度高。