Design and development of automotive blind spot detection radar system based on ROI pre-processing scheme

In the conventional 2D-FFT based target detection method, all range-Doppler cells are computed by FFT (Fast Fourier Transform) and scanned by CA-CFAR (Cell-Averaging Constant False Alarm Rate) detection. This results in high computational complexity and long processing time. In this paper, we developed an automotive 24 GHz BSD (Blind Spot Detection) FMCW (Frequency Modulated Continuous Wave) radar with a low complexity target detection architecture based on a ROI (Region Of Interest) pre-processing scheme. In the real BSD zone, because the number of cars to be detected is limited, the designed method only extracts their velocities corresponding to the range ROIs in which real targets exist. Moreover, the presence probability of vehicles with the same range-bin but different velocities is very low. Thus, in the designed method, some Doppler ROIs cells with a high magnitude are only applied for CA-CFAR detection. This architecture can dramatically reduce the amount of data to be processed compared to that of the conventional 2D FFT based method, resulting in enhanced processing time. We developed a 24 GHz FMCW radar system composed a transceiver, antennas, and signal processing module. The designed algorithm was implemented in a tiny micro-processor of the signal processing module. By implementing our proposed algorithm in the developed 24 GHz FMCW radar system in an anechoic chamber and a real road, we verified that the range and velocity of a car occupying the BSD zone were detected. Compared to that of the conventional method, the reduction ratio of the total processing time was measured to be 52.4 %.     

Calibration efficiency improvement of rule-based energy management system for a plug-in hybrid electric vehicle

This paper presents a calibration method of a rule-based energy management strategy designed for a plug-in hybrid electric vehicle, which aims to find the optimal set of control parameters to compromise within the conflicting calibration requirements (e.g. emissions and economy). A comprehensive evaluating indicator covering emissions and economy performance is constructed by the method of radar chart. Moreover, a radial basis functions (RBFs) neural network model is proposed to establish a precise model within the control parameters and the comprehensive evaluation indicator. The best set of control parameters under offline calibration is gained by the multi-island genetic algorithm. Finally, the offline calibration results are compared with the experimental results using a chassis dynamometer. The comparison results validate the effectiveness of the proposed offline calibrating approach, which is based on the radar chart method and the RBF neural network model on vehicle performance improvement and calibrating efficiency.     

Experimental study on performance characteristics of cold storage heat exchanger for ISG vehicle

The ISG (Idle Stop and Go) system isvery useful in the automobile industry because it increases fuel consumption and reduces green house gas emissions. However, when the engine is on standby, the air-conditioning system does not work due to compressor inactivity, causing thermal discomfort to passengers. This study examines the thermal storage system, which is a cold storage heat exchanger integrated with a current evaporator. The experiments were conducted for an optimum cold storage heat exchanger design with various fin heights and densities, a number of stacking evaporator plates, refrigerant flow circuits inside the evaporator, and PCMs (Phase Change Materials) in the heat exchanger. The effects of coldness-release performance were examined with various ambient temperatures and air flow volume rates to the cold storage heat exchanger. The visualization of PCM’s freezing and melting was conducted with the cold storage heat exchanger. From the results, we found that the air discharge temperature of the air-conditioning system that was applied to the optimum cold storage heat exchanger was delayed around 540 seconds compared to the current air-conditioning system to reach 24 °C. Thus we can say that the cold storage heat exchanger integrated with an evaporator is an effective solution for ISG vehicles in maintaining thermal comfort in vehicle cabins during short engine stops.     

Travel experience matters: Expected personal mobility impacts after simulated L3/L4 automated driving

Transportation - Automated vehicles (AVs) are expected to change personal mobility in the near future. Most studies on the mobility impacts of AVs focus on fully automated (SAE L5) vehicles, but...     

特长高速公路隧道通风斜井钢波纹板式中隔墙技术研究北大核心CSCD

通风导洞中隔墙一般采用技术较为成熟的混凝土中隔墙,但存在表面粗糙、工艺复杂、施工进度不易控制等缺点,无法适用于风道较为复杂的工程。文章以东天山隧道1号斜井为依托,提出了节能型全拼装式钢波纹板中隔墙技术,通过数值模拟以及理论计算的方法验证其在单洞四风道通风斜井中的可行性。研究结果表明:钢波纹板式中隔墙增大了斜井有效通风截面积,断面风速降低约5.3%,同时大幅减小通风斜井内的沿程阻力,仅为既有混凝土墙方案的17%左右;拱顶变形及二次衬砌混凝土结构受力均远低于结构安全限值。该技术克服了传统钢筋混凝土中隔墙的缺点,在满足隧道通风防灾要求的同时,改善了隧道施工环境,且施工工期可缩短为原方案的三分之一。     

Performance decay of stern bearing based on lubrication numerical model and state parameters北大核心CSCD

[目的]为了实现对船舶艉轴承润滑状态的监测和评估,提出一种结合润滑性能衰变模型和支持向量机(SVM)算法的艉轴承润滑性能评估方法。[方法]针对船舶艉轴承润滑状态难以监测和识别的问题,建立轴承润滑衰变数值模型,并运用实验数据对该模型进行验证,研究载荷、粗糙度和半径间隙对润滑状态衰变机理的影响。基于SVM算法,构建润滑状态分类器,通过网格搜索算法优化超参数,利用不同润滑状态的数据集进行训练,最后实现对艉轴承润滑状态的评估。[结果]结果显示,随着外部载荷、粗糙度和半径间隙的增大,轴承润滑状态恶化的临界速度增大,动压润滑工作范围减小,混合润滑工作范围增大;由仿真数据集对润滑状态识别模型的验证表明,所提的润滑状态识别方法准确率达96.88%。[结论]所提方法能监测轴承的润滑性能特征,有效识别轴承的润滑状态。     

铁路隧道钻爆法机械化修建设计关键技术北大核心CSCD

隧道钻爆法机械化修建方法是以全工序高效率大型机械配套为基础,用以解决复杂山区长大山岭隧道安全、优质、高效及经济等施工问题的一种技术方法。文章从隧道设计角度论述了钻爆法机械化修建面临的掌子面安全控制与洞身段变形控制两大关键挑战,并总结了以机械化全断面全地质型施工技术、掌子面稳定性评价方法、掌子面超前主动支护技术、掌子面超前支护“定量化”精准设计技术、低预应力锚杆主动支护技术、早高强喷混凝土主动支护技术、初期支护快速成环封闭技术、围岩形变压力计算方法等为核心的隧道钻爆法机械化修建设计关键技术,为推广应用隧道钻爆法机械化修建方法提供技术支撑。     

Inertia effects of past behavior in commuting modal shift behavior: interactions,variations and implications for demand estimation

Transportation - This paper focuses on empirically investigating the inertia effects of past behavior in commuting modal shift behavior and contributes to the current state of the art by three...     

贵阳岩溶地层地铁盾构隧道工程中新型球状碳化钨刀具的研究与应用北大核心CSCD

在贵阳轨道交通3号线盾构隧道施工中,采用普通刀具易出现滚刀多边形磨损、偏磨、刀刃崩裂等异常磨损和刀圈脱落现象。为改进滚刀刀圈的耐磨、耐冲击性能,提高刀具的综合寿命,提出采用球状碳化钨刀具替换普通刀具,并介绍了激光熔覆焊工艺以及宏观磨损检测工艺。经过施工现场的实际应用,发现球状碳化钨刀具具有更好的耐磨性,新型球状碳化钨刀具平均磨损量为0.00255 mm/延米,相邻普通刀具平均磨损量为0.01655 mm/延米。在第338~736环掘进中,新型球状碳化钨刀具最大磨损量为0.015 mm/延米,刀具无崩刃现象,滚刀轴承、密封等均无异常,有效解决了普通刀具易磨损、磨损不均的问题,为喀斯特地质条件下盾构刀具的选型提供参考。     

采用自动识别系统对水下输气管线、离岸平台和船舶检验评分的实时监测（英文）

The aim of this research is to develop an algorithm and application that can perform real-time monitoring of the safety operation of offshore platforms and subsea gas pipelines as well as determine the need for ship inspection using data obtained from automatic identification system(AIS). The research also focuses on the integration of shipping database,AIS data, and others to develop a prototype for designing a real-time monitoring system of offshore platforms and pipelines. A simple concept is used in the development of this prototype, which is achieved by using an overlaying map that outlines the coordinates of the offshore platform and subsea gas pipeline with the ship's coordinates(longitude/latitude) as detected by AIS. Using such information, we can then build an early warning system(EWS) relayed through short message service(SMS), email, or other means when the ship enters the restricted and exclusion zone of platforms and pipelines. The ship inspection system is developed by combining several attributes. Then, decision analysis software is employed to prioritize the vessel's four attributes, including ship age, ship type, classification, and flag state.Results show that the EWS can increase the safety level of offshore platforms and pipelines, as well as the efficient use of patrol boats in monitoring the safety of the facilities. Meanwhile, ship inspection enables the port to prioritize the ship to be inspected in accordance with the priority ranking inspection score.