智能分布式驱动汽车路径跟踪/制动能量回收协同控制策略研究

为了解决智能分布式驱动汽车路径跟踪与制动能量回收系统间的协同控制难题,充分考虑分布式驱动汽车四轮扭矩独立可控在智能驾驶系统中的优势,设计适应不同路面附着条件的智能分布式驱动汽车转向、制动分层协同控制策略。上层控制器依据不同的路面类型设计差异化的多目标代价函数,以综合优化各工况下的控制目标。高附路面下,制定满足最大能量回收值的全局参考车速,在线优化路径跟踪指令,实现最优能量回收的同时减小系统运算负荷;低附路面下,优先考虑车辆的路径跟踪性能和行驶稳定性,在多目标代价函数中取消对全局参考车速的跟随要求,增设终端速度约束与能量回收项性能指标并减小能量回收项性能指标的权重系数。上层控制器基于模型预测控制方法对多目标代价函数进行滚动优化与预测求解,得到期望的前轮转角及4个车轮的总制动扭矩需求。下层控制器根据制动扭矩需求对四轮的液压制动扭矩和电机制动扭矩进行分配,最终完成整个复合制动过程。基于MATLAB/Simulink和CarSim软件,搭建控制器在环仿真平台,并在高附和低附路面条件下对所提出的策略进行试验验证。研究结果表明：高附路面下,所提出的控制策略在准确跟踪期望路径的同时相较固定比例制动力分配方法可提升2.7%的能量回收值并减少约0.02 s的单次计算时间;低附路面下,与使用高附控制策略相比,能够保证车辆的路径跟踪准确性与行驶稳定性,同时可提升7.8%的能量回收值;控制器在环试验结果证明了该协同控制策略对车辆性能提升的有效性。     

Camera calibration and vehicle tracking: Highway traffic video analytics

We describe a real-time highway surveillance system (RHSS), which operates autonomously to collect statistics (speed and volume) and generates incident alerts (e.g., stopped vehicles). The system is designed to optimize long-term real-time performance accuracy. It also provides convenient integration to an existing surveillance infrastructure with different levels of service. Innovations include a novel 3-D Hungarian algorithm which is utilized for object tracking and a practical, hands-off mechanism for camera calibration. Speed is estimated based on trajectories after mapping/alignment with respect to dominant paths learned based on an evolutionary dynamics model. The system, RHSS, is intensively evaluated under different scenarios such as rain, low-contrast and high-contrast lightings. Performance is presented in comparison to a current commercial product. The contribution is innovation of new technologies that enable hands-off calibration (i.e., automatic detection of vanishing points) and improved accuracy (i.e., illumination balancing, tracking via a new 3-D Hungarian algorithm, and re-initialization of background detection on-the-fly). Results indicate the capability and applicability of the proposed system in real-time and real-world settings.     

时频分析在宽带信号检测中的应用研究

该文以时频分析中最典型的Wigner Ville分布在宽带信号检测中的应用展开讨论 ,与传统的处理方法进行比较 ,着重突出了其时频特征分离的特性。对比匹配滤波器进行了宽带确知信号的检测 ,指出基于互Wigner Ville分布的检测方法能够达到匹配滤波器的检测效果。在此基础上提出了采用时变滤波的改进方法 ,最后讨论了信号时宽、带宽对检测性能的影响。     

提高磁浮交通供电系统功率因数的措施

针对上海高速磁浮交通供电系统的滤波、无功补偿设计的特点,分析了供电系统功率因数较低的原因,提出了提高功率因数的技术措施,并分析了该措施的技术、经济效益。最后给出了改进滤波、补偿系统设计的建议。     

About the possibilities of using the renewable energy power sources on railway transport

Several electrification systems based on renewable energy power sources (first of all, solar energy) are discussed in respect to their applicability to railway transport and, in particular, to suburban electric trains. Two systems are considered with basic technical details and economic estimation, both including the onboard bank of batteries and the photovoltaic converters (PVC) of solar energy for compensation of energy expenses, which could be positioned either on stations or on wagon's roofs. Sun‐tracking systems and their effect on the solar energy conversion efficiency are discussed in application to stationary and moving PVC platforms. An analysis made shows that introduction of the “green” systems discussed will not only have positive ecological impact, but also can bring a notable economical effect even with today's components, while it could be considerably greater with the usage of new PVCs, which are being developed by the authors. Copyright © 2011 John Wiley & Sons, Ltd.     

水下多目标跟踪的网络层次决策方法

水下多目标跟踪逻辑与决策是水下航行器多目标跟踪中需解决的技术难点．目前用于水下多目标跟踪决策的方法都假设各个决策因素相互独立，而实际上水下多目标跟踪决策的因素之间存在着相互影响．本文根据这一特点，建立了水下多目标跟踪决策的指标集和相应的ANP决策模型，提出了基于ANP的水下多目标跟踪逻辑与决策方法．该方法将水下多目标跟踪决策的指标集纳入网络层次结构模型，并通过模型解算得到优化的多目标跟踪决策，具有决策结果比现有方法更加合理、稳健的特点．仿真结果表明该方法是在多目标跟踪决策因素之间存在相互影响情况下解决水下多目标跟踪逻辑与决策问题的有效方法．     

模糊自适应滤波在车载组合导航系统中的应用

文章针对车载GPS/DR组合导航系统工作环境复杂,其观测噪声相应复杂多变的特点,引入了一种基于模糊自适应控制的卡尔曼滤波算法。这一方法基于方差匹配的思想,通过模糊控制器在线调整观测噪声方差,以改变滤波器的自适应性,从而提高导航精度。文章最后对GPS/DR系统进行了仿真,结果表明采用此方法后的滤波精度优于常规Kal-man滤波的结果。     

一种船舶电力滤波器的仿真研究

在小型船舶电力推进系统中,变频驱动产生了严重的谐波污染,导致电力系统的容量大大增加,恶化电网电能质量,甚至影响了船舶安全运行.针对电力推进船舶电网存在的谐波污染问题,设计了电力滤波器的拓扑结构,制定其控制策略,分析该滤波器的工作原理,并进行计算机仿真,验证了该滤波器的有效性.     

基于卡尔曼滤波算法的电机转速精确估计

从无刷直流电机入手建立数学模型，利用卡尔曼Kalman（EKF）滤波原理算法，对无刷直流电机的转速进行精确估计，然后在Matlab环境下仿真，验证卡尔曼滤波算法对电机转速估计的精确性。