电喷汽油机可变进气系统的优化设计

利用发动机一维气体流动模拟程序，对某电喷汽油机进气系统的流动过程进行了模拟计算。对该汽油机采用的可变进气系统的歧管直径和长度、控制阀开关的切换转速等结构参数进行了优化设计。计算结果表明，与原机相比，经优化设计后系统的充气效率最大增加幅值大于11％，且改变了充气效率随转速的变化趋势。分析了配气正时对可变进气系统充气效率的影响。     

蒙特卡洛法在边坡锚杆优化设计中的应用

在边坡可靠性分析的基础上，以边坡几何形状，边坡加固为设计变量，建立了以经济指标为设计目标的目标函数，并采用蒙特卡洛法进行锚杆边坡的优化设计。     

应力约束下车架的结构拓扑优化设计

根据汽车车架的结构及受力特点，建立了汽车车架结构拓扑优化模型，对薄板结构的极限应力分析表明，应力约束下汽车车架结构拓扑优化可用薄板结构尺寸优化方法的数学模型来描述，并用修改的满应力法求解。文中的数值结果表明这个方法是有效的算法。     

考虑汽车档位使用率的传动比优化设计

在汽车整车参数和发动机等已确定的情况下，传动比对整车动力性和燃油经济性很大影响，本文根据发动机的外特性和万有特性，结合汽车的档位使用率，探讨如何选择传动系的传动比及其优化问题，最后给出了传动比优化的算例，优化结果与国内外先进变速器的速比设置相比符合得较好。     

Optimum design of tilting bogie frame in consideration of fatigue strength and weight

This paper addresses the use of finite-element (FE) analysis to calculate the fatigue strength of a bogie frame, for the development of tilting trains in Korea. A multi-body dynamic analysis was performed to extract the load condition by tilting on curves. Using the results of the multi-body dynamic analysis and the load scenario setout in the UIC standard, FE analysis was performed to obtain the stress distribution and to calculate the fatigue strength. An attempt was made to minimize the weight of the bogie frame using a back-propagation artificial neural network (ANN). The results of this study reveal that the stresses at some nodes are near the fatigue limit in the Goodman diagram and by using back-propagation ANN, the weight of the bogie frame could be reduced by 4.7%.     

基于遗传算法的舰船航速模糊控制研究

研究并建立了舰船航速控制系统的数学模型,并将模糊控制理论应用到该系统,提出了一种基于遗传算法的舰船航速模糊控制新方法。该方法较常规的模糊控制具有更优的控制性能,仿真实验结果表明该方法可行、有效。     

Integrated solution for anomalous driving detection based on BeiDou/GPS/IMU measurements

There has been an increasing role played by Global Navigation Satellite Systems (GNSS) in Intelligent Transportation System (ITS) applications in recent decades. In particular, centimeter/decimetre positioning accuracy is required for some safety related applications, such as lane control, collision avoidance, and intelligent speed assistance. Lane-level Anomalous driving detection underpins these safety-related ITS applications. The two major issues associated with such detection are (1) accessing high accuracy vehicle positioning and dynamic parameters; and (2) extraction of irregular driving patterns from such information. This paper introduces a new integrated framework for detecting lane-level anomalous driving, by combining Global Positioning Systems (GPS), BeiDou, and Inertial Measurement Unit (IMU) with advanced algorithms. Specifically, we use Unscented Particle Filter (UPF) to perform data fusion with different positioning sources. The detection of different types of Anomalous driving is achieved based on the application of a Fuzzy Inference System (FIS) with a newly introduced velocity-based indicator. The framework proposed in this paper yield significantly improved accuracy in terms of positioning and Anomalous driving detection compared to state-of-the-art, while offering an economically viable solution for performing these tasks.     

An easy procedure to determine Magic Formula parameters: a comparative study between the starting value optimization technique and the IMMa optimization algorithm

In 2004, a new searching algorithm for Magic Formula tyre model parameters was presented. Now, a summary of the results, for pure and combined slip, that this algorithm is able to achieve is presented. The Magic Formula tyre model needs a set of parameters to describe the tyre properties. The determination of these parameters is dealt with in this article. A new method, called IMMa Optimization Algorithm (IOA), based on genetic techniques, is used to determine these parameters. Here, we show the computational cost that has been used to obtain the optimum parameters of every characteristic of the Magic Formula tyre model, called Delft Tyre 96. The main advantages of the method are its simplicity of implementation and its fast convergence to optimal solution, with no need of deep knowledge of the searching space. Hence, to start the search, it is not necessary to know a set of starting values of the Magic Formula parameters (null sensitivity to starting values). The search can be started with a randomly generated set of parameters between [0, 1]. Nowadays, MF-Tool, an application developed by TNO, uses an optimization technique to fit Magic Formula parameters from Matlab toolbox [van Oosten, J.J.M. and Bakker, E., 1993, {Determination of magic tyre model parameters}. Vehicle System Dynamics, 21, 19–29; van Oosten, J.J.M., Savi, C., Augustin, M., Bouhet, O., Sommer, J. and Colinot, J.P., 1999, {Time, tire, measurements, forces and moments, a new standard for steady state cornering tyre testing}. EAEC Conference, Barcelona, 30 June–2 July.]. We refer to that algorithm as the starting value optimization technique. The comparison between the optimization technique employed by TNO and the proposed IOA method is discussed in this article. In order to give a relative idea of adjustment accuracy, the sum-squared error and the mean-squared error, from the curves of the tyre model with the parameters optimized by both applications compared with test data are evaluated.     

Ant Colony Routing algorithm for freeway networks

Dynamic traffic routing refers to the process of (re)directing vehicles at junctions in a traffic network according to the evolving traffic conditions. The traffic management center can determine desired routes for drivers in order to optimize the performance of the traffic network by dynamic traffic routing. However, a traffic network may have thousands of links and nodes, resulting in a large-scale and computationally complex non-linear, non-convex optimization problem. To solve this problem, Ant Colony Optimization (ACO) is chosen as the optimization method in this paper because of its powerful optimization heuristic for combinatorial optimization problems. ACO is implemented online to determine the control signal – i.e., the splitting rates at each node. However, using standard ACO for traffic routing is characterized by four main disadvantages: 1. traffic flows for different origins and destinations cannot be distinguished; 2. all ants may converge to one route, causing congestion; 3. constraints cannot be taken into account; and 4. neither can dynamic link costs. These problems are addressed by adopting a novel ACO algorithm with stench pheromone and with colored ants, called Ant Colony Routing (ACR). Using the stench pheromone, the ACR algorithm can distribute the vehicles over the traffic network with less or no traffic congestion, as well as reduce the number of vehicles near some sensitive zones, such as hospitals and schools. With colored ants, the traffic flows for multiple origins and destinations can be represented. The proposed approach is also implemented in a simulation-based case study in the Walcheren area, the Netherlands, illustrating the effectiveness of the approach.     

隧道下穿运营机场跑道的爆破振动安全判据研究

以我国第一座采用钻爆法下穿运营机场跑道的隧道恩施金凤大道许家坪隧道工程为依托,开展对机场跑道的爆破动力安全判据的研究。首先基于应力波传播理论及极限拉应力准则,对爆炸应力波传播至机场跑道上表面(即自由面)处发生的反射进行理论分析,建立基于混凝土跑道结构安全的爆破振动速度判据模型,并提出跑道的爆破振动速度安全阈值;同时,基于数值模拟,从统计角度建立拉应力峰值与质点振动速度峰值之间的函数关系,求解得到机场跑道的爆破振动速度安全阈值。最后,将理论分析结果、数值计算分析与《爆破安全规程》进行对比分析,最终确定机场跑道的爆破振动速度安全判据,为在隧道下穿机场跑道爆破施工提供了依据。