燃料电池气体温湿度与电堆性能分析

系统性能指标是实现燃料电池工程化应用的瓶颈之一,系统搭建和调试过程中,空气与燃料温湿度是影响质子交换膜燃料电池性能的重要因素,对系统控制策略和辅机搭配方案的制定产生很大影响。本文通过实验与统计相结合的研究方式,研究15 kW燃料电池电堆在增湿温度分别为60℃、70℃和80℃条件下分别进行氢空单侧增湿、双侧增湿和不增湿时的输出功率、发电效率和单电池电压一致性。其中输出功率采用测试台直接测量、发电效率通过经验公式计算、电压一致性则通过巡检记录和统计方法相结合的方式评价。结果表明70℃时各增湿方案下优于其他温度同等湿度条件下的电堆性能,有增湿条件明显优于无增湿方案电堆性能,而双侧增湿和氢空单侧增湿对电堆性能影响不大。     

船舶绿色电源PEMFC及其性能影响因素分析

能源与环境制约了各国经济的持续发展,绿色船舶成为当前船舶行业的发展趋势,燃料电池作为绿色电源在船舶行业具有广阔的应用前景。燃料电池是一种多输入的电化学反应装置,影响因素较多。该文在验证了质子交换膜燃料电池(Proton Exchange Membrane Fuel Cells,PEMFC)稳态建模正确性的基础上,通过稳态建模,利用MATLAB对影响PEMFC性能的各因素进行了分析讨论,并给出了各影响因素的影响大小。最后,在PEMFC的控制和设计上提出了一些指导性的建议。     

有轨电车氢燃料电池系统通风散热方法研究

为解决有轨电车氢燃料电池系统的散热问题,文章提出一种新型车载氢燃料电池系统通风散热方法,分析了该方法的散热原理和控制策略,并对通风散热结构进行了详细介绍.该车载氢燃料电池系统通风散热方法提高了系统散热效率,降低了散热风机能耗.     

基于MapBasic的战时运输最优路径问题研究

战时运输最优路径问题是一个多目标多约束随机动态路网寻优问题。在分析战时运输最优路径问题特性前提下,着重研究战时运输路阻函数模型,求出时间阻抗、风险阻抗和费用阻抗,标定阻抗参数μ1,μ2和μ3,及确定函数模型的MapBasic表达,在给出最优路径模型基础上,利用改进的Dijkstra算法求解。实例验证表明研究成果满足实用要求。     

The use of demand correlation in the modeling of air carrier departure delays as first‐order autoregressive random processes

A method for modeling air carrier departure delays at commercial‐service airports as autoregressive random processes is presented. This method employs the correlation of a priori demand data to significantly reduce prediction error in the optimal least‐squares estimator for additive white noise. The reduction factor of the prediction error is demonstrated to be on the order of 10² over that of the unbiased estimator. Copyright © 2011 John Wiley & Sons, Ltd.     

基于社交网络的民航旅客偏好建模

从社会网络的视角，提出了一种旅客个体偏好与关系偏好相结合的建模方法．首先，从旅客的历史出行记录中，构建基于共同出行关系的旅客社会网络；然后，构建旅客个体偏好模型和旅客关系偏好模型；最后，基于旅客偏好模型给旅客推荐座位．在民航领域的一个真实的数据集上进行了实验，证明本文提出的偏好模型能够有机地将旅客个体偏好与关系偏好结合起来，较好地描述旅客对航班座位的偏好．     

Resolving the property right of transportation emissions through public–private partnerships

The application of public–private partnerships (P3’s) in the transportation sector has grown in popularity worldwide. Despite this important shift in the provision of transportation service, there are clear gaps in knowledge about the impacts of P3 projects, especially on emissions from transportation systems as a whole. Not only should policy makers evaluate the emissions impacts from P3 projects, but they should also think about innovative models that address or charge for emissions into P3 contracts. This addition to P3 contracts could provide a new solution to the long-existing property right paradox: who owns (is responsible for) emissions from transportation systems? This study attempts to fill the research gap by analyzing these innovative models. Using the road network of Fresno, California, as our case study, we offer a number of interesting insights for policy makers. First, average peak emissions costs range from 1.37 cents per mile (the do-nothing case) to 1.20 cents per mile (profit-maximizing cases) per vehicle. Although emissions costs from the P3 projects are lowest for the profit-maximizing cases, the system-wide emissions costs of these cases are highest because of spillover effects. Second, charging project owners for the emissions costs of P3 projects is not an effective way to reduce emissions or the total costs of travel, especially on a VMT basis. Instead, the public sector should implement emissions-included social cost-based price ceilings. When employing these limits, project owners could still be charged for the emissions costs. Finally, using total travel time as the only objective function for evaluating P3 projects can be misleading. Several P3 projects have shown better outcomes using total travel cost with the inclusion of emissions and fuel consumption costs, instead of using total travel time as the only objective function.     

基于浑沌神经网络的动态交通量预测方法研究

介绍了目前国内外道路交通量预测的方法、特点及实际的预测效果.由于城市道路交通的复杂性,使得一些现有交通量预测方法的预测精度不高.针对这些问题,应用混沌神经网络,建立了城市道路交叉口出口交通量的浑沌神经网络预测模型,并与传统的BP神经网络预测结果对比,表明此模型具有较好的预测效果.     

基于神经网络的车用汽油机过渡工况空燃比辨识

以HL495Q电喷汽油机为研究对象,提出了一种基于BP神经网络的空燃比辨识方法,比较了不同拓扑结构的神经网络对空燃比辨识精度的影响,得到了一种最优的空燃比模型。试验结果表明,空燃比模型能高精度地逼近空燃比的实际动态过程,模型的平均相对误差小于2%。     

燃料电池发动机空气参数的最优控制

研究了燃料电池测试平台空气系统的控制算法,目的是获得最佳的空气温度和湿度控制,使得系统调整时间最短。建立了燃料电池空气子系统的温度控制模型和湿度控制模型,给出了控制算法,并将本研究的最优控制算法应用于燃料电池发动机系统;计算结果表明,该算法实现了系统的最优控制。