混合能源控制技术及应用

本文介绍了混合能源控制器的功能和特点,以及多种能源混合供电的工作流程,并对混合能源的典型应用场景进行分析说明.     

混合对转推进系统设计与实船应用研究

为全面深入了解混合对转推进系统实船安装对船舶性能影响,为数值仿真和性能预报提供实船参考数据,以集装箱运输船为应用对象,提出了一种把吊舱推进器集成在挂舵臂上的混合对转推进系统(CRP-POD),详细阐述了CRP-POD的系统构成、工作模式和电气控制系统实船设计方案。通过实船试验和运行数据分析,安装混合对转推进系统的船舶与同系列安装常规推进系统的船舶相比,特定航行工况下航速有2~3%的提升、回转能力有所降低、航向稳定性上优于常规船。     

混合动力电动汽车技术现状及发展前景

混合动力电动汽车（HEV）已经成为当前汽车行业研究的热点。介绍了混合动力电动汽车的发展状况、动力系统的类型及特征,详细论述了混合动力电动汽车的关键技术,并对混合动力电动汽车的发展前景进行了探讨。     

Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications in China

Short-term forecasting of high-speed rail (HSR) passenger flow provides daily ridership estimates that account for day-to-day demand variations in the near future (e.g., next week, next month). It is one of the most critical tasks in high-speed passenger rail planning, operational decision-making and dynamic operation adjustment. An accurate short-term HSR demand prediction provides a basis for effective rail revenue management. In this paper, a hybrid short-term demand forecasting approach is developed by combining the ensemble empirical mode decomposition (EEMD) and grey support vector machine (GSVM) models. There are three steps in this hybrid forecasting approach: (i) decompose short-term passenger flow data with noises into a number of intrinsic mode functions (IMFs) and a trend term; (ii) predict each IMF using GSVM calibrated by the particle swarm optimization (PSO); (iii) reconstruct the refined IMF components to produce the final predicted daily HSR passenger flow, where the PSO is also applied to achieve the optimal refactoring combination. This innovative hybrid approach is demonstrated with three typical origin–destination pairs along the Wuhan-Guangzhou HSR in China. Mean absolute percentage errors of the EEMD-GSVM predictions using testing sets are 6.7%, 5.1% and 6.5%, respectively, which are much lower than those of two existing forecasting approaches (support vector machine and autoregressive integrated moving average). Application results indicate that the proposed hybrid forecasting approach performs well in terms of prediction accuracy and is especially suitable for short-term HSR passenger flow forecasting.     

Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas

In today’s world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s personal-fleet evolution.Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings.Twenty five-year simulations of Austin’s household vehicle fleet suggest that, under all scenarios modeled, Austin’s vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, PHEVs and Smart Cars are estimated to represent 25% of the fleet’s VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO₂ emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO₂ emissions by 30% (relative to trend).Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year.In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.     

基于能量守恒和四线法的SOC估算策略研究

传统的电池荷电状态(SOC)估算方法已经不能满足蓄电池变电流放电工况的需要,而混合动力液压挖掘机中蓄电池变电流放电工况异常复杂,因此变电流工况下SOC的准确估算具有重要意义。在能量守恒定律和四线法测量蓄电池内阻的基础上,提出了一种新的SOC估算策略,经过仿真和实验分析,证明新的SOC估算策略能够胜任大电流和变电流放电工况下SOC的估算工作。     

不同混合动力电动轿车方案的比较与分析

设计了同在离合器前与发动机的动力耦合的ISA并联、电机在离合器后变速器前与发动机的动力耦合的一般并联、类似于Prius的混联三种HEV方案。对这三种方案和原轿车的最高车速、原地起步加速特性等动力性指标和基于ECE＋EUDC的100km油耗和续驶里程等能量经济性指标及排施行性进行了仿真和分析。得到相应结论。     

大跨径钢管混凝土拱桥复合非线性研究及合理设计探讨

通过运用结构的复合非线性（几何非线性和材料非线性）极限分析理论，对国内一座在建的368m大跨径钢管混凝土中承式系杆拱桥进行了复合非线性稳定性空间分析，在此基础上，还对该钢管混凝土拱桥主拱肋矢跨比、钢管壁厚及混凝土标号等的设计合理性进行了一些探讨。     

混合动力电动汽车的发展

混合动力电动汽车是当今解决汽车节能与排污问题的有效途径，本文阐述混合动力电动汽车的不同型式和特点，以及目前混合动力电动汽车的发展现状，指出发展混合动力电动汽车必须解决的关键技术问题。     

驾驶循环对车辆能量经济性影响的研究

本文依据国内外具有代表性的不同驾驶循环对一实际的内燃机汽车和一构思的混合动力电动汽车的能量经济性进行了分析。研究了内燃机和电机的运行工况分布，并利用内燃机的万有特性图和电机及其控制系统的等效率曲线以及各驾驶循环的相关特性分析了产不同结果的原因。最后对内燃机汽车和混合动力电动汽车的能量经济性受驾驶循环的影响情况进行了比较和分析。