Life cycle cost of conventional,battery electric,and fuel cell electric vehicles considering traffic and environmental policies in China

Electric vehicles (EVs) are considered a promising alternative to conventional vehicles (CVs) to alleviate the oil crisis and reduce urban air pollution and carbon emissions. Consumers usually focus on the tangible cost when choosing an EV or CV but overlook the time cost for restricting purchase or driving and the environmental cost from gas emissions, falling to have a comprehensive understanding of the economic competitiveness of CVs and EVs. In this study, a life cycle cost model for vehicles is conducted to express traffic and environmental policies in monetary terms, which are called intangible cost and external cost, respectively. Battery electric vehicles (BEVs), fuel cell electric vehicles (FCEVs), and CVs are compared in four first-tier, four new first-tier, and 4 s-tier and below cities in China. The comparison shows that BEVs and FCEVs in most cities are incomparable with CVs in terms of tangible cost. However, the prominent traffic and environmental policies in first-tier cities, especially in Beijing and Shanghai, greatly increase the intangible and external costs of CVs, making consumers more inclined to purchase BEVs and FCEVs. The main policy benefits of BEVs and FCEVs come from three aspects: government subsidies, purchase and driving restrictions, and environmental taxes. With the predictable reduction in government subsidies, traffic and environmental policies present important factors influencing the competitiveness of BEVs and FCEVs. In first-tier cities, BEVs and FCEVs already have a competitive foundation for large-scale promotion. In new first-tier and second-tier and below cities, stricter traffic and environmental policies need to be formulated to offset the negative impact of the reduction in government subsidies on the competitiveness of BEVs and FCEVs. Additionally, a sensitivity analysis reveals that increasing the mileage and reducing fuel prices can significantly improve the competitiveness of BEVs and FCEVs, respectively.     

稀土石膏常压酸化法制备硫酸钙晶须的研究

以含稀土的石膏为原料运用常压酸化法合成硫酸钙晶须,探讨了不同工艺条件对生成的硫酸钙晶须形貌的影响,同时还考察了晶型助长剂的种类和晶型助长剂的含量对硫酸钙晶须生长的影响,利用SEM和XRD分别对硫酸钙晶须的表面形貌、物相特征做了表征分析。实验得到制备硫酸钙晶须的最佳的反应条件：稀土石膏质量浓度为0.22 g/mL、反应时间为25 min、盐酸浓度为2.8 mol/L、反应温度为70 ℃、陈化时间为4 h,在此条件下合成的硫酸钙晶须平均长度为61 μm,平均长径比为30.5;通过对比实验选出了CuCl₂作为促进硫酸钙晶须生长的助长剂,在添加5%（质量分数）的CuCl₂的情况下可使硫酸钙晶须长径比从30.5增至41,长度从61 μm增至81 μm。     

原子吸收光谱法测定保护渣中锰含量

采用原子吸收光谱法测定保护渣中锰含量,进行了酸度对测定的影响、试样分解、共存离子干扰、加标回收、精密度分析等试验。结果表明,锰可完全溶解于混合酸溶液中;加入氯化锶,可以消除钠、钙对锰测定的干扰;锰质量浓度在0~12.0μg/mL的范围,工作曲线线性关系良好;加标回收率较高,在97%~102%;测定结果准确度较高,与高碘酸钠光度法分析结果一致性较好。     

发挥设备专业化优势探索项目建设设备综合管理标准化工作

设备综合管理工作始终贯穿在项目建设整个过程中.从项目立项审查、基础设计审查、设备订货前的技术把关,到工程施工环节的专业技术检查,再到项目中交、联动试车、投料试车,处处可见设备综合管理的内容.本文梳理出设备综合管理的主要节点内容、现状和存在的问题,针对镇海基地项目群的建设,就如何发挥设备专业化的优势、如何对设备综合管理工作进行创新、如何优化工作流程进行了探索.旨在通过设备综合管理工作的统筹和协调,将专业化优势形成合力,更高质量、更高效率地为项目建设服务.     

Thermodynamic analysis of ethanol synthesis from hydration of ethylene coupled with a sequential reaction

Coal-based ethanol production by hydration of ethylene is limited by the low equilibrium ethylene conversion at elevated temperature. To improve ethylene conversion, coupling hydration of ethylene with a potential ethanol consumption reaction was analyzed thermodynamically. Five reactions have been attempted and compared: (1) dehydration of ethanol to ethyl ether ({\mathrm{2C}}_{\mathrm{2}}{\mathrm{H}}_{\mathrm{5}}\mathrm{OH}\iff{\mathrm{C}}_{\mathrm{2}}{\mathrm{H}}_{\mathrm{5}}{\mathrm{OC}}_{\mathrm{2}}{\mathrm{H}}_{\mathrm{5}}{\mathrm{+H}}_{\mathrm{2}}\mathrm{O}), (2) dehydrogenation of ethanol to acetaldehyde ({\mathrm{C}}_{\mathrm{2}}{\mathrm{H}}_{\mathrm{5}}\mathrm{OH}\iff {\mathrm{CH}}_{\mathrm{3}}{\mathrm{CHO+H}}_{\mathrm{2}}), (3) esterification of acetic acid with ethanol ({\mathrm{C}}_{\mathrm{2}}{\mathrm{H}}_{\mathrm{5}}{\mathrm{OH+CH}}_{\mathrm{3}}\mathrm{COOH}\iff {\mathrm{CH}}_{\mathrm{3}}{\mathrm{COOC}}_{\mathrm{2}}{\mathrm{H}}_{\mathrm{5}}{\mathrm{+H}}_{\mathrm{2}}\mathrm{O}), (4) dehydrogenation of ethanol to ethyl acetate ({\mathrm{2C}}_{\mathrm{2}}{\mathrm{H}}_{\mathrm{5}}\mathrm{OH}\iff {\mathrm{CH}}_{\mathrm{3}}{\mathrm{COOC}}_{\mathrm{2}}{\mathrm{H}}_{\mathrm{5}}{\mathrm{+2H}}_{\mathrm{2}}), and (5) oxidative dehydrogenation of ethanol to ethyl acetate ({\mathrm{2C}}_{\mathrm{2}}{\mathrm{H}}_{\mathrm{5}}{\mathrm{OH+O}}_{\mathrm{2}}\iff {\mathrm{CH}}_{\mathrm{3}}{\mathrm{COOC}}_{\mathrm{2}}{\mathrm{H}}_{\mathrm{5}}{\mathrm{+2H}}_{\mathrm{2}}\mathrm{O}). The equilibrium constants and equilibrium distributions of the coupled reactions were calculated and the effects of feed composition, temperature and pressure upon the ethylene equilibrium conversion were examined. The results show that dehydrogenation of ethanol to acetaldehyde has little effect on ethylene conversion, whereas for dehydrogenation of ethanol to acetaldehyde and ethyl acetate, ethylene conversion can be improved from 8% to 12.8% and 18.5%, respectively, under conditions of H₂O/C₂H₄ = 2, 10 atm and 300°C. The esterification of acetic acid with ethanol can greatly enhance the ethylene conversion to 22.5%; in particular, ethylene can be actually completely converted to ethyl acetate by coupling oxidative dehydrogenation of ethanol.     

Wearing prediction of stellite alloys based on opposite degree algorithm

In order to predict the wearing of stellite alloys,the related methods of rare metals data processing were discussed. The method of opposite degree(OD) algorithm was put forward to predict the wearing of stellite alloys.OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation(BP) and radial basis function(RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.     

基于状态空间法的电动机故障诊断和识别

电动机的初期故障信号一般较弱,不易辨别,而状态空间法在小信号的处理中灵敏度很高。为达到对电动机故障的诊断和识别,试图把状态空间法应用到对电动机的故障诊断中,先通过推导,从数学理论层面分析了状态空间法对于电动机故障信号的可辨别性,再使用Matlab软件搭建状态空间的辨别模型,把实验台测试的三组数据导入到模型中进行测试。测试的结果有力地证明了此方法的可行性,并能克服快速傅里叶变换(FFT)中数据采集量较大、分辨率不高的缺点。