严格计量程序 确保支付合理

公路工程计量与支付工作是工程建设过程中的重要组成内容，是保证投资的手段，在工程实施过程中，我们应始终坚持公平、公正的原则，明确计量与支付工作的程序，做到“三不计”——不超计、不漏计、不重计。     

虚拟仪器在内燃机测试中的开发应用

提出了一种由笔记本电脑及其专用数据采集器组成的内燃机测试仪器。着重就其工作原理，系统组成，特点及应用情况进行了论述。     

EXCEL在测量资料管理中的应用

测量内业是对外业工作的总结和归档，工作比较繁琐，而将EXCEL应用于测量资料管理中可以化繁为简，减少内业工作强度，提高管理工作水平，故有必要对该方法作一介绍。     

Influence of the heavy fuel spill from the Prestige tanker wreckage in the overlying seawater column levels of copper, nickel and vanadium (NE Atlantic ocean)

The water column above the Prestige wreckage was sampled during two consecutive campaigns: Prestinaut (December 2002) two weeks after the tanker sunk and HidroPrestige0303 (March 2003) one month after the sealing of the main fuel leaks. Samples of the original cargo fuel and the emulsified fuel in the surface of the ocean were also collected. Analysis of the fuel indicated the release of 135 kg of Cu, 1700 kg of Ni and 5300 kg of V from the original fuel to the water column, remaining 35 kg of Cu, 3100 kg of Ni and 13,800 kg of V in the emulsified fuel. The metal partitioning between the water column and the emulsioned floating fuel, Cu > Ni ~ V, are in accordance with the stability index for the metal–nitrogen bond in metalloporphyrins. This release had an impact on dissolved trace metal concentrations in the water column. An increase on dissolved copper (2.8–4.7 nM) and nickel (2.2–8.0 nM) with respect to natural values (1–3 nM for Cu and 1.6–5 nM for Ni) was observed. Values for vanadium (28–35 nM) were in the range of pristine North Atlantic waters (30–36 nM). This contamination was especially observed in the upper water column (0–50 m), associated with the mixing of seawater with the fuel moving upwards, and in deep waters, where the residence time of fuel is higher. Future research in this field should focus on the environmental variables and the processes that control the release of contaminants from fuels for a better assessment of the contamination in oil-spill events.     

Estimation of wheel–rail friction for vehicle certification

In certification of new rail vehicles with respect to running characteristics, a wide variety of operating conditions needs to be considered. However, in associated test runs the wheel–rail friction condition is difficult to handle because the friction coefficient needs to be fairly high and the friction is also generally hard to assess. This is an issue that has been studied in the European project DynoTRAIN and part of the results is presented in this paper. More specifically, an algorithm for estimating the wheel–rail friction coefficient at vehicle certification tests is proposed. Owing to lack of some measurement results, the algorithm here is evaluated in a simulation environment which is also an important step towards practical implementation. A quality measure of the friction estimate is suggested in terms of estimated wheel–rail spin and total creep. It is concluded that, tentatively, the total creep should exceed 0.006 and the spin should be less than 1.0 m^?1 for the algorithm to give a good friction estimate. Sensitivity analysis is carried out to imitate measurement errors, but should be expanded in further work.     

Fast computing and approximate fuel consumption modeling for Internal Combustion Engine passenger cars

This article presents a fuel consumption model, SEFUM (Semi Empirical Fuel Use Modeling), and its comparison with three models from the literature on a 600 km experimental database. This model is easy to calibrate with only a few required parameters that are provided by car manufacturers. The test database has been built from 21 drivers who drove in two conditions (normal and ecodriving) on a 15 km trip. For the model evaluation, three indicators have been selected: instantaneous fuel use root mean square error, cumulated error and computation time in order to evaluate the accuracy both in cumulated and instantaneous fuel use and to estimate computation time of each model. Results tend to prove that the model is able to compute rapidly (maximum of 1500 simulated kilometers under Matlab) in comparison to all other models while ensuring a high accuracy and precision for cumulated and instantaneous fuel use.     

典型工况构建方法对新能源汽车能耗评价的影响分析

新能源汽车的能耗及其经济性与行驶工况高度关联。为了对新能源汽车的能耗进行合理评估，以西安市为例，分别应用聚类分析法、聚类马尔可夫分析法、短行程车速-加速度(Velocity-Acceleration,V-A)矩阵法和变步长V-A矩阵法构建城市客车运行工况，并进一步提出基于自组织映射(Self-organizing Maps,SOM)神经网络聚类的V-A矩阵法。对5种方法构建的工况进行对比和误差分析。在此基础上，基于一款插电式混合动力城市客车，应用全局优化方法——庞特里亚金最小值原理设计能量管理策略，分析车辆能耗和经济性以及5种工况的优缺点。研究结果表明：聚类分析法构建工况的平均特征值误差最大，计算量较大；变步长V-A矩阵法的平均特征值误差小于聚类法，计算量最小；短行程V-A矩阵法与变步长V-A矩阵法误差接近；聚类马尔可夫法的误差居中，计算量最大；基于SOM聚类的V-A矩阵法的平均特征值误差最小，能反映不同路段以及运行时间的差异，且能在聚类之后快速提取短行程的同时兼顾速度和加速度的分布；从能耗角度来看，基于SOM聚类的V-A矩阵法的能耗在5种方法中居中；聚类分析法构建的工况平均车速低于其他工况，但加减速频繁，能耗成本最高；聚类马尔可夫法由于对车速进行平滑处理，加减速频繁程度最小，能耗成本最低。     

Driving cycles that reproduce driving patterns,energy consumptions and tailpipe emissions

This study presents the Energy Based Micro-trip (EBMT) method, which is a new method to construct driving cycles that represent local driving patterns and reproduce the real energy consumption and tailpipe emissions from vehicles in a given region. It uses data of specific energy consumption, speed, and percentage of idling time as criteria of acceptable representativeness. To study the performance of the EBMT, we used a database of speed, fuel consumption, and tailpipe emissions (CO₂, CO, and NO_x), which was obtained monitoring at 1 Hz, the operation of 15 heavy-duty vehicles when they operated within different traffic conditions, during eight months. The speed vs. time data contained in this database defined the local driving pattern, which was described by 19 characteristic parameters (CPs). Using this database, we ran the EBMT and described the resulting driving cycle by 19 characteristics parameters (CPs*). The relative differences between CPs and CPs* quantified how close the obtained driving cycle represented the driving pattern. To observe tendencies of our results, we repeated the process 1000 times and reported the average relative difference (ARD) and the interquartile range (IQR) of those differences for each CP.. We repeated the process for the case of a traditional Micro-trip method and compared to previous results. The driving cycles constructed by the EBMT method showed the lowest values of ARDs and IQRs, meaning that it produces driving cycles with the highest representativeness of the driving patterns, and the best reproduction of energy consumption, and tailpipe emissions.     

Measuring transport related CO2 emissions induced by online and brick-and-mortar retailing

We develop a method for empirically measuring the difference in transport related carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their transport CO₂ footprints by 84% when buying standard consumer electronics products.     

Does traffic-related calibration of car-following models provide accurate estimations of vehicle emissions?

Fuel consumption or pollutant emissions can be assessed by coupling a microscopic traffic flow model with an instantaneous emission model. Traffic models are usually calibrated using goodness of fit indicators related to the traffic behavior. Thus, this paper investigates how such a calibration influences the accuracy of fuel consumption and NOx and PM estimations. Two traffic models are investigated: Newell and Gipps. It appears that the Gipps model provides the closest simulated trajectories when compared to real ones. Interestingly, a reverse ranking is observed for fuel consumption, NOx and PM emissions. For both models, the emissions of single vehicles are very sensitive to the calibration. This is confirmed by a global sensitivity analysis of the Gipps model that shows that non-optimal parameters significantly increase the variance of the outputs. Fortunately, this is no longer the case when emissions are calculated for a group of many vehicles. Indeed, the mean errors for platoons are close to 10% for the Gipps model and always lower than 4% for the Newell model. Another interesting property is that optimal parameters for each vehicle can be replaced by the mean values with no discrepancy for the Newell model and low discrepancies for the Gipps model when calculating the different emission outputs. Finally, this study presents preliminary results that show that multi-objective calibration methods are certainly the best direction for future works on the Gipps model. Indeed, the accuracy of vehicle emissions can be highly improved with negligible counterparts on the traffic model accuracy.