内燃机连杆设计计算的若干理论研究

在对多种连杆大量计算的基础上，总结了连杆设计的经验，指出连杆大端对称于中心线的两侧刚度分布均匀，是保证其应力分布均匀的前提，是连杆合理设计的一个重要原则．文中提出，为了保证精度，连杆计算应采用多体接触模型，并对影响计算精度的各种因素做了分析。讨论了螺栓位置和预紧力应如何选取以及齿形制造误差对强度的影响。     

柴油闪急沸腾喷雾的试验研究

通过对柴油机高压油管进行外加热源加热热，在Ｅ１５０柴油机上实现柴油的闪急沸腾喷雾，并对柴油机的性能及排放进行了试验研究。结果表明，采用闪急沸腾喷雾，柴油机油耗可降低８ｇ／ｋＷ．Ｈ，烟度下降０．４ＢＳＵ，ＮＯＸ排放略有升高，ＣＯ，ＨＣ排放均降低。     

BP和RBF神经网络在辨识内燃机燃烧过程中的应用

分析了发动机燃烧过程的研究方式,提出了用BP和RBF网络辨识内燃机燃烧过程的方法。选定神经网络的结构、隐层神经元的作用函数和控制参数,成功地得到了发动机的辨识模型,结果由RBF网络辨识的模型给出,从这一模型可以获得任意点缸内压力和温度以延拓的参数,为排放分析、计算和结构优化提供了良好的基础。     

符号时间序列方法在汽油机燃烧循环变动特征分析中的应用

应用一种新的分析方法———符号时间序列方法对汽油机燃烧循环变动进行了研究。测量得到了某汽油机16种不同工况下的示功图,从提高精度与有利于数据的符号化观点出发,确定以缸内峰值压力作为汽油机燃烧循环变动的表征参数,把符号时间序列分析的具体技术和实施途径应用于试验数据,获得了汽油机燃烧循环变动随转速与负荷的变化规律,提出了利用改进的SHAN NON熵作为汽油机燃烧循环变动的评价指标的新观点。研究结果表明:该方法能较好地应用于汽油机燃烧循环变动特征分析。     

涡流比对双燃料发动机燃烧过程影响的数值分析

利用数值模拟的方法研究了涡流比对柴油引燃天然气发动机燃烧速率的影响。计算软件为经过修改的KIVA-Ⅲ程序。计算对象为具有深盆形燃烧室的发动机。研究表明，当涡流比从0依次增加到2．5、5时，虽然缸内平均湍流强度增加。但最高湍流区湍流强度先升后降；由于燃烧速率赖于当地的湍流强度，而不是缸内的平均湍流强度。所以燃烧速率并不是一直随涡流比增大而增大。     

内燃机振动动力式主动吸振器的研究

振动主动控制技术具有减振效率高，有效减振频率范围度，反应敏捷等优点，在机械振动领域具有广泛的应用前景。在一台四缸柴油机上进行振动主动控制的研究，使用主动控制技术控制动力吸振式的频率，使其能足够发动机的主动振动频率，并保持最佳状态，从而有效地抑制发动机的振动。     

内燃机活塞-缸套-活塞环系统工作状态的识别方法

提出了一种基于证据理论方法的内燃机活塞—缸套—活塞环系统工作状态的识别方法。通过搭建试验台架,从实车试验中获取曲轴箱压力信号和机身振动加速度信号;提取试验特征值,组建模型样本和试验样本,并运用证据理论信息融合方法对内燃机的工作状态进行识别。研究结果表明:应用证据理论信息融合方法融合曲轴箱压力信号和机身振动加速度信号,进而识别活塞—缸套—活塞环系统的工作状态这一方法有效、可行。     

Transport energy consumption in mountainous roads. A comparative case study for internal combustion engines and electric vehicles in Andorra

This paper analyses transport energy consumption of conventional and electric vehicles in mountainous roads. A standard round trip in Andorra has been modelled in order to characterise vehicle dynamics in hilly regions. Two conventional diesel vehicles and their electric-equivalent models have been simulated and their performances have been compared. Six scenarios have been simulated to study the effects of factors such as orography, traffic congestion and driving style. The European fuel consumption and emissions test and Artemis urban driving cycles, representative of European driving cycles, have also been included in the comparative analysis. The results show that road grade has a major impact on fuel economy, although it affects consumption in different levels depending on the technology analysed. Electric vehicles are less affected by this factor as opposed to conventional vehicles, increasing the potential energy savings in a hypothetical electrification of the car fleet. However, electric vehicle range in mountainous terrains is lower compared to that estimated by manufacturers, a fact that could adversely affect a massive adoption of electric cars in the short term.     

Heteroscedastic Gaussian processes for uncertainty modeling in large-scale crowdsourced traffic data

Accurately modeling traffic speeds is a fundamental part of efficient intelligent transportation systems. Nowadays, with the widespread deployment of GPS-enabled devices, it has become possible to crowdsource the collection of speed information to road users (e.g. through mobile applications or dedicated in-vehicle devices). Despite its rather wide spatial coverage, crowdsourced speed data also brings very important challenges, such as the highly variable measurement noise in the data due to a variety of driving behaviors and sample sizes. When not properly accounted for, this noise can severely compromise any application that relies on accurate traffic data. In this article, we propose the use of heteroscedastic Gaussian processes (HGP) to model the time-varying uncertainty in large-scale crowdsourced traffic data. Furthermore, we develop a HGP conditioned on sample size and traffic regime (SSRC-HGP), which makes use of sample size information (probe vehicles per minute) as well as previous observed speeds, in order to more accurately model the uncertainty in observed speeds. Using 6 months of crowdsourced traffic data from Copenhagen, we empirically show that the proposed heteroscedastic models produce significantly better predictive distributions when compared to current state-of-the-art methods for both speed imputation and short-term forecasting tasks.     

4缸柴油机停缸仿真及试验研究

采用停缸技术对小型4缸柴油机的燃油消耗率和排放进行了仿真和试验研究。利用GT-Power建立模型并模拟了停缸位置对燃油消耗率的影响,结合传热损失等因素确定了试验停缸位置。在断油式停缸和断油断气式停缸模式下进行试验和燃烧分析。试验结果表明:停缸后缸内等容度降低;断油式停缸后燃油消耗率和NOx增大但炭烟减少;断油断气式停缸后部分试验点燃油消耗率降低,但NOx和炭烟排放增加。