基于试验的自动变速器故障诊断分析

通过现有的失速试验、时滞试验、油压试验、道路试验、故障码扫描等多种试验方法，可在变速器解体之前获得故障信息。在深入分析自动变速器结构及各元件功能的基础上，将各种试验进行合理的逻辑组合，对获得的故障信息进行逻辑分析，最终可将故障源限定在最小的范围之内。分析探讨了这种方法的可行性。     

自动变速器故障的功能分析法

功能分析法，即是通过对变速器各部分结构元件工作原理的分析，了解它们在整个系统中的作用，在此基础上分析得出各结构元件失效将产生的后果，并将故障现象与可能的故障源建立一一对应的联系，最后总结归纳出故障源群组的方法。它能较全面地概括出自动变速器可能产生的各类故障，为准确诊断自动变速器故障创造了有利条件。     

现代轿车自动变速器技术分析

自动变速器作为现代汽车传动系统中一个十分重要的总成，对车辆诸多性能的提高起着重要的作用。世界轿车自动变速器技术的发展无疑反映了当今该项技术的潮流，自动变速器技术正朝着结构多挡化、性能高效化、换挡智能化和舒适化等方向发展。     

汽车离合器从动盘扭转耐久试验中弹簧疲劳断裂的自动识别

对汽车离合器从动盘扭转耐久试验中弹簧断裂的自动识别技术进行研究，提出一种以弹簧刚度特性变化为识别特征的识别原理，进行了相关的分析计算；介绍了基于此原理的自动识别方案及测试过程，并给出实际运行结果。此技术提高了测试智能化水平。     

AMT换挡品质的研究

电控机械式自动变速器（AMT）具有传动效率高、结构紧凑及工作可靠等优点。介绍了AMT换挡品质的定义及其影响因素，分析了几种影响因素之间的内在关系，并在此理论基础上寻求一种可获得最佳AMT换挡品质的方法。AMT按照其对发动机控制方式的不同，可分为柔性控制和刚性控制结构。     

人工智能在车辆自动驾驶中的应用

提出一种新的基于人工智能的感知 计划 动作agent结构实现智能车辆自动驾驶的方案。首先通过描述该结构的原理说明该结构可以解决自动驾驶中存在的一些问题,接着通过建立自动驾驶知识库阐述如何具体实现自动驾驶,最后通过仿真实验验证该方法能够为智能车辆实现自动或辅助驾驶提供一种非常有效的机制。     

双离合器式自动变速器换挡特性研究

介绍了双离合式自动变速器工作原理，建立了换挡过程的数学模型，并对升、降挡的换挡特性进行了仿真与试验分析，为DCT的开发设计提供了参考依据。     

间歇式沥青拌和站冷料供给系统流量的标定方法

以实例介绍间歇式沥青拌和冷料供给系统流量的标定方法和步骤，以确保冷料供给器按目标配合比准确供料，使沥青混合料的生产配比更加接近目标配比，保证拌和成品料的质量。     

Validation of an extended discrete first-order model with variable speed limits

This paper validates the prediction model embedded in a model predictive controller (MPC) of variable speed limits (VSLs). The MPC controller was designed based on an extended discrete first-order model with a triangular fundamental diagram. In our previous work, the extended discrete first-order model was designed to reproduce the capacity drop and the propagation of jam waves, and it was validated with reasonable accuracy without the presence of VSLs. As VSLs influence traffic dynamics, the dynamics including VSLs needs to be validated, before it can be applied as a prediction model in MPC. For conceptual illustrations, we use two synthetic examples to show how the model reproduces the key mechanisms of VSLs that are applied by existing VSL control approaches. Furthermore, the model is calibrated by use of real traffic data from Dutch freeway A12, where the field test of a speed limit control algorithm (SPECIALIST) was conducted. In the calibration, the original model is extended by using a quadrangular fundamental diagram which keeps the linear feature of the model and represents traffic states at the under-critical branch more accurately. The resulting model is validated using various traffic data sets. The accuracy of the model is compared with a second-order traffic flow model. The performance of two models is comparable: both models reproduce accurate results matching with real data. Flow errors of the calibration and validation are around 10%. The extended discrete first-order model-based MPC controller has been demonstrated to resolve freeway jam waves efficiently by synthetic cases. It has a higher computation speed comparing to the second-order model-based MPC.     

A methodology for evaluating the performance of model-based traffic prediction systems

Model-based traffic prediction systems (mbTPS) are a central component of the decision support and ICM (integrated corridor management) systems currently used in several large urban traffic management centers. These models are intended to generate real-time predictions of the system’s response to candidate operational interventions. They must therefore be kept calibrated and trustworthy. The methodologies currently available for tracking the validity of a mbTPS have been adapted from approaches originally designed for off-line operational planning models. These approaches are insensitive to the complexity of the network and to the amount and quality of the data available. They also require significant human intervention and are therefore not suitable for real-time monitoring. This paper outlines a set of criteria for designing tests that are appropriate for the mbTPS task. It also proposes a test that meets the criteria. The test compares the predictions of the mbTPS in question to those of a model-less alternative. A t-test is used to determine whether the predictions of the mbTPS are superior to those of the model-less predictor. The approach is applied to two different systems using data from the I-210 freeway in Southern California.