Magic Formula轮胎模型参数辨识的一种混合优化方法

Magic Formula(MF)轮胎模型能够准确描述轮胎的侧偏特性,广泛应用于车辆动力学的研究。由于MF轮胎模型参数多,且高度非线性,从大量的试验数据中准确辨识这些参数相当困难。提出一种基于遗传算法和数值优化算法的混合优化方法,采用由粗到精的辨识过程,先利用遗传算法得出近似最优解,再利用数值优化算法辨识出精确的参数。利用辨识出的参数计算轮胎的侧偏特性,计算结果与试验数据吻合良好,表明该方法是辨识MF轮胎模型参数的有效手段。     

混合动力汽车多途径节能定量研究

文中分析了动力总成的能量消耗特点及功率流关系,提出了混合动力汽车的4条节能途径,并计算城市客车在典型城市工况下的燃油及能量消耗。分别对各节能途径进行了节能贡献的分析,最后总结了各城市工况下最大的总节能潜力。     

混合动力汽车产业发展现状及趋势

混合动力汽车(Hybrid Electric Vehicle, HEV)结合了传统驱动系统和能量存储系统,利用内燃机和电机来驱动车辆,是传统汽车向纯电动汽车过渡的重要桥梁,在如今电动汽车全球大爆发的背景下,混合动力汽车将成为未来节能减排愿景的重要组成部分。文章探讨了近年来混合动力汽车产业的发展状况,介绍了几种新型的混合动力技术,对混合动力汽车的技术优势和不足进行了分析研究,指出了当前混合动力汽车产业面临的一些问题,并对未来混合动力汽车的发展进行了展望。     

混合动力轿车动力总成控制系统的研发

开发了一种并联式HEV的动力总成控制系统,可实现HEV能量管理和状态切换控制。动力总成控制系统在硬件在环测试中进行了功能验证和调试,在实际路面上进行了实车功能和性能试验。实车试验结果表明所研发的动力总成控制策略具有良好的控制品质,能够满足混合动力电动汽车的使用要求。     

Impact of vehicle usage on consumer choice of hybrid electric vehicles

We analyze the vehicle usage and consumer profile attributes extracted from both National Household Travel Survey and Vehicle Quality Survey data to understand the impact of vehicle usage upon consumers’ choices of hybrid electric vehicles in the US. In addition, the key characteristics of hybrid vehicle drivers are identified to determine the market segmentations of hybrid electric vehicles and the critical attributes to include in the choice model. After a compatibility test of two datasets, a pooled choice model combining both data sources illustrates the significant influences of vehicle usage upon consumers’ choices of hybrid electric vehicles. Even though the data-bases have in the past been used independently to study travel behavior and vehicle quality ratings, here we use them together.     

混合动力汽车汽油机电子节气门模糊智能PID控制

应用英飞凌新一代车用嵌入式控制芯片XC164,开发了基于模糊智能积分PID复合控制算法的混合动力汽车汽油机电子节气门控制系统,为混合动力汽车主控制器和发动机控制之间提供了控制接口。通过对混合动力轿车进行的实际行驶中频繁急加速、急减速过程中电子节气门目标开度和实际控制开度的对比试验,验证了电子节气门控制响应速度快、稳态误差小及控制系统软硬件设计满足混合动力总成对发动机控制的要求。     

A system based approach to develop hybrid model predicting extreme urban NOx and PM2.5 concentrations

One of the major drawbacks of conventional air quality models is their inability in accurately predicting extreme air pollutant concentrations. Hybrid modelling is one of the techniques that estimates/predicts the ‘entire range’ of the distribution of pollutant concentrations by combining the deterministic based models (capable in predicting average range) with suitable statistical (probability) distribution models (capable in predicting extreme range). This research paper describes system based approach in developing hybrid model to predict hourly averages as well as extreme percentile ranges of NO_x and PM_2.5 concentrations at two urban locations having complex traffic heterogeneity, highly variable tropical meteorology and different geographical characteristics. At one of the selected locations i.e. Delhi megacity, during winters, hybridization of AERMOD and Lognormal predicts NO_x and PM_2.5 concentrations satisfactorily with index of agreement ‘d’ values of 0.98–0.99, respectively; however, during summers, AERMOD-Log-logistic and AERMOD-Lognormal are best predicting NO_x and PM_2.5 concentrations with d values of 0.98–0.96, respectively. In another, i.e., Chennai, a coastal megacity, AERMOD-Lognormal predicts PM_2.5 concentrations satisfactorily with d values of 0.98 and 0.99 during winter and summer seasons, respectively. Further, hybrid model has also been used to evaluate regulatory compliance.     

A hybrid controller for autonomous vehicles driving on automated highways

This paper addresses the problem of the hybrid control of autonomous vehicles driving on automated highways. Vehicles are autonomous, so they do not communicate with each other nor with the infrastructure. Two problems have to be dealt with: a vehicle driving in a single-lane highway must never collide with its leading vehicle; and a vehicle entering the highway at a designated entry junction must be able to merge from the merging lane to the main lane, again without any collision. To solve these problems, we equip each vehicle with a hybrid controller, consisting of several continuous control laws embedded inside a finite state automaton. The automaton specifies when a given vehicle must enter the highway, merge into the main lane, yield to other vehicles, exit from the highway, and so on. The continuous control laws specify what acceleration the vehicle must have in order to avoid collisions with nearby vehicles. By carefully designing these control laws and the conditions guarding the automaton transitions, we are able to demonstrate three important results. First, we state the initial conditions guaranteeing that a following vehicle never collides with its leading vehicle. Second, we extend this first result to a lane of autonomous vehicles. Third, we prove that if all the vehicles are equipped with our hybrid controller, then no collision can ever occur, and all vehicles either merge successfully or are forced to drop out when they reach the end of their merging lane. Finally, we show the outcome of a highway microsimulation modelled after the Katy Corridor near Houston, Texas: our single-lane highway can accommodate 4000 vehicles per hour with neither drop-outs nor traffic congestion. It is entirely programmed in SHIFT, a hybrid systems simulation language developed at UC Berkeley by the PATH group. This shows that SHIFT is a well suited language for designing safe control laws for autonomous highway systems, among others.     

复合式膜生物反应器处理生活污水的特性研究

复合式膜生物反应器与A/O工艺相结合处理生活污水,使反应器兼具活性污泥法、生物膜法、膜分离3种处理过程,系统出水稳定.膜出水COD平均去除率达85.3%,含量小于50 mg/L;氨氮平均去除率为69.1%,含量20 mg/L以下;总氮平均去除率为50.8%,出水水质符合国家生活杂用水水质标准.