A Shifting Strategy for Electric Commercial Vehicles Considering Mass and Gradient Estimation

The extended Kalman filter (EKF) algorithm and acceleration sensor measurements were used to identify vehiclemass and road gradient in the work. Four different states of fixed mass, variable mass, fixed slope and variableslope were set to simulate real-time working conditions, respectively. A comprehensive electric commercial vehicleshifting strategy was formulated according to the identification results. The co-simulation results showed that,compared with the recursive least square (RLS) algorithm, the proposed algorithm could identify the real-timevehicle mass and road gradient quickly and accurately. The comprehensive shifting strategy formulated had thefollowing advantages, e.g., avoiding frequent shifting of vehicles up the hill, making full use ofmotor braking downthe hill, and improving the overall performance of vehicles.

Shifting Rule Modification Strategy of Automatic Transmission Based on Driver-vehicle-road Environment

Accidental or frequent shift often occurs when the shifting rule is built based on traditional two parameters （i.e., velocity and throttle）, because the speed of engine varies slower than change of throttle opening. Currently, modifying shift point velocity value or throttle by throttle change rate is one of common methods, but the results are not so satisfactory in some working condition such as uphill. The reason is that these methods merely consider throttle change rate which is not enough for a car driving in driver-vehicle-road environment system. So a novel fuzzy control modification strategy is proposed to avoid or reduce those abnormal shift actions. It can adjust shifting rule by the change rate of throttle, current gear position and road environment information, while different gear position and driving environment get corresponding modification value. In order to compare the results of shifting actions, fuel consumption and braking distance, emergent braking in level road and extra-urban driving cycle（EUDC） working conditions with fuzzy shifting schedule modification strategy are simulated digitally. Furthermore, a hardware-in-the-loop simulation platform is introduced to verify its effect in slope road condition according to the ON/OFF numbers of solenoid valve in hydraulic system. The simulation results show that the problem of unexpected shift in those working conditions may be resolved by fuzzy modification strategy. At last, it is concluded that although there is some slight decline in power performance in uphill situation, this fuzzy modification strategy could correctly identify slope of road, decrease braking distance, improve vehicle comfort and fuel economy effectively and prolong the life of clutch system. So, this fuzzy logic shifting strategy provides important references for vehicle intelligent shifting schedule.

Simulation-based multi-objective optimization for roll shifting strategy in hot strip mill

A simulation-based multi-objective optimization approach for roll shifting strategy in hot strip mills was presented. Firstly, the effect of roll shifting strategy on wear contour was investigated by mtmerical simulation, and two evaluation indexes including edge smoothness and body smoothness of wear contours were introduced. Secondly, the edge smoothness average and body smoothness average of all the strips in a rolling campaign were selected as objective functions, and shifting control parameters as decision variables, the multi-objective method of MODE/D as the optimizer, and then a simulation-based multi-objective optimization model for roll shifting strategy was built. The experimental result shows that MODE/D can obtain a good Pareto-optimal front, which suggests a series of alternative solutions to roll shifting strategy. Moreover, the conflicting relationship between two objectives can also be found, which indicates another advantage of multi-objective optimization. Finally, industrial test confirms the feasibility of the multi-objective approach for roll shifting strategy, and it can improve strip profile and extend same width rolling miles of a rolling campaign from 35 km to 70 km.

Multi-objective optimization for roll shifting strategy in cross rolling campaigns of hot strip mill

A multi-objective optimization approach for the roll shifting strategy in cross rolling campaigns of hot strip mills is presented. The effect of different roll shifting strategies on roll wear contour is studied by numerical simulation, and two evaluation indexes ,namely body smoothness and edge smoothness, are proposed. The average body smoothness and average rolling edge smoothness of all strips in a rolling campaign are taken as the objective functions, the shifting positions of all wide strips as the decision variables, and the multi-objective method of NSGA-II as the optimizer. Thus a multi-objective optimization model for the roll shifting strategy is built. The simulation results show that work roll shifting can make wear contour smooth,and a dish-shaped wear contour without severe local wear can be achieved by the roll shifting strategy with varying stroke. Optimization experimentation shows that by means of NSGA-II,a good Pareto-optimal front can be obtained, which suggests a series of alternative solutions for roll shifting strategy optimization. The experimentation also shows that there is a conflict between the two objectives. Finally, application cases confirm the feasibility of the multi-objective approach, which can improve the strip profile ,reduce edge waves and extend the rolling miles of a rolling campaign.

VEHICLE SIMULATION MODEL FOR DEVELOPING AN INTELLIGENT SLOPE SHIFT STRATEGY

With the rapid development of electronics and the growing demand for highervehicle performance, intelligent shift technology is becoming increasingly important, and itpromises to be a developing trend in vehicle automatic transmissions, A new simulation model ispresented, which includes engine, powertrain, tire and vehicle dynamics models. Based on the model,simulation experiments are conducted to investigate the slope shift strategy. The data andconclusions obtained from the simulations are valuable contributions to the development of anintelligent slope shift strategy.

Shift scheduling strategy development for parallel hybrid construction vehicles

The shift scheduling system of the transmission has an important effect on the dynamic and economic performance of hybrid vehicles. In this work, shift scheduling strategies are developed for parallel hybrid construction vehicles. The effect of power distribution and direction on shift characteristics of the parallel hybrid vehicle with operating loads is evaluated, which must be considered for optimal shift control. A power distribution factor is defined to accurately describe the power distribution and direction in various parallel hybrid systems. This paper proposes a Levenberg-Marquardt algorithm optimized neural network shift scheduling strategy. The methodology contains two objective functions, it is a dynamic combination of a dynamic shift schedule for optimal vehicle acceleration, and an energy-efficient shift schedule for optimal powertrain efficiency. The study is performed on a test bench under typical operating conditions of a wheel loader. The experimental results show that the proposed strategies offer effective and competitive shift performance.

Simulation of automobile fuel consumption and emissions for various driver's manual shifting habits

The effects of different habits of the drivers on gear shifting strategies for manual powertrain were investigated. For the realization of simulation, the shifting habits of the drivers were conducted in the Advisor software to investigate and compare the emission rates. Simulation was developed based on the optimal gear shifting strategy and criteria and was validated both in fuel economy and emissions by analyzing the results in the various driving cycle and driving styles. To explore an optimal gear shifting strategy with best fuel economy and lowest emission for a manual transmission, a strategy was designed with a highest possible gear criterion as long as the torque requirement can be satisfied. Based on two different criteria, namely the engine working conditions and the driver's intention, the governing parameters in decision making for gear shifting of manual transmission in conventional engine were discussed. It is also shown that the optimum gear shifting strategy is based on that both the engine state and the driver's intention eliminates unnecessary shiftings that are present when the intention is overlooked. The optimum shifting habit and the best driving cycle in terms of minimum emissions and fuel consumption were proposed.

基于Cruise的重型商用车性能匹配分析

针对重型商用车动力系统开发周期长、成本高的问题,该文首先参考法规基于MATLAB编写程序生成需要的换挡策略,再通过AVL Cruise对整车性能匹配进行建模和仿真分析,得到油耗、动力性都满足要求的最优动力方案,并与该方案对应的实测值进行对比分析。结果表明,仿真结果与实测结果基本吻合,模型仿真可以代替实测对整车性能提前评估,缩短产品开发周期和成本。

基于数字孪生的动力换挡拖拉机换挡策略研究

发动机性能变化和牵引阻力波动等时变因素对大功率动力换挡拖拉机(PST)换挡策略的适应性具有巨大威胁。为了构建动态精准模型和应对负载波动,以提高PST换挡策略的适应性,提出了一种基于数字孪生的自适应换挡策略。一方面,将发动机状态变化视作内部干扰,基于深度确定性策略梯度(DDPG)算法对虚拟PST发动机进行实时校准,结合PST机理模型,实现对PST的实时动态精准建模。另一方面,将牵引阻力波动视作外部干扰,提出基于深度Q网络(DQN)的换挡策略生成方法。在实时动态精准建模和换挡策略自动生成两个机制的协同作用下,实现换挡策略的自适应调整。最后,开展了犁耕工况下的虚拟PST训练仿真及本文方法与模糊自适应方法的车速跟踪对比试验。结果表明,发动机转矩和燃油消耗率跟踪误差均值不超过7.28 N·m和1.55 g/(kW·h),实现了对物理PST的动态精准建模。在长时间使用之后,发动机和牵引阻力的变化导致模糊自适应方法的换挡点和模糊规则不再完全适用,换挡表现逐渐变差,而本文方法的换挡表现和车速跟踪效果全程良好,其车速跟踪误差均值、燃油消耗率均值和总换挡次数分别为0.0125 m/s、229.76 g/(kW·h)和42,比模糊自适应方法分别减小0.91%、11.14%、34.38%,验证了本文方法的适应性和优越性。

汽车领域人工智能应用探讨

人工智能技术的发展推动着全球各行业的技术革新。目前汽车行业的蓬勃发展离不开人工智能技术的融合应用,主要包括2个方面:在汽车制造中,生产线设备维护、故障检测、智能仓储物流等智能化系统;在车载系统中,智能汽车电子、自动驾驶技术、ADAS车辆行驶状态检测等。基于此,主要对人工智能技术在汽车制造与车载系统中的应用加以分析。研究数据表明,与传统技术的汽车生产相比,融合人工智能技术的汽车生产安全性提高了11.6%,返工率降低了5.0%,故障平均检测时长缩短了15 min。展望了未来人工智能在汽车自动驾驶方面的机遇和以及安全防盗、算力不足的挑战,为推动智能汽车发展提供参考。

基础研究支撑教育、科技、人才“三位一体”发展战略探讨

基础研究是推进教育、科技、人才一体化战略布局的重要抓手和着力点。纵观历史,世界上重要的教育、科技和人才中心的形成都源于基础研究的重大突破及其应用发展。根据科学史中“汤浅现象”的测算原理,世界科学中心、人才中心和高等教育中心基本上是同构的。进入新时代,我国基础研究在推进教育、科技、人才发展的过程中涌现出了新特征和新趋势,面临着新的发展机遇。科学地、有效地认识基础研究发展规律对教育、科技、人才一体战略布局具有重要的现实意义。未来,我国基础研究资助体系的建设,应面向基础研究精细化、体系化,加强战略性基础研究布局;面向科学研究范式的转换期,加强对基础科学及其发展规律的系统认识;面向基础研究的智能化和数字化,优化专家参与和决策机制。

大型水运枢纽船舶闸室连续排挡模型及算法研究

为提高内河通航设施船舶通航效率,提高通航设施工作能力,提出一种可以求解考虑船舶顺序入闸和不考虑船舶顺序入闸两种情况的船舶闸室连续排挡模型和算法。利用二维装箱问题模型建立船舶闸室连续排挡模型,采用贪婪策略思想,提出船舶闸室连续排挡模型求解算法。根据百色枢纽工程生成仿真到闸船舶船型数据,用算法进行闸室排挡计算。结果表明,在随机生成90艘船舶的情况下,考虑船舶到闸顺序的排挡结果需要使用47个闸次,闸次平均占用率为76.424%,不考虑船舶到闸顺序的排挡结果需要使用45个闸次,闸次平均占用率为76.821%,模型和算法能够对不同情况下船舶闸室进行有效连续排挡。

新型插电式混合动力客车换挡控制策略的分析

提出了一种新型插电式混合动力变速器并分析其换挡模式。基于AMESim仿真软件建立新型混合动力变速器模型,分析和制定换挡控制策略,设计测试用例并在MATLAB/Simulink中搭建整车模型。仿真测试结果表明,该新型混合动力装置对换挡冲击的控制效果良好,换挡品质好,可实现动力无中断、平滑换挡,满足控制策略要求。对提升城市新能源客车换挡品质及节能环保等方面具有现实意义。

翻译转换理论下汽车英语的翻译策略

汽车发展日新月异,提高汽车英语翻译技巧对了解汽车行业前沿技术和促进技术交流尤为重要。本文分析了汽车英语词汇和句子的特征,在卡特福德翻译转换理论的指导下,提出了汽车英语的翻译原则,尝试从层次转换和范畴转换两个角度对汽车英语的词汇和句子翻译进行分析,并就如何提高汽车英语翻译技巧提出了建议。

基于VeriStand的硬件在环仿真系统在LF 2204动力换挡拖拉机上的应用

考虑到新的测试软件被开发后,拖拉机实车测试的安全性,有效性和高经济性等多方面因素的影响,提出了一种基于NI-VeriStand的HIL(硬件在环仿真系统)在LF 2204动力换挡拖拉机控制系统上的应用,基于仿真软件SimulationX对动力换挡拖拉机设计整车仿真模型,通过该模型应用HIL仿真系统对动力换挡控制系统策略软件进行全面的功能测试,以确定该控制系统的可靠性、完整性。

适用于直流微网系统的新型双向三端口变换器及其控制策略

在传统分布式新能源并网接口中增加储能装置作为第三端口,可有效改善因分布式新能源强不确定性和随机性等特征引发的输出功率波动问题。为此提出并研究了一种适用于高升降压比直流微网系统的新型非隔离双向三端口变换器及其控制方法。通过集成双有源半桥变换器和非隔离双向Buck/Boost变换器,实现了三个端口中任意两个端口之间功率的双向传输。详细分析了所提新型变换器的工作原理、变换器输出特性以及控制策略,通过移相+脉宽调制控制方法,实现了宽范围的电压调节和各端口间功率的平滑切换。搭建了一台1 kW的试验样机,验证了所提出的新型三端口变换器及其控制方法的可行性和有效性。研究结果对于提高分布式新能源接入稳定性具有理论指导与工程实践借鉴意义。

晋陕蒙地区煤炭运输通道运营对策研究

晋陕蒙地区煤炭运输通道的建设是落实国家“双碳”战略导向、运输结构调整政策,健全煤炭内循环体系的重要组成部分。基于保障国家能源安全战略目标,结合现阶段晋陕蒙地区煤炭生产布局调整及能源安全,分析晋陕蒙地区煤炭运输通道功能分工及运输通道症结,根据晋陕蒙地区煤炭产销结构与趋势分析及煤炭运输通道外运量预测,提出晋陕蒙地区铁路煤炭运输通道格局调整优化方案,从煤运通道需求、运输企业运营2个方面,提出打通运输市场隐形“瓶颈”,合理分流公路运量,降低铁路运营成本,提高铁路运输效率,优化铁路运输结构等运营对策。

纯电动汽车模糊控制经济性换挡策略研究

针对某纯电动汽车在传统换挡策略下产生的频繁换挡问题,在AMT传统换挡控制策略研究的基础上,使用模糊控制以加速踏板开度和加速踏板开度变化率对驾驶员意图进行识别,然后结合驾驶员意图以及车速制定换挡策略。建立传统换挡策略和模糊控制驾驶员意图识别换挡策略的AMT换挡仿真模型。通过仿真结果的对比,验证模糊控制驾驶员意图识别的换挡策略的有效性。结果表明:对比传统换挡策略,模糊控制驾驶意图识别的换挡策略减少了换挡次数,经济性略有提升。

驱动系统效率最优的并联混合动力商用车模式切换及换挡控制策略

为提高搭载自动变速器的并联混合动力商用车燃油经济性,以驱动系统效率最优为目标,提出一种新的驱动模式边界划分和挡位边界划分方法。制定了基于效率最优的模式切换及换挡控制策略,并在中国重型商用车行驶工况下对所制定的控制策略进行了仿真验证。结果表明,所提出的策略不仅能够维持电池荷电状态的平衡,且百公里油耗比电辅助控制策略低11.2%,具有更好的燃油经济性。

基于工况识别的纯电动汽车2DCT换挡策略研究

为使纯电动汽车具有更好的经济性,同时保持较好的动力性,针对自主研发的纯电动汽车两挡干式双离合变速器(2DCT),提出一种基于工况识别的实时换挡策略。通过径向基神经网络预测车速,利用动态规划提取7种循环工况的最优换挡点,并搭建基于相似度比对的工况识别模型,对车辆行驶工况进行识别,实现实时换挡。基于MATLAB/Simulink进行仿真并完成2DCT台架实验。结果表明,提出的基于工况识别的实时换挡策略能同时兼顾车辆的经济性和换挡频率。