【作者】 李睿；

【导师】 郑宏宇；

【作者基本信息】 吉林大学 ， 车辆工程， 2021， 硕士

【摘要】 随着经济的快速发展,我国公路货运量以及货物周转量逐年上升,商用车销售量以及保有量逐年增加,公路运输的能源消耗问题逐渐变得不可忽视。因此,针对商用车的节能控制研究具有重要的意义。通过车辆无线通讯技术获取实时行车环境信息进行预测性分析决策,实现对车辆状态的自主调整,将有效提高商用车节能控制策略的适应性与控制效果,对降低车辆能耗具有重要的作用。针对商用车公路运输的行驶特点,本文依托吉林省教育厅科学技术项目“基于线控底盘的分布式电动汽车动力学建模与协同控制”(项目编号:JJKH20200963KJ),对比分析了国内外已有的相关研究现状,对预测性节能控制以及变速器换挡规律的研究进展进行了总结,设计了研究内容。首先基于商用车发动机油耗特性优化变速器换挡规律,提升整车燃油经济性;然后采用稳态与动态控制相结合的方法,开发适用于商用车的预测性节能控制策略;最后通过搭建商用车硬件在环试验台验证所提出控制策略的有效性,主要研究内容总结如下:(1)为研究预测性节能控制策略,首先对车辆传动系统以及制动系统进行纵向动力学建模,基于加速度阈值对车辆模型的行驶状态进行切换。在车辆传动系统模型中,利用车辆发动机油耗特性对变速器换挡规律进行设计优化,改善其燃油经济性;在车辆制动系统模型中,建立电控气压制动系统模型,根据各车轴垂直载荷动态分配制动力,保证制动性能。(2)针对车辆长路径行驶工况,结合道路高度信息,采用模型预测控制对车辆的稳态速度曲线进行规划,作为后续车辆在典型工况局部动态规划的支持条件。其中,为克服车辆行驶状态转移过程中的非线性特征,通过车辆能量变化关系进行线性化处理,计算得到车辆纵向动力学线性模型,同时在控制过程中加入平顺系数,防止车速曲线出现突变而影响车辆舒适性。(3)针对车辆行驶过程中遇到的限速路段、低附着路面以及交通路口等典型工况,将车辆通过智能网联技术提取的典型工况信息作为对车速限制的量化约束条件。在稳态规划结果的基础上,兼顾车辆行驶安全性与舒适性,并基于贝尔曼动态规划算法求解各阶段车速最优解,以获取车辆在典型工况行驶过程中的最优车速曲线,从而在车辆动态行驶过程中达到降低车辆燃油消耗的目的。(4)搭建商用车硬件在环试验台。在Truck Sim软件中嵌入制动系统模型,在MATLAB/Simulink软件中编写预测性节能控制策略,以Lab VIEW RT及Truck Sim RT作为软件支持,以NI-PXI及Micro Auto Box作为硬件控制器,以制动系统盘式制动器与制动阀体作为执行机构,完成对商用车预测性节能控制策略的硬件在环验证工作。更多还原

【Abstract】 With the rapid development of economy,the road freight volume and cargo turnover of our country have increased year by year,so as to the sales and ownership of commercial vehicles.The problem of energy consumption of road transportation gradually becomes not negligible.Therefore,the research on energy-saving control of commercial vehicles is of great significance.Relying on the intelligent and connected vehicle technology,through the vehicle wireless communication technology to obtain real-time driving environment information,carry out predictive analysis and decision-making,realize the independent adjustment of vehicle state,will effectively improve the adaptability and control effect of commercial vehicle energy-saving control strategy,and play an important role in reducing vehicle energy consumption.According to the driving characteristics of commercial vehicles in road transportation,supported by Science and Technology Project of Jilin Provincial Department of Education“Distributed electric vehicle dynamic and collaborative control based on chassis-by-wire system”(Project Number :JJKH20200963KJ),this paper compares and analyzes the existing research status at home and abroad,summarizes the research progress of predictive energysaving control and transmission shift schedule,and designs the research content.Firstly,the gearshift schedule of the transmission is optimized based on the fuel consumption characteristics of the engine of commercial vehicle to improve its fuel economy.Secondly,a predictive energy-saving control strategy suitable for commercial vehicles is developed by combining steady-state control with dynamic control based on intelligent and connected vehicle technology.Finally,the effectiveness of the proposed control algorithm is verified by building a hardware in the loop test bench of commercial vehicles.The main contents of this paper are summarized as follows:(1)In order to establish predictive energy-saving control strategy,the longitudinal dynamics model of vehicle transmission system and braking system is established firstly,and the driving state of vehicle model is switched based on acceleration threshold.In the model of vehicle transmission system,the gearshift schedule of the transmission is optimized by using the fuel consumption characteristics of the vehicle engine to improve its fuel economy;in the vehicle braking system model,the electronically controlled pneumatic braking system model is established to dynamically distribute the braking force according to the vertical load of each axle,so that the braking performance is ensured.(2)Aiming at the long-distance driving condition of vehicles,the road height information is obtained by combining with intelligent and connected vehicle technology,and the steady-state speed curve of vehicles is planned by using model predictive control,which is the support condition of local dynamic planning of subsequent vehicles under typical driving conditions.Among them,in order to overcome the nonlinear characteristics in the process of vehicle driving state transition,the vehicle longitudinal dynamic linear model is calculated by linearization of vehicle energy change relationship.At the same time,the ride coefficient is added in the control process to prevent the sudden change of vehicle speed curve and affect the vehicle comfort.(3)In view of the typical working conditions such as speed limit section,low adhesion road and traffic intersection encountered in the process of vehicle driving,the typical working condition information extracted by the vehicle through intelligent and connected vehicle technology is taken as the quantitative constraint condition of speed limit.Based on the results of steady-state planning,both safety and comfort of vehicle driving are taken into account,and the optimal solution of vehicle speed at each stage is solved based on the Bellman dynamic programming algorithm to obtain the optimal speed curve of the vehicle during typical driving conditions.The target of reducing vehicle fuel consumption is achieved during the dynamic driving of the vehicle.(4)Build commercial vehicle hardware in the loop test bench.The model of braking system is embedded into the software,and the predictive energy-saving control strategy is realized in MATLAB/Simulink,Lab VIEW RT and Truck Sim RT are used as software support to provide driving scenarios,NI-PXI and d SPACE are used as hardware controllers,and the disc brake and brake valve of the braking system are used as actuators,so that the hardware in the loop verification of predictive energy saving control strategy is completed.更多还原