增程式电动客车能量管理控制策略研究

发布时间：2018-05-14 03:18

本文选题：增程式电动客车 + 系统建模　；参考：《北京理工大学》2016年硕士论文

【摘要】：增程式电动汽车的出现弥补了纯电动汽车续驶里程短的缺点,其电池容量大、对传统燃料的依赖程度低、动力系统结构简单、脱离了复杂的动力耦合装置,是目前新能源汽车的研究方向,也是传统内燃机汽车向纯电动汽车过渡的最佳车型,研究增程式电动汽车的关键技术对推动新能源汽车的市场化进程具有重要意义。本文以增程式电动城市客车为研究对象,围绕其动力系统参数匹配、系统建模与能量管理控制策略展开了研究,重点讨论了基于动态规划全局算法在能量管理控制策略上的应用。本文主要研究内容和结论如下:首先,基于增程式电动客车的动力系统结构和工作原理,结合整车性能参数指标,提出增程式电动客车动力系统关键部件的参数匹配方法,完成了动力系统关键部件的主要参数匹配。在Matlab/Simulink环境下,采用实验建模为主、理论建模为辅的方法,建立各个子系统的前向仿真模型,并以整车控制器模型为核心对子模型进行整车集成,最终得到增程式电动客车的前向仿真模型,为后续控制策略的仿真验证奠定基础。针对增程式电动客车的运行特点,提出根据不同行驶里程需求和电池荷电状态变化速率划分车辆运行模式,并分析了不同运行模式下能量管理控制策略的控制目标。在传统混合动力汽车CDCS控制策略的基础上,提出了三种基于确定规则的增程式电动客车的能量管理控制策略,基于Simulink/Stateflow混合建模方法建立能量管理控制策略模型。以功率跟随型发动机多点控制为例,应用NSGA-Ⅱ优化算法对APU的启停逻辑及关键参数进行优化分析,有效地避免了车辆行驶过程中发动机的频繁启停,实现良好的燃油经济性和排放性能。基于全局最优理论,结合城市客车的行驶特点,提出了基于动态规划算法的增程式电动客车能量管理控制策略。在Matlab环境下建立增程式电动客车能量后向仿真数学模型,对提出的控制策略进行仿真验证。提出将单个循环的仿真结果直接应用于连续的循环工况中,可以在保证最优控制效果的同时大大减少动态规划算法的计算时间。通过采用纯电动模式加固定SOC下降斜率的增程模式组合的能量管理策略,以满足不同行驶里程需求,同时实现较优的车辆经济性和排放性能。最后,基于动态规划离线优化结果,提取出易于工程实现的控制规则,得到基于动态规划仿真结果的规则型增程式电动客车能量管理控制策略。仿真结果表明,将动态规划全局优化算法应用于增程式电动客车能量管理控制策略的设计开发可以实现全局最优控制,在保证汽车动力性和行驶里程需求的同时实现汽车综合经济性最优。基于硬件在环仿真技术,搭建增程式电动客车的dSPACE硬件在环试验平台,对基于动态规划优化结果的规则型能量管理控制策略进行仿真试验。试验结果表明,所提出的控制策略可以满足实时运算要求,得到与动态规划离线优化得到的最优控制基本一致的控制效果。然后搭建了增程式电动客车动力系统的试验台架,进行了动力辅助系统的转速控制试验,主要包括PID参数的整定和转速阶跃试验。试验结果表明控制效果良好,基本满足APU的转速控制要求,为后续能量管理控制策略的台架验证奠定了研究基础。
[Abstract]:The appearance of the added electric vehicle has made up for the shortcoming of the short driving range of the pure electric vehicle. Its battery capacity is large, the dependence on the traditional fuel is low, the structure of the power system is simple, and the complex power coupling device is separated. It is the research direction of the new energy vehicle at present. It is also the best vehicle for the transmission of the internal combustion engine to the pure electric vehicle. The key technology of developing an electric vehicle is of great significance to the promotion of the market process of new energy vehicles. This paper takes an electric city bus as the research object, and focuses on the dynamic programming global algorithm based on the dynamic programming global algorithm, focusing on its dynamic system parameters matching, system modeling and energy management control strategy. The main contents and conclusions of this paper are as follows: firstly, based on the structure and working principle of the power system of the electric passenger car, combined with the performance parameters of the vehicle, the parameter matching method for the key components of the power system of the electric bus is put forward, and the main parameters of the key components of the power system are completed. In the Matlab/Simulink environment, the forward simulation model of each subsystem is established by the method of experimental modeling and theoretical modeling, and the whole vehicle is integrated with the whole vehicle controller model as the core. Finally, the forward imitation true model of the electric bus is obtained, which lays the foundation for the simulation verification of the follow-up control strategy. In view of the running characteristics of an electric passenger car, the vehicle operation mode is divided according to the different running mileage demand and the change rate of the battery charge state, and the control target of the energy management control strategy under different operating modes is analyzed. On the basis of the traditional hybrid electric vehicle CDCS control strategy, three kinds of determination are put forward. The energy management control strategy of electric bus is added regularly, and the energy management control strategy model is set up based on the Simulink/Stateflow hybrid modeling method. Taking the multi point control of the power following engine as an example, the NSGA- II optimization algorithm is used to optimize and analyze the starting and stopping logic and key parameters of the APU, which effectively avoids the vehicle passing through. On the basis of the global optimal theory, based on the global optimal theory and the driving characteristics of the city bus, the energy management and control strategy of an increasing program electric bus based on dynamic programming algorithm is proposed based on the global optimal theory. In the Matlab environment, a mathematical model of the energy backward simulation of an extended electric bus is set up. The proposed control strategy is simulated. It is proposed to apply the simulation results of a single loop directly to the continuous cycle condition, which can greatly reduce the calculation time of the dynamic programming algorithm while ensuring the optimal control effect. In order to meet the different mileage requirements and achieve better vehicle economy and emission performance. Finally, based on the off-line optimization results of dynamic programming, the control rules that are easy to be realized are extracted and the energy management control strategy of a regular model electric passenger car based on the dynamic programming simulation results is obtained. The global optimization algorithm is applied to the design and development of the energy management and control strategy of the electric passenger car, which can realize the global optimal control and realize the optimal comprehensive economic performance at the same time. Based on the hardware in loop simulation technology, the dSPACE hardware of the Da Jianzeng electric bus is flat in the loop test. The experimental results show that the proposed control strategy can meet the real-time operation requirements and get the same control effect that is basically consistent with the optimal control obtained by the dynamic programming off-line optimization. Then, the dynamic system of an electric passenger car is built. The test bench has carried out the speed control test of the power auxiliary system, mainly including the tuning of the PID parameters and the speed step test. The test results show that the control effect is good and basically meets the requirements of the speed control of the APU. It lays a foundation for the study of the follow-up energy management control strategy.

【学位授予单位】：北京理工大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：U469.72

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