基于品质工学的电动汽车再生制动系统优化研究

发布时间：2018-03-06 21:32

本文选题：纯电动汽车　切入点：再生制动　出处：《重庆交通大学》2016年硕士论文　论文类型：学位论文

【摘要】：纯电动汽车以其零排放、低噪音、不受石油匮乏影响等优点日益受到全世界的广泛关注,纯电动汽车相关技术的研发也受到各大汽车公司、研究机构的高度重视。然而与传统内燃机汽车相比,纯电动汽车的续驶里程普遍受到电池容量的限制,无法完全满足人们长距离的出行需求。得益于电机的发电特性,制动工况下,电动汽车可进行再生制动,将部分制动能量以电能的形式回收储存,有效地提高整车能量使用率,延长续驶里程。制动力分配策略作为再生制动系统的重要组成部分,直接影响制动能量回收率的高低。模糊概念符合人类思维方式,基于模糊控制理论设计制动力分配策略可有效地实现对制动系统的控制。品质工学认为产品的品质是靠设计出来的,通过稳健性设计能够得到品质高、稳健性优异的产品。以再生制动模糊控制系统为开发对象,以提高能量回收率为试验目的,对模糊控制系统进行稳健性设计,以实现能量回收率的进一步提升。(1)基于制动相关法规和动力学模型,分析了再生制动影响因素,探讨了三种典型再生制动策略的优劣性。分析表明,再生制动控制策略设计过程中需要考虑电机性能、电池荷电状态、路况以及制动强度的影响。(2)基于模糊控制理论,设计再生制动模糊控制系统。选择车速、电池荷电状态、制动强度为输入变量,以再生制动力占比为控制目标,在保证制动稳定性、保护电池的前提下,制定了模糊控制规则,并基于MATLAB模糊工具箱搭建了相应模型。(3)基于仿真软件ADVISOR,检验模糊控制系统效果。对ADVISOR软件进行二次开发,基于MATLAB/Simulink软件搭建再生制动模糊控制系统,选择日本1015工况、美国UDDS工况、美国纽约城市NYCC工况进行仿真实验。试验结果显示再生制动模糊控制系统可有效地回收制动能量。(4)基于品质工学,优化模糊控制模型。以模糊控制隶属度函数形状因子为优化对象,对再生制动模糊控制系统进行性能改进。仿真试验结果显示,通过对隶属度函数形状的调整,三种工况下能量回收率取得了一定程度的提高,即控制系统的品质和稳定性都取得了提高。在国家倡导推行“绿色出行、低碳生活”的背景下,适应电动汽车延长续驶里程的实际需求,在考虑制动稳定性的前提下,建立了再生制动模糊控制模型,并通过品质工学对模糊控制模型进行了优化改进,提出了性能稳定、能量回收率高的再生制动控制系统,为模糊控制与品质工学相结合的研究方式提供一定参考。
[Abstract]:Pure electric vehicles, with their advantages of zero emission, low noise, no oil shortage and so on, have attracted more and more attention all over the world. The research and development of pure electric vehicles related technologies have also been received by major automobile companies. However, compared with the traditional internal-combustion engine vehicles, the driving range of pure electric vehicles is generally limited by battery capacity, which can not fully meet the long distance travel needs of people. Under braking condition, the electric vehicle can be regenerated and stored in the form of electric energy, which can effectively improve the energy utilization rate of the whole vehicle. As an important part of regenerative braking system, braking force distribution strategy has a direct influence on braking energy recovery. The braking force distribution strategy based on fuzzy control theory can effectively control the braking system. Quality engineering believes that the quality of the product depends on the design, and high quality can be obtained through robust design. Taking regenerative braking fuzzy control system as the development object and improving the energy recovery rate as the experimental purpose, the robust design of the fuzzy control system is carried out. In order to realize the further improvement of energy recovery, based on the relevant regulations and dynamic models of braking, the influencing factors of regenerative braking are analyzed, and the advantages and disadvantages of three typical regenerative braking strategies are discussed. In the design of regenerative braking control strategy, the performance of motor, the charge state of battery, the influence of road condition and braking intensity should be considered. Based on fuzzy control theory, the fuzzy control system of regenerative braking should be designed. The braking strength is the input variable and the proportion of regenerative braking force is taken as the control target. On the premise of ensuring the braking stability and protecting the battery, the fuzzy control rules are formulated. The corresponding model is built based on MATLAB fuzzy toolbox. (3) based on the simulation software ADVISOR. the effect of fuzzy control system is tested. The secondary development of ADVISOR software is carried out, and the regenerative braking fuzzy control system is built based on MATLAB/Simulink software, and Japan 1015 working condition is selected. The simulation results show that the regenerative braking fuzzy control system can effectively recover the braking energy based on quality engineering. The fuzzy control model is optimized. Taking the shape factor of membership function of fuzzy control as the optimization object, the performance of regenerative braking fuzzy control system is improved. The simulation results show that, by adjusting the shape of membership function, The energy recovery rate has been improved to a certain extent under the three conditions, namely, the quality and stability of the control system have been improved. The fuzzy control model of regenerative braking is established under the premise of considering the braking stability to meet the actual demand of prolonging the driving range of electric vehicles. The fuzzy control model is optimized and improved by quality engineering, and the stability of performance is proposed. The regenerative braking control system with high energy recovery rate provides a certain reference for the research of the combination of fuzzy control and quality engineering.
【学位授予单位】：重庆交通大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：U469.72

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