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合肥市纯电动公交车工况及能量控制策略研究

Research on Driving Cycle and Energy Control Strategy for Pure Electric Buses in Hefei

【作者】 唐邦强

【导师】 尹志宏;

【作者基本信息】 昆明理工大学 , 车辆工程, 2011, 硕士

【摘要】 内燃机汽车的大规模使用带来了不可再生能源的过度消耗、环境的巨大污染和交通拥堵,解决的方法是研制开发新能源汽车和提倡使用绿色公共交通。我国相关部委已出台政策鼓励优先发展新能源公共交通事业,各个企业也掀起了研制纯电动公交车的热潮并且取得了良好的成果。目前纯电动公交车能量存储系统控制策略存在两个问题:一是控制策略的制定是建立在标准工况基础上的,国内外研究表明,纯电动公交车实际行驶工况和国家标准工况有较大差异,因此有必要建立一套适合纯电动公交车的工况。二是传统的逻辑门限控制策略存在动作频繁、稳定性差的状况,为改善控制效果需要对传统的逻辑门限控制策略进行优化或建立新的控制策略。为解决这两个问题,本文依托国家863资助项目“合肥市环境和工况差异与新能源汽车适配技术研究”展开以下研究:1、合肥市纯电动公交工况研究。依据合肥市纯电动汽车示范工程采集到的数据,经过统计分析后得出车辆运行规律,运用主成分和聚类分析法提炼出三个典型工况模块,合成了合肥市纯电动公交工况(HF-PEB-DC)循环。循环符合纯电动公交车实际运行情况,对中等规模城市具有参考价值,同时也为工况的自识别和控制策略的制定奠定了基础。2、工况自识别系统研究。建立工况之后,采用模糊控制原理设计了工况自识别系统,以行驶阶段的驻车时间比例、平均速度和加速度作为模糊控制器的输入,合肥市纯电动公交工况典型模块参数为输出。给出了系统的模糊控制策略,制定了各个语言变量的赋值表和模糊状态表,用Simulink搭建了仿真模型,仿真结果显示原来随机的、不确定的工况已转化为符合典型工况模块特征的工况,说明设计的工况自识别系统是可行的。识别后的工况参数作为能量存储系统新的逻辑门限控制策略的门限值。3、混合能量存储系统控制策略研究。常见的控制策略有传统的逻辑门限、模糊逻辑和动态规划法,在比较它们的优劣之后,本文提出以平均速度约束加超级电容器荷电状态(SOC)约束为门限的新的逻辑门限控制策略,这种控制策略具有多个优点。然而它也存在优化的空间,本文提出了一种基于古典变分法求解车辆能量存储系统能量损耗率最低的最优控制思路,为混合能量储存系统的后期优化提供了一个研究的方向。4、Simulink仿真表明,新的逻辑门限控制策略是合理的,混合能量存储系统能合理的分配功率,蓄电池组提供的功率大幅下降,峰值功率由超级电容器提供,再生制动能量也大部分由超级电容器吸收,系统达到了设计目标,能够改善纯电动公交车的性能。

【Abstract】 The extensive use of internal combustion engine vehicle brought several problems, such as excessive consumption of non-renewable energy, huge environment pollution and traffic congestion. The solutions are to develop new energy vehicles and advocate use green public transport. The related ministries have already issued policies which encourage the development of new energy public transportation.The policies are supported by each enterprise and achieved good results in our country.At present, the control strategy of pure electric bus energy storage system has two problems: First, the formulation of control strategy is built on the basis of the standard driving cycle, but domestic and international research shows that national standards and the actual driving cycle are quite different, especially the pure electric bus driving cycle. There are cannot serve as the main basis for strategy formulation. Therefore, it is necessary to establish a set of pure electric bus driving cycle. Second, the traditional logic threshold control strategy exist some questions, such as frequent moves, poor stability condition. So we need to optimize and create a new control strategy for improving the control performance of the traditional logic threshold.To address these two problems, the paper relies on country 863 financing projects which "environment and driving cycle differences and new energy technology research in Hefei". We will study the following contents.1. Driving cycle for pure electric bus is to study in Hefei. The data is from pure electric vehicle demonstration project in Hefei. We obtain vehicle running laws through analysis statistical and get three typical driving cycle module by using principal component and clustering analysis awful-sounding. Hefei pure electric buses driving cycle circulation (HF-PEB-DC) synthesized form these analyses. The circulation conform the pure electric bus actual operation situation and provide the reference for medium-sized city. At the same time, it also provides the basis for the foundation of driving cycle identification and control strategy.2. Research on self-recognition system of driving cycle. After established driving cycle for pure electric buses in Hefei, the driving cycle recognition system has designed by fuzzy control theory. The fuzzy controller input use the pause time rate of driving stages and average speed and acceleration. The output use pure electric buses driving cycle typical module parameters in Hefei. We pose system control strategy and make each language variable assignment table and fuzzy status table and using Simulink build a simulation model. The simulation results show that the original random and uncertain condition has been converted to typical driving cycle which accorded with the module features. It is proved that the development of pure electric buses driving cycle since recognition system is feasible. The identification of driving cycle parameters is used as threshold of the new logic threshold control strategy for the energy storage system.3. Study on mixed energy storage system control strategy. Common control strategies contain traditional logic threshold and fuzzy logic and dynamic programming. Through comparison their advantages and disadvantages, the paper proposes an average rate constraint plus super capacitor state of charge (SOC) constraint for the threshold of a new logic threshold control strategy. This control strategy has several advantages. However, it also has the further optimization. This paper presents a variational method based on the classical vehicle energy storage system. The lowest rate of energy loss in the optimal control ideas is for the mixed energy storage system. This provides a post-optimization research.4. Simulation shows that the control strategy formulation is reasonable. The mixture energy storage system by battery and supercapacitor can reasonable allocation of power which provided by battery dropped significantly and the peak power provided by the super-capacitors. Regenerative braking energy is absorbed mostly by super-capacitors. The system meets the design objectives. It can improve the performance of pure electric bus.

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