电动汽车磷酸铁锂电池建模及荷电状态估计研究-机械工程专业论文.docxVIP

II II 电倍率等对电池 SOC 估计的影响及影响因子的强弱。针对经典电池荷电状态估计 算法存在的不足，利用建立的 RC 修正模型，提出了基于扩展 Kalman 滤波的电池 荷电状态估计方法，并对递推方程的初始值进行了讨论和分析。与传统方法相比 较，提出的方法具有良好的动态性能、对初值误差不敏感、以及具有很好的抑制 测量噪声等特性。 5、为了验证建立的模型的准确性以及提出的电池荷电状态估计的有效性，在 此，搭建了电池的实验测试平台，包括电池硬件实验平台和电池测试软件。利用 Simunlink 模块对电池的 RC 修正模型进行了仿真。实验结果表明，在恒流放电、 HPPC循环和 UDDS三种不同工况下，测得的最大误差与平均误差非常小，误差最 大值不超过 0.1385V ，平均误差值不超过 0.0197V ，相对的最大误差值不超过 4.2%， 提出的 RC 修正模型具有很高的估算精度。 同时，在该实验测试平台上，对提出的基于 RC 修正模型的 EKF 的荷电状态 估计方法也进行了 实验验证。实验结果表明，在恒流放电、恒流脉冲放电、 CYC_UDDS 及 CYC_1051_prius 四种不同工况下，得到的 平均误差 都 不超过 2 . 8 7 %，最大误差也不超过 4.89% ，因此，提出的荷电状态估计方法具有较高的精 度和良好的抗干扰能力。 关键词：电动汽车；磷酸铁锂电池；电池模型；荷电状态估计 III III Abstract Under the National Natural Science Foundation of China 51261024)and the Jiangxi Provincial Science and Technology Program funded projects (No.20141BBE50021) and battery manufacturers (Original Energy Technology), according to the dynamic characteristics of lithium iron phosphate in different working conditions, the paper establish RC correction model that has a specific relationship of the batterys internal state and external characteristics, study in-depth the extended Kalman filter algorithm based on RC modified model, use algorithm to estimate the state of charge for lithium iron phosphate, this algorithm based on RC modified model has better applicability, provided help for the design of the battery management system, the research mainly include the following contents: Discusses background and significance of the research. The status of domestic research about the battery model and state of charge to estimate are summarized. The structure, working principle and advantages of lithium iron phosphate battery was introduced in detail, manufacturing process of lithium iron phosphate battery are given. Based on this, puts forward the main contents and the main innovation points of this paper. On the analysis of the lithium iron phosphate battery performance under different working conditions, including the basic characteristic of the battery, ele