M. Daboussy, D. Chrenko, E. Aglzim, Z. H. Che Daud, L. Le Moyne
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引用次数: 8
Abstract
This paper presents a extented Kalman filter based on a dynamic model of a commercial lithium ion battery pack in automotive applications, and experimental data are collected using the Noao. This vehicle is an electric track with range extender, which has been developed and produced by the association Pôle de Performance de Nevers Magny-Cours (PPNMC). This model has been developed with MATLAB/Simulink to investigate the output characteristics of lithium-ion batteries. It incorporates I-V performance of the battery, battery capacity fading, temperature effect on battery performance, and the battery temperature rise. This estimation technique is used in order to estimate some parameters, which cannot be measured directly by physical sensors such as SOC and SOH and to compensate for uncertainties in the model parameters and the measurements. The proposed model is validated by comparing simulation results with experimental data collected through battery testbed of Noao vehicle.
本文提出了一种基于商用锂离子电池组动态模型的扩展卡尔曼滤波，并利用Noao进行了实验数据采集。这辆车是一辆带增程器的电动履带，由Pôle de Performance de Nevers Magny-Cours (PPNMC)协会开发和生产。利用MATLAB/Simulink开发了该模型，研究了锂离子电池的输出特性。包括电池的I-V性能、电池容量衰减、温度对电池性能的影响、电池温升。该估计技术用于估计一些物理传感器(如SOC和SOH)无法直接测量的参数，并补偿模型参数和测量结果中的不确定性。通过将仿真结果与诺奥汽车电池试验台采集的实验数据进行对比，验证了所提模型的有效性。
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