A comparative study on the applicability of ultracapacitor models for electric vehicles under different temperatures
发表时间:2021-01-21     阅读次数:     字体:【


摘要

This paper presents a systematic evaluation for five typical equivalent circuit models (ECMs) of ultracapacitors (UCs) under different ambient temperatures. A comprehensive experimental profile is designed to obtain the test datasets. The genetic algorithm (GA) is employed to identify the model parameters for five UC models under different temperatures and state of charge (SOCs). Three results can be obtained from the systematic analysis. (1) Due to the better model accuracy and robustness, the Thevenin model is preferred for UC cell modeling with the maximum errors less than 8 mV. (2) Compared with the other four UC models, the Thevenin model with one-state hysteresis (Thevenin-hys model) is preferred for UC pack modeling because of its better performance. (3) From the point of view of model accuracy and robustness against different ambient temperatures, if the SOC is less than 0.5, the UCs are not suitable for further application.


部分图片:

图1 Configuration of the experimental rig.

图2 Errors of the five UC models by using the UDDS data at 10 ℃.

引文信息

Wang C, He H, Zhang Y, et al. A comparative study on the applicability of ultracapacitor models for electric vehicles under different temperatures[J]. Applied Energy, 2017, 196: 268-278.(下载链接)

其他相关论文

1. R. Xiong, H. Chen, C .Wang and F. Sun, “Towards a smarter hybrid energy storage system based on battery and ultracapacitor - a critical review on topology and energy management”, Journal of Cleaner Production, vol. 202, pp. 1228-1240, Nov 2018.(下载链接


上一篇:Design and simulation studies of battery-supercapacitor hybrid energy storage system for improved performances of traction system of solar vehicle
下一篇:Wavelet transform based energy management strategies for plug-in hybrid electric vehicles considering temperature uncertainty.
0
联系地址:北京市海淀区中关村南大街5号北京理工大学   Copyright  ©  2020-   先进储能科学与应用课题组  All Rights Reserved.网站地图
友情链接: 新能源与智能载运期刊    北京理工大学    ICEIV2022会议    机械与车辆学院    机械工程学报    Applied Energy期刊