Online Estimation of Peak Power Capability of Li-Ion Batteries in Electric Vehicles by a Hardware-in-Loop Approach
发表时间:2021-01-01     阅读次数:     字体:【


摘要:

Battery peak power capability estimations play an important theoretical role for the proper use of the battery in electric vehicles. To address the failures in relaxation effects and real-time ability performance, neglecting the battery's design limits and other issues of the traditional peak power capability calculation methods, a new approach based on the dynamic electrochemical-polarization (EP) battery model, taking into consideration constraints of current, voltage, state of charge (SoC) and power is proposed. A hardware-in-the-loop (HIL) system is built for validating the online model-based peak power capability estimation approach of batteries used in hybrid electric vehicles (HEVs) and a HIL test based on the Federal Urban Driving Schedules (FUDS) is used to verify and evaluate its real-time computation performance, reliability and robustness. The results show the proposed approach gives a more accurate estimate compared with the hybrid pulse power characterization (HPPC) method, avoiding over-charging or over-discharging and providing a powerful guarantee for the optimization of HEVs power systems. Furthermore, the HIL test provides valuable data and critical guidance to evaluate the accuracy of the developed battery algorithms.


部分图片:

图1 The test bench for HIL experiment.

图2 Peak power capability and current online estimation results: (a) Peak discharge currents; (b) Peak charge currents; (c) Peak discharge powers; (d) Peak charge powers.

引文信息

XIONG R, HE H, SUN F, et al. Online Estimation of Peak Power Capability of Li-Ion Batteries in Electric Vehicles by a Hardware-in-Loop Approach[J]. Energies, MDPI AG, 2012, 5(5): 1455–1469.(下载链接

其他相关论文

1. Rui Xiong,Fengchun Sun,Hongwen He,Trong Duy Nguyen. A data-driven adaptive state of charge and power capability joint estimator of lithium-ion polymer battery used in electric vehicles[J]. Energy,2013,63.(下载链接

2. Sun F , Xiong R , He H . Estimation of state-of-charge and state-of-power capability of lithium-ion battery considering varying health conditions[J]. Journal of Power Sources, 2014, 259(aug.1):166-176. (下载链接)



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