【摘要】：車載動(dòng)力電池的荷電狀態(tài)(state of charge,SOC)不僅影響電池的循環(huán)壽命,而且影響整車的安全性。快速而準(zhǔn)確的荷電狀態(tài)估算是電源管理系統(tǒng)的重要組成部分。通過對(duì)實(shí)驗(yàn)數(shù)據(jù)進(jìn)行曲線擬合,分析了荷電狀態(tài)的影響因素。將擴(kuò)展卡爾曼濾波算法(extended kalman filter,EKF)和無跡卡爾曼濾波算法((unscented kalman filter,UKF)應(yīng)用到動(dòng)力電池SOC估算中,針對(duì)機(jī)場(chǎng)電動(dòng)擺渡車特殊的運(yùn)行特點(diǎn),設(shè)計(jì)合理的SOC估算算法,用MATLAB進(jìn)行仿真并分析算法的快速性和準(zhǔn)確性。
[Abstract]:(state of charge,SOC) not only affects the cycle life of the battery, but also affects the safety of the whole vehicle. Fast and accurate state estimation is an important part of power management system. Through curve fitting of experimental data, the influence factors of charged state are analyzed. The extended Kalman filter algorithm (extended kalman filter,EKF) and the unscented Kalman filter algorithm (unscented kalman filter,UKF) are applied to the estimation of power battery SOC. A reasonable SOC estimation algorithm is designed for the special operation characteristics of the airport electric ferry vehicle. MATLAB is used to simulate and analyze the speed and accuracy of the algorithm.
【作者單位】： 中國(guó)民航大學(xué)航空地面特種設(shè)備民航研究基地;中國(guó)民航大學(xué)機(jī)場(chǎng)學(xué)院;
【分類號(hào)】：U469.6;V351.35;TM912
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本文編號(hào)：2343467