Neng Xiong

Mr. Neng Xiong

orcid

Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 July 2019 in Energy
Verified
Journal Article
Closed access
Feng GuoFeng Guo
Feng Guo
GHGuangdi Hu
Guangdi Hu
SXShun Xiang
Shun Xiang
PZPengkai Zhou
Pengkai Zhou
RHRu Hong
Ru Hong
NXNeng Xiong
Neng Xiong

12 May 2017 in Energies
Verified
Journal Article
Open access
PDF file
QZQiao Zhu
Qiao Zhu
NXNeng Xiong
Neng Xiong
Mingliang YangMingliang Yang
Mingliang Yang
RHRuisen HUANG
Ruisen HUANG
GHGuangdi Hu
Guangdi Hu
This work is focused on the state of charge (SOC) estimation of a lithium-ion battery based on a nonlinear observer. First, the second-order resistor-capacitor (RC) model of the battery pack is introduced by utilizing the physical behavior of the battery. Then, for the nonlinear function of the RC model, a one-sided Lipschitz condition is proposed to ensure that the nonlinear function can play a positive role in the observer design. After that, a nonlinear observer design criterion is presented based on the H ∞ method, which is formulated as linear matrix inequalities (LMIs). Compared with existing nonlinear observer-based SOC estimation methods, the proposed observer design criterion does not depend on any estimates of the unknown variables. Consequently, the convergence of the proposed nonlinear observer is guaranteed for any operating conditions. Finally, both the static and dynamic experimental cases are given to show the efficiency of the proposed nonlinear observer by comparing with the classic extended Kalman filter (EKF).

1 September 2017 in Energies
Verified
Journal Article
Open access
PDF file
YCYixing Chen
Yixing Chen
DHDeqing Huang
Deqing Huang
QZQiao Zhu
Qiao Zhu
Weiqun LiuWeiqun Liu
Weiqun Liu
CLCongzhi Liu
Congzhi Liu
NXNeng Xiong
Neng Xiong
An accurate state of charge (SOC) estimation is the basis of the Battery Management System (BMS). In this paper, a new estimation method which considers fractional calculus is proposed to estimate the lithium battery state of charge. Firstly, a modified second-order RC model based on fractional calculus theory is developed to model the lithium battery characteristics. After that, a pulse characterization test is implemented to obtain the battery terminal voltage and current, in which the parameter identification is completed based on least square method. Furthermore, the proposed method based on Fractional Unscented Kalman Filter (FUKF) algorithm is applied to estimate the battery state of charge value in both static and dynamic battery discharging experiment. The experimental results have demonstrated that the proposed method shows high accuracy and efficiency for state of charge estimation and the fractional calculus contributes to the battery state of charge estimation.

5 August 2021 in Energies
Verified
Journal Article
Open access
PDF file
ZZZhongwei Zhang
Zhongwei Zhang
DZDan Zhou
Dan Zhou
NXNeng Xiong
Neng Xiong
QZQiao Zhu
Qiao Zhu
This paper deals with the state of charge (SOC) estimation of lithium-ion battery (LIB) in electric vehicles (EVs). In order to accurately describe the dynamic behavior of the battery, a fractional 2nd-order RC model of the battery pack is established. The factional-order battery state equations are characterized by the continuous frequency distributed model. Then, in order to ensure the effective function of nonlinear function, Lipschitz condition and unilateral Lipschitz condition are proposed to solve the problem of nonlinear output equation in the process of observer design. Next, the linear matrix (LMIS) inequality based on Lyapunov’s stability theory and H∞ method is presented as a description of the design criteria for non-fragile observer. Compared with the existing literature that adopts observers, the proposed method takes the advantages of fractional-order systems in modeling accuracy, the robustness of H∞ method in restricting the unknown variables, and the non-fragile property for tolerating slow drifts on observer gain. Finally, The LiCoO2 LIB module is utilized to verify the effectiveness of the proposed observer method in different operation conditions. Experimental results show that the maximum estimation accuracy of the proposed non-fragile observer under three different dynamic conditions is less than 2%.

10 May 2018 in Modern Physics Letters B
Verified
Journal Article
Closed access
ZZZhao Zhang
Zhao Zhang
TYTao Yang
Tao Yang
NXNeng Xiong
Neng Xiong
FQFengxue Qian
Fengxue Qian

9 November 2021
Verified
Book Chapter
Closed access
PDF file
YWYu Wenze
Yu Wenze
LQLiang Quan
Liang Quan
ZZZhang Zicheng
Zhang Zicheng
HJHu Jinjing
Hu Jinjing
WHWang Hansong
Wang Hansong
TCTing-Chang Chang
Ting-Chang Chang