Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
A Novel Battery State of Charge Estimation Method Based on a Super-Twisting Sliding Mode Observer
by
Liu, Yuntian
, Huangfu, Yigeng
, Gao, Fei
, Xu, Jiani
, Zhao, Dongdong
in
Accuracy
/ Algorithms
/ Automatic
/ Control theory
/ Electric power
/ Engineering Sciences
/ Fluid mechanics
/ Li-ion battery
/ Mechanics
/ Methods
/ Monte Carlo simulation
/ Noise
/ Partial differential equations
/ Physics
/ second-order RC equivalent circuit model
/ sliding mode observer
/ state of charge
/ super-twisting algorithm
/ Systems stability
/ Thermics
2018
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
A Novel Battery State of Charge Estimation Method Based on a Super-Twisting Sliding Mode Observer
by
Liu, Yuntian
, Huangfu, Yigeng
, Gao, Fei
, Xu, Jiani
, Zhao, Dongdong
in
Accuracy
/ Algorithms
/ Automatic
/ Control theory
/ Electric power
/ Engineering Sciences
/ Fluid mechanics
/ Li-ion battery
/ Mechanics
/ Methods
/ Monte Carlo simulation
/ Noise
/ Partial differential equations
/ Physics
/ second-order RC equivalent circuit model
/ sliding mode observer
/ state of charge
/ super-twisting algorithm
/ Systems stability
/ Thermics
2018
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
A Novel Battery State of Charge Estimation Method Based on a Super-Twisting Sliding Mode Observer
by
Liu, Yuntian
, Huangfu, Yigeng
, Gao, Fei
, Xu, Jiani
, Zhao, Dongdong
in
Accuracy
/ Algorithms
/ Automatic
/ Control theory
/ Electric power
/ Engineering Sciences
/ Fluid mechanics
/ Li-ion battery
/ Mechanics
/ Methods
/ Monte Carlo simulation
/ Noise
/ Partial differential equations
/ Physics
/ second-order RC equivalent circuit model
/ sliding mode observer
/ state of charge
/ super-twisting algorithm
/ Systems stability
/ Thermics
2018
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
A Novel Battery State of Charge Estimation Method Based on a Super-Twisting Sliding Mode Observer
Journal Article
A Novel Battery State of Charge Estimation Method Based on a Super-Twisting Sliding Mode Observer
2018
Request Book From Autostore
and Choose the Collection Method
Overview
A novel method for Li-ion battery state of charge (SOC) estimation based on a super-twisting sliding mode observer (STSMO) is proposed in this paper. To design the STSMO, the state equation of a second-order RC equivalent circuit model (SRCECM) is derived to represent the dynamic behaviors of the Li-ion battery, and the model parameters are determined by the pulse current discharge approach. The convergence of the STSMO is proven by Lyapunov stability theory. The experiments under three different discharge profiles are conducted on the Li-ion battery. Through comparisons with a conventional sliding mode observer (CSMO) and adaptive extended Kalman filter (AEKF), the superiority of the proposed observer for SOC estimation is validated.
Publisher
MDPI AG,MDPI
Subject
This website uses cookies to ensure you get the best experience on our website.