SwePub
Sök i LIBRIS databas

  Extended search

onr:"swepub:oai:research.chalmers.se:6ee1cf8d-e1cd-470e-979a-cdb59c229621"
 

Search: onr:"swepub:oai:research.chalmers.se:6ee1cf8d-e1cd-470e-979a-cdb59c229621" > Electrochemical Mod...

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Electrochemical Model-Based Fast Charging: Physical Constraint-Triggered PI Control

Li, Yang, 1984 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Vilathgamuwa, D. Mahinda (author)
Queensland University of Technology (QUT)
Wikner, Evelina, 1987 (author)
Chalmers tekniska högskola,Chalmers University of Technology
show more...
Wei, Zhongbao (author)
Beijing Institute of Technology
Zhang, Xinan (author)
University of Western Australia
Thiringer, Torbjörn, 1966 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Wik, Torsten, 1968 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Zou, Changfu, 1987 (author)
Chalmers tekniska högskola,Chalmers University of Technology
show less...
 (creator_code:org_t)
2021
2021
English.
In: IEEE Transactions on Energy Conversion. - 1558-0059 .- 0885-8969. ; 36:4, s. 3208-3220
  • Journal article (peer-reviewed)
Abstract Subject headings
Close  
  • This paper proposes a new fast charging strategy for lithium-ion (Li-ion) batteries. The approach relies on an experimentally validated high-fidelity model describing battery electrochemical and thermal dynamics that determine the fast charging capability. Such a high-dimensional nonlinear dynamic model can be intractable to compute in real-time if it is fused with the extended Kalman filter or the unscented Kalman filter that is commonly used in the community of battery management. To significantly save computational efforts and achieve rapid convergence, the ensemble transform Kalman filter (ETKF) is selected and tailored to estimate the nonuniform Li-ion battery states. Then, a health- and safety-aware charging protocol is proposed based on successively applied proportional-integral (PI) control actions. The controller regulates charging rates using online battery state information and the imposed constraints, in which each PI control action automatically comes into play when its corresponding constraint is triggered. The proposed physical constraint-triggered PI charging control strategy with the ETKF is evaluated and compared with several prevalent alternatives. It shows that the derived controller can achieve close to the optimal solution in terms of charging time and trajectory, as determined by a nonlinear model predictive controller, but at a drastically reduced computational cost.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Naturresursteknik -- Energisystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Environmental Engineering -- Energy Systems (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)

Keyword

Electrochemical model
lithium plating
fast charging
lithium-ion (Li-ion) battery
ensemble transform Kalman filter (ETKF)

Publication and Content Type

art (subject category)
ref (subject category)

Find in a library

To the university's database

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view