Conference item

An ADMM algorithm for MPC-based energy management in hybrid electric vehicles with nonlinear losses

Abstract:: In this paper we present a convex formulation of the Model Predictive Control (MPC) optimisation for energy management in hybrid electric vehicles, and an Alternating Direction Method of Multipliers (ADMM) algorithm for its solution. We develop a new proof of convexity for the problem that allows the nonlinear dynamics to be modelled as a linear system, then demonstrate the performance of ADMM in comparison with Dynamic Programming (DP) through simulation. The results demonstrate up to two orders of magnitude improvement in solution time for comparable accuracy against DP.

Publication status:: Published

Peer review status:: Peer reviewed

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APA Style

East, S., & Cannon, M. (2019). An ADMM algorithm for MPC-based energy management in hybrid electric vehicles with nonlinear losses. 2018 IEEE Conference on Decision and Control (CDC).

MLA Style

East, S., and M. Cannon. “An ADMM Algorithm for MPC-Based Energy Management in Hybrid Electric Vehicles with Nonlinear Losses.” 2018 IEEE Conference on Decision and Control (CDC), IEEE, 2019.

Chicago Style

East, S, and M Cannon. 2019. “An ADMM Algorithm for MPC-Based Energy Management in Hybrid Electric Vehicles with Nonlinear Losses.” In 2018 IEEE Conference on Decision and Control (CDC). IEEE.
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Files:: CDC18_1835_FI.pdf

(Preview, Accepted manuscript, pdf, 434.8KB, Terms of use)

Publisher copy:: 10.1109/CDC.2018.8619731

Authors

+ East, S More by this author

Institution:: University of Oxford
Division:: MPLS Division
Department:: Engineering Science
Role:: Author

+ Cannon, M More by this author

Institution:: University of Oxford
Division:: MPLS
Department:: Engineering Science
Oxford college:: St John's College
Role:: Author
ORCID:: 0000-0003-2189-7876

+ Engineering and Physical Sciences Research Council More from this funder

Publisher:: IEEE
Host title:: 2018 IEEE Conference on Decision and Control (CDC)
Journal:: 2018 IEEE Conference on Decision and Control (CDC) More from this journal
Publication date:: 2019-01-21
Acceptance date:: 2018-09-13
DOI:: 10.1109/CDC.2018.8619731
EISSN:: 2576-2370
ISSN:: 0743-1546

Pubs id:: pubs:920427
UUID:: uuid:0df993e8-e731-41cd-9b9b-fc1c942ddd54
Local pid:: pubs:920427
Source identifiers:: 920427
Deposit date:: 2018-09-19

Terms of use

Copyright holder:: Institute of Electrical and Electronics Engineers
Copyright date:: 2019
Notes:: Copyright © 2018, IEEE

Licence:: Terms and Conditions of Use for Oxford University Research Archive

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