Joint design and control of electric vehicle propulsion systems

Frans J.R. Verbruggen; Mauro Salazar; Marco Pavone; Theo Hofman

Joint design and control of electric vehicle propulsion systems

Frans J.R. Verbruggen
, Mauro Salazar
, Marco Pavone
, Theo Hofman

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

28 Citations (Scopus)

241 Downloads (Pure)

Abstract

This paper presents models and optimization methods for the design of electric vehicle propulsion systems. Specifically, we first derive a bi-convex model of a battery electric powertrain including the transmission and explicitly accounting for the impact of its components' size on the energy consumption of the vehicle. Second, we formulate the energy-optimal sizing and control problem for a given driving cycle and solve it as a sequence of second-order conic programs. Finally, we present a real-world case study for heavy-duty electric trucks, comparing a single-gear transmission with a continuously variable transmission (CVT), and validate our approach with respect to state-of-the-art particle swarm optimization algorithms. Our results show that, depending on the electric motor technology, CVTs can reduce the energy consumption and the battery size of electric trucks between up to 10%, and shrink the electric motor up to 50%.

Original language	English
Title of host publication	European Control Conference 2020, ECC 2020
Publisher	Institute of Electrical and Electronics Engineers
Pages	1725-1731
Number of pages	7
ISBN (Electronic)	9783907144015
Publication status	Published - May 2020
Event	2020 European Control Conference, ECC 2020 - Saint Petersburg, Russian Federation Duration: 12 May 2020 → 15 May 2020

Conference

Conference	2020 European Control Conference, ECC 2020
Abbreviated title	ECC 2020
Country/Territory	Russian Federation
City	Saint Petersburg
Period	12/05/20 → 15/05/20

Funding

ACKNOWLEDGMENT The authors would like to thank Dr. C. Dinca and Dr. S. Singh for the fruitful discussions and Dr. I. New, S. Schneider, J. T. Luke and P. Duhr for proofreading this paper. This research was partially supported by the National Science Foundation under CAREER Award CMMI-1454737 and CPS Award-1837135, and the Toyota Research Institute (TRI). This article solely reflects the opinions and conclusions of its authors and not NSF, TRI, or any other entity.

Funders	Funder number
National Science Foundation	1837135, CMMI-1454737, CPS Award-1837135
Toyota Research Institute

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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http://asl.stanford.edu/wp-content/papercite-data/pdf/Verbruggen.Salazar.ea.ECC2020.pdf

Cite this

@inproceedings{1486a76d1fe04f9fa310586016c349bd,

title = "Joint design and control of electric vehicle propulsion systems",

abstract = "This paper presents models and optimization methods for the design of electric vehicle propulsion systems. Specifically, we first derive a bi-convex model of a battery electric powertrain including the transmission and explicitly accounting for the impact of its components' size on the energy consumption of the vehicle. Second, we formulate the energy-optimal sizing and control problem for a given driving cycle and solve it as a sequence of second-order conic programs. Finally, we present a real-world case study for heavy-duty electric trucks, comparing a single-gear transmission with a continuously variable transmission (CVT), and validate our approach with respect to state-of-the-art particle swarm optimization algorithms. Our results show that, depending on the electric motor technology, CVTs can reduce the energy consumption and the battery size of electric trucks between up to 10\%, and shrink the electric motor up to 50\%.",

author = "Verbruggen, \{Frans J.R.\} and Mauro Salazar and Marco Pavone and Theo Hofman",

year = "2020",

month = may,

language = "English",

pages = "1725--1731",

booktitle = "European Control Conference 2020, ECC 2020",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "2020 European Control Conference, ECC 2020, ECC 2020 ; Conference date: 12-05-2020 Through 15-05-2020",

}

Verbruggen, FJR, Salazar, M, Pavone, M & Hofman, T 2020, Joint design and control of electric vehicle propulsion systems. in European Control Conference 2020, ECC 2020., 9143869, Institute of Electrical and Electronics Engineers, pp. 1725-1731, 2020 European Control Conference, ECC 2020, Saint Petersburg, Russian Federation, 12/05/20. <http://asl.stanford.edu/wp-content/papercite-data/pdf/Verbruggen.Salazar.ea.ECC2020.pdf>

TY - GEN

T1 - Joint design and control of electric vehicle propulsion systems

AU - Verbruggen, Frans J.R.

AU - Salazar, Mauro

AU - Pavone, Marco

AU - Hofman, Theo

PY - 2020/5

Y1 - 2020/5

N2 - This paper presents models and optimization methods for the design of electric vehicle propulsion systems. Specifically, we first derive a bi-convex model of a battery electric powertrain including the transmission and explicitly accounting for the impact of its components' size on the energy consumption of the vehicle. Second, we formulate the energy-optimal sizing and control problem for a given driving cycle and solve it as a sequence of second-order conic programs. Finally, we present a real-world case study for heavy-duty electric trucks, comparing a single-gear transmission with a continuously variable transmission (CVT), and validate our approach with respect to state-of-the-art particle swarm optimization algorithms. Our results show that, depending on the electric motor technology, CVTs can reduce the energy consumption and the battery size of electric trucks between up to 10%, and shrink the electric motor up to 50%.

AB - This paper presents models and optimization methods for the design of electric vehicle propulsion systems. Specifically, we first derive a bi-convex model of a battery electric powertrain including the transmission and explicitly accounting for the impact of its components' size on the energy consumption of the vehicle. Second, we formulate the energy-optimal sizing and control problem for a given driving cycle and solve it as a sequence of second-order conic programs. Finally, we present a real-world case study for heavy-duty electric trucks, comparing a single-gear transmission with a continuously variable transmission (CVT), and validate our approach with respect to state-of-the-art particle swarm optimization algorithms. Our results show that, depending on the electric motor technology, CVTs can reduce the energy consumption and the battery size of electric trucks between up to 10%, and shrink the electric motor up to 50%.

UR - https://www.scopus.com/pages/publications/85090116102

M3 - Conference contribution

AN - SCOPUS:85090116102

SP - 1725

EP - 1731

BT - European Control Conference 2020, ECC 2020

PB - Institute of Electrical and Electronics Engineers

T2 - 2020 European Control Conference, ECC 2020

Y2 - 12 May 2020 through 15 May 2020

ER -

Joint design and control of electric vehicle propulsion systems

Abstract

Conference

Funding

UN SDGs

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