Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles

Huilong Yu; Dongpu Cao

doi:10.1109/IVS.2018.8500629

Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles

Huilong Yu
, Dongpu Cao

Vehicle Intelligence Pioneers Inc.
University of Waterloo

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

11 Citations (Scopus)

Abstract

Hybrid energy storage system (HESS) has been recognized as one of the most promising solutions to overcome the drawbacks of the expensive and short life lithium-ion battery with low power density, by introducing a proper number of supercapcitors. However, the hybridization introduces complicated sizing and energy management problems. This papers aims to investigate the sizing and real-time energy management of a devised HESS for electric vehicles with an electric race car as a case study. In particular, a proposed multi-objective Bi-level optimal sizing and control framework is implemented to find the optimal parameters of the energy management algorithm, the optimal number of the lithiumion battery cells and the supercapacitor banks. The simulation results have validated the effectiveness of the investigated methodology in minimizing the total mass of the HESS and maximizing the cycle life of the lithium-ion battery.

Original language	English
Title of host publication	2018 IEEE Intelligent Vehicles Symposium, IV 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	191-196
Number of pages	6
ISBN (Electronic)	9781538644522
DOIs	https://doi.org/10.1109/IVS.2018.8500629
Publication status	Published - 18 Oct 2018
Externally published	Yes
Event	2018 IEEE Intelligent Vehicles Symposium, IV 2018 - Changshu, Suzhou, China Duration: 26 Sept 2018 → 30 Sept 2018

Publication series

Name	IEEE Intelligent Vehicles Symposium, Proceedings
Volume	2018-June

Conference

Conference	2018 IEEE Intelligent Vehicles Symposium, IV 2018
Country/Territory	China
City	Changshu, Suzhou
Period	26/09/18 → 30/09/18

UN SDGs

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

SDG 7 Affordable and Clean Energy

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10.1109/IVS.2018.8500629

Cite this

Yu, H., & Cao, D. (2018). Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles. In 2018 IEEE Intelligent Vehicles Symposium, IV 2018 (pp. 191-196). Article 8500629 (IEEE Intelligent Vehicles Symposium, Proceedings; Vol. 2018-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IVS.2018.8500629

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title = "Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles",

abstract = "Hybrid energy storage system (HESS) has been recognized as one of the most promising solutions to overcome the drawbacks of the expensive and short life lithium-ion battery with low power density, by introducing a proper number of supercapcitors. However, the hybridization introduces complicated sizing and energy management problems. This papers aims to investigate the sizing and real-time energy management of a devised HESS for electric vehicles with an electric race car as a case study. In particular, a proposed multi-objective Bi-level optimal sizing and control framework is implemented to find the optimal parameters of the energy management algorithm, the optimal number of the lithiumion battery cells and the supercapacitor banks. The simulation results have validated the effectiveness of the investigated methodology in minimizing the total mass of the HESS and maximizing the cycle life of the lithium-ion battery.",

author = "Huilong Yu and Dongpu Cao",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Intelligent Vehicles Symposium, IV 2018 ; Conference date: 26-09-2018 Through 30-09-2018",

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doi = "10.1109/IVS.2018.8500629",

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Yu, H & Cao, D 2018, Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles. in 2018 IEEE Intelligent Vehicles Symposium, IV 2018., 8500629, IEEE Intelligent Vehicles Symposium, Proceedings, vol. 2018-June, Institute of Electrical and Electronics Engineers Inc., pp. 191-196, 2018 IEEE Intelligent Vehicles Symposium, IV 2018, Changshu, Suzhou, China, 26/09/18. https://doi.org/10.1109/IVS.2018.8500629

Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles. / Yu, Huilong; Cao, Dongpu.
2018 IEEE Intelligent Vehicles Symposium, IV 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 191-196 8500629 (IEEE Intelligent Vehicles Symposium, Proceedings; Vol. 2018-June).

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

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T1 - Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles

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AU - Cao, Dongpu

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N2 - Hybrid energy storage system (HESS) has been recognized as one of the most promising solutions to overcome the drawbacks of the expensive and short life lithium-ion battery with low power density, by introducing a proper number of supercapcitors. However, the hybridization introduces complicated sizing and energy management problems. This papers aims to investigate the sizing and real-time energy management of a devised HESS for electric vehicles with an electric race car as a case study. In particular, a proposed multi-objective Bi-level optimal sizing and control framework is implemented to find the optimal parameters of the energy management algorithm, the optimal number of the lithiumion battery cells and the supercapacitor banks. The simulation results have validated the effectiveness of the investigated methodology in minimizing the total mass of the HESS and maximizing the cycle life of the lithium-ion battery.

AB - Hybrid energy storage system (HESS) has been recognized as one of the most promising solutions to overcome the drawbacks of the expensive and short life lithium-ion battery with low power density, by introducing a proper number of supercapcitors. However, the hybridization introduces complicated sizing and energy management problems. This papers aims to investigate the sizing and real-time energy management of a devised HESS for electric vehicles with an electric race car as a case study. In particular, a proposed multi-objective Bi-level optimal sizing and control framework is implemented to find the optimal parameters of the energy management algorithm, the optimal number of the lithiumion battery cells and the supercapacitor banks. The simulation results have validated the effectiveness of the investigated methodology in minimizing the total mass of the HESS and maximizing the cycle life of the lithium-ion battery.

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M3 - Conference contribution

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T2 - 2018 IEEE Intelligent Vehicles Symposium, IV 2018

Y2 - 26 September 2018 through 30 September 2018

ER -

Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles

Abstract

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Conference

UN SDGs

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