Energy Management of Hybrid Electric Vehicles

Hong Wang; Yanjun Huang; Hongwen He; Chen Lv; Wei Liu; Amir Khajepour

doi:10.1016/B978-0-12-812786-5.00005-7

Energy Management of Hybrid Electric Vehicles

Hong Wang, Yanjun Huang, Hongwen He, Chen Lv, Wei Liu, Amir Khajepour

School of Mechanical Engineering

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

21 Citations (Scopus)

Abstract

This chapter presents a comprehensive review of energy-management strategy (EMS) systems utilized in hybrid electric vehicles (HEVs). HEVs are one of the most viable technologies to achieve energy savings and environmental protection goals. EMSs of HEVs have been studied extensively to improve the performance of HEVs and to speed up the industrialization of them. In this chapter, different types of power-management algorithms such as offline and online methods are briefly reviewed and classified. This chapter also presents a case study that shows three different energy0management approaches for the control of a series hybrid electric off-road vehicles using rules-based, dynamic programming, and model predictive control strategies. The performance of these three EMSs is evaluated and compared.

Original language	English
Title of host publication	Modeling, Dynamics, and Control of Electrified Vehicles
Publisher	Elsevier
Pages	159-206
Number of pages	48
ISBN (Electronic)	9780128127865
ISBN (Print)	9780128131091
DOIs	https://doi.org/10.1016/B978-0-12-812786-5.00005-7
Publication status	Published - 1 Jan 2017

Keywords

Hybrid electric vehicles
dynamic programming, and model predictive control strategy
energy-management strategy
heuristic strategies
optimization-based strategies

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10.1016/B978-0-12-812786-5.00005-7

Cite this

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abstract = "This chapter presents a comprehensive review of energy-management strategy (EMS) systems utilized in hybrid electric vehicles (HEVs). HEVs are one of the most viable technologies to achieve energy savings and environmental protection goals. EMSs of HEVs have been studied extensively to improve the performance of HEVs and to speed up the industrialization of them. In this chapter, different types of power-management algorithms such as offline and online methods are briefly reviewed and classified. This chapter also presents a case study that shows three different energy0management approaches for the control of a series hybrid electric off-road vehicles using rules-based, dynamic programming, and model predictive control strategies. The performance of these three EMSs is evaluated and compared.",

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AU - Wang, Hong

AU - Huang, Yanjun

AU - He, Hongwen

AU - Lv, Chen

AU - Liu, Wei

AU - Khajepour, Amir

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AB - This chapter presents a comprehensive review of energy-management strategy (EMS) systems utilized in hybrid electric vehicles (HEVs). HEVs are one of the most viable technologies to achieve energy savings and environmental protection goals. EMSs of HEVs have been studied extensively to improve the performance of HEVs and to speed up the industrialization of them. In this chapter, different types of power-management algorithms such as offline and online methods are briefly reviewed and classified. This chapter also presents a case study that shows three different energy0management approaches for the control of a series hybrid electric off-road vehicles using rules-based, dynamic programming, and model predictive control strategies. The performance of these three EMSs is evaluated and compared.

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KW - dynamic programming, and model predictive control strategy

KW - energy-management strategy

KW - heuristic strategies

KW - optimization-based strategies

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BT - Modeling, Dynamics, and Control of Electrified Vehicles

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ER -

Energy Management of Hybrid Electric Vehicles

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