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Cited by 221

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A New Battery/Ultracapacitor Energy Storage System Design and Its Motor Drive Integration for Hybrid Electric Vehicles

Lu, Shuai, Corzine, Keith A., Ferdowsi, Mehdi·2007·IEEE Transactions on Vehicular Technology

Abstract

This paper proposes a new energy storage system (ESS) design, including both batteries and ultracapacitors (UCs) in hybrid electric vehicle (HEV) and electric vehicle applications. The conventional designs require a DC-DC converter to interface the UC unit. Herein, the UC can be directly switched across the motor drive DC link during the peak power demands. The resulting wide voltage variation due to UC power transfer is addressed by the simple modulator that is introduced in this paper, so that the motor drive performance is not disrupted. Based on this new methodology, this paper further introduces two ESS schemes with different topologies, namely 1) UC rating and 2) energy flow control. They are applicable to both lightly and heavily hybridized HEVs. Both schemes have the benefits of high efficiency (without a DC-DC link) and low cost. The simulation and experimental results validate the new methodology.

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Crossref · 10.1109/tvt.2007.896971

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Metadata

Authors
Lu, S., Corzine, K. A., & Ferdowsi, M.
Venue
IEEE Transactions on Vehicular Technology
Published
2007-07
Volume
56
Issue
4
Pages
1516-1523
ISSN
  • 0018-9545 (ISSN-L)
  • 1939-9359
OpenAlex
W2097632345
Cited by
221
References
0
FWCI
22.99
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A New Battery/Ultracapacitor Energy Storage System Design and Its Motor Drive Integration for Hybrid Electric Vehicles. https://app.cochat.ai/papers/10.1109/tvt.2007.896971
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Lu, S., Corzine, K. A., & Ferdowsi, M. (2007). A New Battery/Ultracapacitor Energy Storage System Design and Its Motor Drive Integration for Hybrid Electric Vehicles. IEEE Transactions on Vehicular Technology. https://doi.org/10.1109/tvt.2007.896971

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.