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Optimal Dimensioning and Power Management of a Fuel Cell/Battery Hybrid Bus via Convex Programming
Abstract
This paper is concerned with the simultaneous optimal component sizing and power management of a fuel cell/battery hybrid bus. Existing studies solve the combined plant/controller optimization problem for fuel cell hybrid vehicles (FCHVs) by using methods with disadvantages of heavy computational burden and/or suboptimality, for which only a single driving profile was often considered. This paper adds three important contributions to the FCHVs-related literature. First, convex programming is extended to rapidly and efficiently optimize both the power management strategy and sizes of the fuel cell system (FCS) and the battery pack in the hybrid bus. The main purpose is to encourage more researchers and engineers in FCHVs field to utilize the new effective tool. Second, the influence of the driving pattern on the optimization result (both the component sizes and hydrogen economy) of the bus is systematically investigated by considering three different bus driving routes, including two standard testing cycles and a realistic bus line cycle with slope information in Gothenburg, Sweden. Finally, the sensitivity of the optimization outcome to the potential price decreases of the FCS and the battery is quantitatively examined.
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Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
A comparative study of equivalent circuit models for Li-ion batteries
Hu, X., Li, S., & Peng, H. (2012) · Journal of Power Sources · doi:10.1016/j.jpowsour.2011.10.013 · Cited by 2,179
Cited by
Recent advances and challenges of fuel cell based power system architectures and control – A review
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Ding, T., Liu, S., Yuan, W., Bie, Z., & Zeng, B. (2016) · IEEE Transactions on Sustainable Energy · doi:10.1109/tste.2015.2494587 · Cited by 423
Emergence of hybrid energy storage systems in renewable energy and transport applications – A review
Hemmati, R., & Saboori, H. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.06.029 · Cited by 423
Advanced Machine Learning Approach for Lithium-Ion Battery State Estimation in Electric Vehicles
Hu, X., Li, S. E., & Yang, Y. (2016) · IEEE Transactions on Transportation Electrification · doi:10.1109/tte.2015.2512237 · Cited by 375
Self-citationReview of energy storage systems for vehicles based on technology, environmental impacts, and costs
Balali, Y., & Stegen, S. (2021) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.110185 · Cited by 260
Metadata
- Authors
- Hu, X., Murgovski, N., Johannesson, L. M., & Egardt, B.
- Venue
- IEEE/ASME Transactions on Mechatronics
- Published
- 2015-02
- Volume
- 20
- Issue
- 1
- Pages
- 457-468
- ISSN
- 1083-4435 (ISSN-L)
- 1941-014X
- OpenAlex
- W1996984710
- Cited by
- 307
- References
- 2
- FWCI
- 40.03
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Hu, X., Murgovski, N., Johannesson, L. M., & Egardt, B. (2015). Optimal Dimensioning and Power Management of a Fuel Cell/Battery Hybrid Bus via Convex Programming. IEEE/ASME Transactions on Mechatronics. https://doi.org/10.1109/tmech.2014.2336264
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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