The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
A Parallel Hybrid Electric Vehicle Energy Management Strategy Using Stochastic Model Predictive Control With Road Grade Preview
Abstract
The energy efficiency of parallel hybrid electric vehicles (HEVs) can degrade significantly when the battery state-of-charge (SoC) reaches its boundaries. The road grade has a great influence on the HEV battery charging and discharging processes, and therefore the HEV energy management can be benefited from the road grade preview. In real-world driving, the road grade ahead can be considered as a random variable because the future route is not always available to the HEV controller. This brief proposes a stochastic model predictive control-based energy management strategy using the vehicle location, traveling direction, and terrain information of the area for HEVs running in hilly regions with light traffic. The strategy does not require a determined route being known in advance. The road grade is modeled as a Markov chain and stochastic HEV fuel consumption and battery SoC models are developed. The HEV energy management problem is formulated as a finite-horizon Markov decision process and solved using stochastic dynamic programming. The proposed method is evaluated in simulation and compared with an equivalent consumption minimization strategy and the dynamic programming results. It is shown that the developed method can help maintaining the battery SoC within its boundaries and achieve good energy consumption performance.
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Cites
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Power management strategy for a parallel hybrid electric truck
Lin, C.-C., Peng, H., Grizzle, J. W., & Kang, J.-M. (2003) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2003.815606 · Cited by 1,277
MPC-Based Energy Management of a Power-Split Hybrid Electric Vehicle
Borhan, H., Vahidi, A., Phillips, A. M., Kuang, M. L., Kolmanovsky, I. V., & Di Cairano, S. (2012) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2011.2134852 · Cited by 736
A-ECMS: An Adaptive Algorithm for Hybrid Electric Vehicle Energy Management
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A-ECMS: An Adaptive Algorithm for Hybrid Electric Vehicle Energy Management
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Modeling and Control of a Power-Split Hybrid Vehicle
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A Stochastic Optimal Control Approach for Power Management in Plug-In Hybrid Electric Vehicles
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Cited by
Ali, A., & Söffker, D. (2018) · Energies · doi:10.3390/en11030476 · Cited by 134
Zhang, S., Luo, Y., Wang, J., Wang, X., & Li, K. (2017) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2017.2672542 · Cited by 106
Self-citationA digital twin-based edge intelligence framework for decentralized decision in IoV system
El Azzaoui, A., Jeremiah, S. R., Xiong, N. N., & Park, J. H. (2023) · Information Sciences · doi:10.1016/j.ins.2023.119595 · Cited by 22
Metadata
- Authors
- Zeng, X., & Wang, J.
- Venue
- IEEE Transactions on Control Systems Technology
- Published
- 2015-11
- Volume
- 23
- Issue
- 6
- Pages
- 2416-2423
- ISSN
- 1063-6536 (ISSN-L)
- 1558-0865
- OpenAlex
- W2029490915
- Cited by
- 254
- References
- 16
- FWCI
- 24.93
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zeng, X., & Wang, J. (2015). A Parallel Hybrid Electric Vehicle Energy Management Strategy Using Stochastic Model Predictive Control With Road Grade Preview. IEEE Transactions on Control Systems Technology. https://doi.org/10.1109/tcst.2015.2409235
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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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