Energy management strategy for plug-in hybrid electric vehicles based on vehicle speed prediction and limited traffic information

Daxin Chen, Tao Chen, Zhijun Li, Zhixi Liu, Chaoyang Sun and Hua Zhao

Energy, 2025, vol. 326, issue C

Abstract: —The adaptability of the energy management strategy (EMS) of a plug-in hybrid electric vehicle (PHEV) to actual road conditions determines the actual performance. This paper proposes a long short-term EMS (LS-EMS) that utilizes limited traffic information and speed prediction to constrain the state of charge (SOC) and optimize the powertrain. The strategy aims to improve the fuel economy of a power-split PHEV on real driving routes. In the long-time scale, the fuzzy controller converts limited connected information into SOC constraints for each sub-section of the entire trip. In the short-time scale, a speed predictor constructed with temporal convolutional networks, predicts vehicle speed from 5 to 15 s into the future. Combining the long short-term information, the model predictive control optimizes power allocation based on the look-ahead vehicle speed under segmental SOC constraints. Simulations are conducted on the collected commuter routes. The proposed method within a 10-s prediction period closely approximates the optimal result calculated by dynamic programming. The proposed LS-EMS plans the range of SOC by section on the commuter road and reduces the energy consumption by 12.0 % compared to the charge-depleting charge-sustaining rule strategy.

Keywords: Plug-in hybrid electric vehicles; Energy consumption optimization; Limited connected information; SOC constraints; Energy management (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544225019346
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:326:y:2025:i:c:s0360544225019346

DOI: 10.1016/j.energy.2025.136292

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().