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Article

A Real-Time Optimal Car-Following Power Management Strategy for Hybrid Electric Vehicles with ACC Systems

1
School of Computer Science and Engineering, Central South University, Changsha 410083, China
2
School of Automation, Central South University, Changsha 410083, China
3
Changsha College for Preschool Education, Changsha 410007, China
4
Big Date Institute, Central South University, Changsha 410087, China
*
Author to whom correspondence should be addressed.
Academic Editor: Aldo Sorniotti
Energies 2021, 14(12), 3438; https://doi.org/10.3390/en14123438
Received: 24 March 2021 / Revised: 30 May 2021 / Accepted: 2 June 2021 / Published: 10 June 2021
(This article belongs to the Collection Electric and Hybrid Vehicles Collection)
This paper develops a model predictive multi-objective control framework based on an adaptive cruise control (ACC) system to solve the energy allocation and battery state of charge (SOC) maintenance problems of hybrid electric vehicles in the car-following scenario. The proposed control framework is composed of a car-following layer and an energy allocation layer. In the car-following layer, a multi-objective problem is solved to maintain safety and comfort, and the generated speed sequence in the prediction time domain is put forward to the energy allocation layer. In the energy allocation layer, an adaptive equivalent-factor-based consumption minimization strategy with the predicted velocity sequences is adopted to improve the engine efficiency and fuel economy. The equivalent factor reflects the extent of SOC variation, which is used to maintain the battery SOC level when optimizing the energy. The proposed controller is evaluated in the New York City Cycle (NYCC) driving cycle and the Urban Dynamometer Driving Schedule (UDDS) driving cycle, and the comparison results demonstrate the effectiveness of the proposed controller. View Full-Text
Keywords: connected hybrid electric vehicle; energy management; receding horizon control; energy-saving connected hybrid electric vehicle; energy management; receding horizon control; energy-saving
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MDPI and ACS Style

Sun, X.; Liu, W.; Wen, M.; Wu, Y.; Li, H.; Huang, J.; Hu, C.; Huang, Z. A Real-Time Optimal Car-Following Power Management Strategy for Hybrid Electric Vehicles with ACC Systems. Energies 2021, 14, 3438. https://doi.org/10.3390/en14123438

AMA Style

Sun X, Liu W, Wen M, Wu Y, Li H, Huang J, Hu C, Huang Z. A Real-Time Optimal Car-Following Power Management Strategy for Hybrid Electric Vehicles with ACC Systems. Energies. 2021; 14(12):3438. https://doi.org/10.3390/en14123438

Chicago/Turabian Style

Sun, Xiaobo; Liu, Weirong; Wen, Mengfei; Wu, Yue; Li, Heng; Huang, Jiahao; Hu, Chao; Huang, Zhiwu. 2021. "A Real-Time Optimal Car-Following Power Management Strategy for Hybrid Electric Vehicles with ACC Systems" Energies 14, no. 12: 3438. https://doi.org/10.3390/en14123438

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