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

Xiaobo Sun, Weirong Liu, Mengfei Wen, Yue Wu, Heng Li, Jiahao Huang, Chao Hu and Zhiwu Huang
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Xiaobo Sun: School of Computer Science and Engineering, Central South University, Changsha 410083, China
Weirong Liu: School of Computer Science and Engineering, Central South University, Changsha 410083, China
Mengfei Wen: Changsha College for Preschool Education, Changsha 410007, China
Yue Wu: School of Automation, Central South University, Changsha 410083, China
Heng Li: School of Computer Science and Engineering, Central South University, Changsha 410083, China
Jiahao Huang: School of Automation, Central South University, Changsha 410083, China
Chao Hu: Big Date Institute, Central South University, Changsha 410087, China
Zhiwu Huang: School of Automation, Central South University, Changsha 410083, China

Energies, 2021, vol. 14, issue 12, 1-17

Abstract: 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.

Keywords: connected hybrid electric vehicle; energy management; receding horizon control; energy-saving (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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