Optimal Energy Management Strategy for a Plug-in Hybrid Electric Vehicle Based on Road Grade Information

Yonggang Liu, Jie Li, Ming Ye, Datong Qin, Yi Zhang and Zhenzhen Lei
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Yonggang Liu: State Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing 400044, China
Jie Li: State Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing 400044, China
Ming Ye: Key Laboratory of Advanced Manufacture Technology for Automobile Parts, Ministry of Education, Chongqing University of Technology, Chongqing 400054, China
Datong Qin: State Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing 400044, China
Yi Zhang: Department of Mechanical Engineering, University of Michigan-Dearborn, Dearborn, MI 48128, USA
Zhenzhen Lei: State Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing 400044, China

Energies, 2017, vol. 10, issue 4, 1-20

Abstract: Energy management strategies (EMSs) are critical for the improvement of fuel economy of plug-in hybrid electric vehicles (PHEVs). However, conventional EMSs hardly consider the influence of uphill terrain on the fuel economy and battery life, leaving vehicles with insufficient battery power for continuous uphill terrains. Hence, in this study, an optimal control strategy for a PHEV based on the road grade information is proposed. The target state of charge ( SOC ) is estimated based on the road grade information as well as the predicted driving cycle on uphill road obtained from the GPS/GIS system. Furthermore, the trajectory of the SOC is preplanned to ensure sufficient electricity for the uphill terrain in the charge depleting (CD) and charge sustaining (CS) modes. The genetic algorithm is applied to optimize the parameters of the control strategy to maintain the SOC of battery in the CD mode. The pre-charge mode is designed to charge the battery in the CS mode from a reasonable distance before the uphill terrain. Finally, the simulation model of the powertrain system for the PHEV is established using MATLAB/Simulink platform. The results show that the proposed control strategy based on road-grade information helps successfully achieve better fuel economy and longer battery life.

Keywords: plug-in hybrid electric vehicles; energy management strategy; road grade; state of charge (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: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

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