@inproceedings{507079b93d94406f89d4ba6b497d3637,
title = "Research on energy management strategy of mining truck based on MPC",
abstract = "The power system of electric-drive truck equipped with hybrid energy storage is proposed to efficiently utilize the engine power and braking regenerative energy. The truck power system model including the hybrid energy storage system is built in which the energy management of mining truck is designed with the minimizing fuel consumption. The optimal output engine power under the cycle working condition of the truck can be predicted by the model predictive control method. Taking the advantage of battery and supercapacitor, the power distribution strategy of hybrid energy storage system is suggested to make the engine operating around the optimal fuel consumption curve. This energy management strategy of the truck is executed in realtime with the driver-in-loop. The results indicate that this energy management strategy can reduce the fuel consumption up to 13\%\textasciitilde{}15\% comparing with that of traditional electricdrive truck.",
keywords = "Energy management, Hybrid energy storage, Mining truck, Model predict control, Real-time simulation",
author = "Yanhua Shen and Shuai Li and Tao Xu",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 7th International Conference on Advances in Construction Machinery and Vehicle Engineering, ICACMVE 2019 ; Conference date: 14-05-2019 Through 16-05-2019",
year = "2019",
month = may,
doi = "10.1109/ICACMVE.2019.00053",
language = "English",
series = "Proceedings - 2019 International Conference on Advances in Construction Machinery and Vehicle Engineering, ICACMVE 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "237--242",
booktitle = "Proceedings - 2019 International Conference on Advances in Construction Machinery and Vehicle Engineering, ICACMVE 2019",
address = "United States",
}