@inproceedings{56df16893b76466187e8df2cda270574,
title = "Study on MPC-based Energy Management for a Series Tracked Vehicle",
abstract = "To improve the energy usage ratio of a series tracked vehicle, energy management control strategy based on model predictive control (MPC) was proposed. A nonlinear prediction model is established, and the cost function based on the equivalent fuel consumption model of the battery is used as the evaluation index, the dynamic programming (DP) algorithm is used to implement the rolling optimization solution in the prediction time domain which complete the real-time power allocation. Compared with rule-based control strategy, MPC can achieve a 4.1\% better economy performance and more balanced state of charge (SOC).",
keywords = "dynamic programming, model predictive control, power distribution, series hybrid vehicle",
author = "Chao Wei and Xitao Wu and Sicheng Liu",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 28th IEEE International Symposium on Industrial Electronics, ISIE 2019 ; Conference date: 12-06-2019 Through 14-06-2019",
year = "2019",
month = jun,
doi = "10.1109/ISIE.2019.8781404",
language = "English",
series = "IEEE International Symposium on Industrial Electronics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1898--1902",
booktitle = "Proceedings - 2019 IEEE 28th International Symposium on Industrial Electronics, ISIE 2019",
address = "United States",
}