@article{ref1,
title="Energy-saving model predictive cruise control combined with vehicle driving cycles",
journal="International journal of automotive technology",
year="2022",
author="Xu, ZhiHao and Li, JianHua and Xiao, Feng and Zhang, Xu and Song, ShiXin and Wang, Da and Qi, ChunYang and Wang, JianFeng and Peng, SiLun",
volume="23",
number="2",
pages="439-450",
abstract="This study analyzes the problem of adaptive cruise control of vehicles in different driving cycles and divides diverse weight coefficient intervals for the vehicles under the different driving cycles to improve the adaptability of the vehicles in various environments. This paper first describes the driving environment of the adaptive cruise vehicle, and a model prediction algorithm with fixed weight coefficients is established to control the vehicle state. Then, a neural network is established to identify the vehicle driving cycles, the weight intervals are divided in accordance with different driving cycles, and the weight value is dynamically adjusted through fuzzy control. Lastly, the variable weight coefficients of different driving cycles are combined with the model prediction controller. The software cosimulation shows that the method designed in this paper plays a positive role in the fuel economy of adaptive cruise.<p /> <p>Language: en</p>",
language="en",
issn="1229-9138",
doi="10.1007/s12239-022-0040-z",
url="http://dx.doi.org/10.1007/s12239-022-0040-z"
}