Hybrid-learning-based classification and quantitative inference of driver braking intensity of an electrified vehicle

• المؤلفون الرئيسيون: Lv, Chen, Xing, Yang, Lu, Chao, Liu, Yahui, Guo, Hongyan, Gao, Hongbo, Cao, Dongpu
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2019
• الموضوعات: Hybrid Learning; Random Forest; Engineering::Electrical and electronic engineering
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/105882; http://hdl.handle.net/10220/50054; http://dx.doi.org/10.1109/TVT.2018.2808359

The recognition of driver's braking intensity is of great importance for advanced control and energy management for electric vehicles. In this paper, the braking intensity is classified into three levels based on novel hybrid unsupervised and supervised learning methods. First, instead of selec...