Open AccessResearch on Energy Management Strategy of Diesel Hybrid Electric Vehicle Based on Decision Tree CART Algorithm
Author(s) -
Fang Ye,
Xicheng Zhai
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/677/3/032076
Subject(s) - cart , decision tree , computer science , energy management , diesel fuel , tree (set theory) , diesel engine , electric vehicle , automotive engineering , algorithm , fuel efficiency , power (physics) , energy (signal processing) , mathematical optimization , artificial intelligence , engineering , mathematics , statistics , mechanical engineering , mathematical analysis , physics , quantum mechanics
Aiming at the emission of nitrogen oxides from hybrid electric vehicles (HEV), a strategy of diesel hybrid energy management based on decision tree CART algorithm was proposed.Firstly, a classification algorithm combining decision tree and regression tree is proposed to predict the trend change relationship of a case from one or more predictive variables according to the category and variable characteristics.Secondly, by controlling the torque distribution between the engine and the motor, an additional degree of freedom is introduced to adjust the trade-off between pure fuel economy and pure restriction.Finally, the simulation method is used to understand the system performance and adjust the proposed energy management strategy.The results show that in the proposed energy management strategy for diesel hybrid power, the reduction of NO x has an impact on fuel consumption, and the potential of NO x emission can be limited by choosing the best operating point and limiting engine power.