Open AccessApplication of Driving Style Recognition in the Shift Control of a Two-speed DCT for Pure Electric Vehicles
Author(s) -
Jianjun Zhang,
Xinbo Chen
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1922/1/012002
Subject(s) - transmission (telecommunications) , schedule , computer science , clutch , matlab , manual transmission , function (biology) , control theory (sociology) , simulation , control (management) , engineering , automotive engineering , artificial intelligence , telecommunications , evolutionary biology , biology , operating system
The driving style recognition algorithm can be used to obtain the driver’s current driving style in real time. Thus, the algorithm is combined with the transmission control logic to make the shifting operation of the transmission adaptive to drivers of different driving styles. Firstly, by introducing the dynamic coefficient, the comprehensive shift schedule that match different driving styles is calculated. Next, the two transmission shift evaluation indexes, i.e., shift time and degree of jerk are determined, with the corresponding objective function established. Using this function as the constraint function of the NSGA-II multi-objective genetic optimization algorithm, the Pareto optimal solution set of the engagement speed control parameters of the two clutches under different motor output torques is obtained. The transmission shift control strategy proposed herewith is validated by the co-simulation of MATLAB/Simulink and MSC Carsim software. The co-simulation results show that the transmission can automatically adjust the shift parameters according to different types of driving styles, so that the shift schedule and shift quality of the two-speed dual-clutch transmission are in accordance with the needs of drivers with different driving styles.