scholarly journals Regenerative Braking Compensatory Control Strategy Considering CVT Power Loss for Hybrid Electric Vehicles

Energies ◽  
2018 ◽  
Vol 11 (3) ◽  
pp. 497 ◽  
Author(s):  
Yang Yang ◽  
Xiaolong He ◽  
Yi Zhang ◽  
Datong Qin
2014 ◽  
Vol 926-930 ◽  
pp. 743-746 ◽  
Author(s):  
Jing Ming Zhang ◽  
Jin Long Liu ◽  
Ming Zhi Xue

The introduction of driving motors brings in the function of regenerative braking for Hybrid Electric Vehicles (HEV). In order to study the further information of regenerative braking, the relation between the degree of mixing in HEV and the recovery rate of regenerative braking was analyzed. The study object was the front-wheel driving HEV with the wire-control composite regenerative braking control strategy. Conclusions were deduced through the theoretical derivation. The braking model was established on the platform in MATLAB/SIMULINK and it was simulated within a HEV. The results indicate that the recovery rate would increase if the degree of mixing rises.


2014 ◽  
Vol 945-949 ◽  
pp. 1587-1596
Author(s):  
Xian Zhi Tang ◽  
Shu Jun Yang ◽  
Huai Cheng Xia

The driving style comprehensive identification method based on the entropy theory is presented. The error and error proportion of each identification result are calculated. The entropy and the variation degree of the identification error of each identification method are calculated based on the definition of information entropy. According to the entropy and the variation degree of the identification error, the weight of each kind of identification method can be determined in the comprehensive identification method, and the driving style comprehensive identification algorithm is derived. The control strategy of hybrid electric vehicles based on the driving style identification is proposed. The economic control strategy and dynamic control strategy are established. Depending on the results of driving style identification, aiming at different kinds of drivers, the mode of control strategies can be adjusted, so the demands of different kinds of drivers can be satisfied. The hybrid electric vehicle simulation model and control strategy model are built, and the simulations have been done. Due to the simulation results, the drivers’ intention comprehensive identification method based on the entropy theory is proved to represent the driver’s driving style systematically and comprehensively, and the hybrid electric vehicle control strategy based on the driving style identification can make the vehicles satisfy different drivers’ demands.


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