scholarly journals Design and Implementation of 1.8kW bi-directional LDC with Parallel Control Strategy for Mild Hybrid Electric Vehicles

2017 ◽  
Vol 22 (1) ◽  
pp. 75-81 ◽  
Author(s):  
Hyun-Bin Kim ◽  
Jea-Woong Jeong ◽  
Sungwoo Bae ◽  
Jong-Soo Kim
Keyword(s):  
Electric Vehicles ◽  
Control Strategy ◽  
Hybrid Electric Vehicles ◽  
Design And Implementation ◽  
Parallel Control ◽  
Hybrid Electric ◽  
Mild Hybrid

A Method for Battery Sizing in Parallel P4 Mild Hybrid Electric Vehicles

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Luca Castellazzi ◽  
Sanjarbek Ruzimov ◽  
Angelo Bonfitto ◽  
Andrea Tonoli ◽  
Nicola Amati
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Hybrid Electric ◽  
Mild Hybrid

Control Strategy of Hybrid Electric Vehicles Based on Driving Style Identification

2014 ◽  
Vol 945-949 ◽  
pp. 1587-1596
Author(s):  
Xian Zhi Tang ◽  
Shu Jun Yang ◽  
Huai Cheng Xia
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Entropy Theory ◽  
Driving Style ◽  
Identification Error ◽  
Identification Method ◽  
Hybrid Electric

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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