.png){kind=icon}
.png){kind=icon}
Return
Differential Evolution-Based Multiobjective Optimization of the Electrical Continuously Variable Transmission System
.png){kind=icon}
PRE
AI
DOI：10.1109/TIE.2017.2733458.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
With the increasing popularity of hybrid electric vehicles (HEVs), the demands of improving the fuel economy and energy efficiency of HEVs are enlarged. The technology electrical continuously variable transmission (E-CVT) system provides the opportunity to fulfill this requirement. However, conventional E-CVT with planetary gears suffer from frictional loss, high maintenance, and audible noise. Therefore, a series of gearless E-CVT propulsion systems are developed. Thereinto, a doubl-rotor single-stator brushless E-CVT having high torque density, reduced stator end winding length, and reduced copper loss was recently proposed. However, only torque of the E-CVT system is optimized by the genetic algorithm in the previous study. This paper adopts a differential evolution algorithm coupled with finite element method to optimize torque, energy efficiency, torque ripples, and multiobjective of the E-CVT system by reconfiguring the height of rotors, the areas of slots, and the height of yoke. It is simulated that by only tuning the weighting factors, the permanent magnetic machine in the E-CVT system can operate in the highest torque mode, highest energy efficiency mode, lowest torque ripples mode, and multiobjective optimization mode.
Keywords:
Different evolution (DE)
electrical continuously variable transmission (E-CVT)
energy efficiency
finite element method (FEM)
hybrid electric vehicles (HEVs)
multiobjective optimization
torque
torque ripples
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.2
Papers:
1.8W
Citations:
9.8W