Bibliographic Details
| Title: |
Off-Line Optimization Based Active Control of Torsional Oscillation for Electric Vehicle Drivetrain. |
| Authors: |
Cheng Lin, Shengxiong Sun, Paul Walker, Nong Zhang |
| Source: |
Applied Sciences (2076-3417); Dec2017, Vol. 7 Issue 12, p1261, 18p |
| Subject Terms: |
AUTOMATIC control of electric drives, GENETIC algorithms |
| Abstract: |
As there is no clutch or hydraulic torque converter in electric vehicles to buffer and absorb torsional vibrations. Oscillation will occur in electric vehicle drivetrains when drivers tip in/out or are shifting. In order to improve vehicle response to transients, reduce vehicle jerk and reduce wear of drivetrain parts, torque step changes should be avoided. This article mainly focuses on drivetrain oscillations caused by torque interruption for shifting in a Motor-Transmission Integrated System. It takes advantage of the motor responsiveness, an optimal active control method is presented to reduce oscillations by adjusting motor torque output dynamically. A rear-wheel-drive electric vehicle with a two gear automated manual transmission is considered to set up dynamic differential equations based on Newton's law of motion. By linearization of the affine system, a joint genetic algorithm and linear quadratic regulator method is applied to calculate the real optimal motor torque. In order to improve immediacy of the control system, time consuming optimization process of parameters is completed off-line. The active control system is tested in AMEsim® and limitation of motor external characteristics are considered. The results demonstrate that, compared with the open-loop system, the proposed algorithm can reduce motion oscillation to a satisfied extent when unloading torque for shifting. [ABSTRACT FROM AUTHOR] |
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| Database: |
Complementary Index |