Genetic Algorithms optimized Multi-objective Controller for an Induction Machine based Electrified Powertrain

被引：0
|
作者：
Hanif, A. [1 ]
Ahmed, Q. [2 ]
Bhatti, A. I. [2 ]
Rizzoni, G. [2 ]
机构：
[1] COMSATS Inst Informat Technol, Lahore, Pakistan
[2] OSU, CAR, Columbus, OH 43210 USA
来源：
2017 IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (CCTA 2017) | 2017年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In electrified powertrain control, meeting the torque demands and ensuring efficient Electrical Machine (EM) operations are two essential but conflicting demands. A multi-objective Linear Parameters Varying (LPV) controller is proposed to address the problem of these conflicting objectives. The synthesis of multi-objective controller is based on the selection of optimal weighting functions optimized by Genetic Algorithm (GA). The effectiveness of the proposed controller is tested and evaluated for an electrified powertrain operating in a standard urban driving cycles. The stability of the proposed Multi-Objective Controller (MOC) is established. The nonlinear simulation of the proposed controller delivers the robust performance and better efficiency of an EV Induction Machine (IM) based electric drive over the entire driving cycle.
引用
收藏
页码：853 / 858
页数：6
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