Expanding electric vehicles lifetime in power electronic stage using an optimized fuzzy logic controller

被引:0
作者
Ponce, Pedro [1 ]
MacCleery, Brian [2 ]
Soriano, Luis A. [5 ]
Garcia, Manuel [3 ]
Levi, Victor [4 ]
Molina, Arturo [1 ]
机构
[1] Tecnol Monterrey, Escuela Ingn & Ciencias, Ave Eugenio Garza Sada 2501, Monterrey 64849, NL, Mexico
[2] Natl Instruments Mopac, C 2N H05, Austin, TX USA
[3] Inst Politecn Nacl, Escuela Super Ingn Mecan & Elect, Mexico City, DF, Mexico
[4] Univ Manchester, Ferranti Bldg C13Sackville St Manchester, Manchester M13 9PL, Lancs, England
[5] Univ Autonoma Chapingo, Dept Ingn Mecan Agr, Texcoco, Mexico
来源
INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM | 2022年 / 16卷 / 01期
关键词
Electric vehicle; Power electronics; Fuzzy controller; Metaheuristic optimization; DC; SIMULATION; MOTORS;
D O I
10.1007/s12008-021-00794-w
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Currently, electric vehicles can achieve high driving performance when they use brushless motors. Moreover, the demand for more electric vehicles pushes companies to improve their driving performance and improve the speed and torque response. However, the power electronics stages inside the vehicle must be studied during the vehicle's design and operation. Generally, when high driving performance is reached, the command signals for achieving this performance stressed the power electronics stage, so its lifetime could be decremented drastically. Thus, the power electronic stage has to be incorporated into the design of the speed controller and be optimized to expand its lifetime. This paper deals with the optimization process between the power electronic stage and the speed controller. As a result, the power electronics stage will expand its lifetime. Since there is not enough information about the lifetime of the power electronic stage into electric vehicles and how it is affected by the high driving performance conditions, this paper contributes to generating knowledge about its lifetime and how it could be improved. Besides, this work illustrates the implementation of a fuzzy logic speed controller optimized by particle swarm optimization using co-simulation. This controller is adapted according to the speed and lifetime requirements. A conventional PID controller is compared against the proposed controller to show the advantages of using co-simulation between Multisim and LabVIEW. As a result, the superior performance of the proposed controller is demonstrated when the temperature is controlled in electric vehicles, so the lifetime of the power electronics stage could be expanded. Also, this paper presents a novel approach using a metaheuristic optimization that runs online.
引用
收藏
页码:49 / 63
页数:15
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