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- W4386899183 abstract "The modelling and control of electric vehicles is a field of research that is essential for optimizing the performance, safety, and reliability of EVs. This field is expected to grow in importance as EVs become more popular and new technologies are developed to improve their performance and reduce their environmental impact. Thus this paper works on modelling and control of electric vehicle drive systems using a unified approach applying a novel version of gorilla troop optimizer, namely a chaotic form of GTO, coined as ChGTO. Several one-dimensional chaotic maps are used to alter two controlling parameters and the position update rule in the parent algorithm. The worth of the developed approach is assessed through two different types of high-dimensional benchmark test functions. Moreover, the suggested technique is also utilized to reduce higher-dimensional electric motor and drive models in a combined framework. The respective controllers are also implemented with the help of model matching technique. The results of all the experiments conducted show great promise." @default.
- W4386899183 created "2023-09-21" @default.
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- W4386899183 date "2023-08-09" @default.
- W4386899183 modified "2023-10-02" @default.
- W4386899183 title "Modelling and control of electric vehicle motors and drives in a unified framework" @default.
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- W4386899183 doi "https://doi.org/10.1109/sefet57834.2023.10245153" @default.
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