Chimp optimization‐based fuzzy controller for hybrid electric vehicle speed control using electronic throttle plate.
Saved in:
| Title: | Chimp optimization‐based fuzzy controller for hybrid electric vehicle speed control using electronic throttle plate. |
|---|---|
| Authors: | Tripathi, Sandeep1 (AUTHOR), Shrivastava, Ashish2 (AUTHOR) rewa.ashish@gmail.com, Jana, Kartick C.1 (AUTHOR) |
| Source: | Optimal Control - Applications & Methods. Jan2024, Vol. 45 Issue 1, p163-184. 22p. |
| Subjects: | Electric controllers, Electronic control, Hybrid electric vehicles, Chimpanzees, Internal combustion engines, Heuristic algorithms |
| Abstract: | Today's concern about climate change and the country's economic growth have made adopting hybrid electric vehicles (HEV) a worthy solution. Since the gas emissions of HEVs are closely related to their motor performance, developing an effective HEV motor control technique is essential. The performance and acceleration of an HEV motor are determined by the internal combustion engine (ICE) and the electronic throttle plate (ETP), which employ an air‐fuel mixture for vehicle propulsion. In order to deal with this problem, this article presented an optimal fuzzy controller that controls the throttle plate's angular position and motor speed in HEVs. However, the efficiency and reliability of fuzzy controllers depend upon their gains factor. So, a different heuristic algorithm is employed to self‐tuning the fuzzy logic controller (FLC) gain factor. The performance of the suggested ChOA‐fuzzy‐based controller was evaluated utilizing various control error indices and time‐domain stability. A comprehensive controller performance analysis using different metaheuristic techniques has been carried out to validate the proposed scheme. The findings show that the suggested ChOA‐fuzzy‐based controller performs better than other techniques. [ABSTRACT FROM AUTHOR] |
| Copyright of Optimal Control - Applications & Methods is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | Today's concern about climate change and the country's economic growth have made adopting hybrid electric vehicles (HEV) a worthy solution. Since the gas emissions of HEVs are closely related to their motor performance, developing an effective HEV motor control technique is essential. The performance and acceleration of an HEV motor are determined by the internal combustion engine (ICE) and the electronic throttle plate (ETP), which employ an air‐fuel mixture for vehicle propulsion. In order to deal with this problem, this article presented an optimal fuzzy controller that controls the throttle plate's angular position and motor speed in HEVs. However, the efficiency and reliability of fuzzy controllers depend upon their gains factor. So, a different heuristic algorithm is employed to self‐tuning the fuzzy logic controller (FLC) gain factor. The performance of the suggested ChOA‐fuzzy‐based controller was evaluated utilizing various control error indices and time‐domain stability. A comprehensive controller performance analysis using different metaheuristic techniques has been carried out to validate the proposed scheme. The findings show that the suggested ChOA‐fuzzy‐based controller performs better than other techniques. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 01432087 |
| DOI: | 10.1002/oca.3051 |
