Optimized Analytical Crone Controller for Electric Vehicle System
- DOI
- 10.2991/978-94-6463-252-1_71How to use a DOI?
- Keywords
- Robust Controller; Sensitivity; Complementary sensitivity function; electrical vehicle performance indices
- Abstract
The usage of Fractional Order (FO) controllers for an electrical vehicle system is examined in this research (EVS). The auxiliary batteries, controller, charging port, onboard charger, electric motor, power in veelectriction battery pack, DC-DC converter, transmission, and thermal cooling system are only a few of the components used by the Electrical Vehicle System (EVS). A FO control method is used to achieve system performance requirements, and the Fractional Order-PID controller parameters are adjusted by means of a Nelder-Mead optimization procedure. Numerical simulations demonstrate the viability of the suggested methods. The findings of the crone controller are compared with those of the fractional order (FO) and integer order (IO) controllers, and the relative strengths and shortcomings of the modeling are evaluated. This particular FOC has proved to be superior to traditional methods. Moreover, the analysis of the system cross-checked with crone controller.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - C. Srisailam AU - M. Manjula AU - K. Muralidhar Goud PY - 2023 DA - 2023/11/09 TI - Optimized Analytical Crone Controller for Electric Vehicle System BT - Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023) PB - Atlantis Press SP - 709 EP - 720 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-252-1_71 DO - 10.2991/978-94-6463-252-1_71 ID - Srisailam2023 ER -