Submitted:
23 February 2025
Posted:
24 February 2025
You are already at the latest version
Abstract
Technology for EV's and HEV's has become a viable way to reduce reliance on fossil fuels and carbon emissions. The architecture of EV systems is examined in this paper, with a focus on energy distribution, battery integration and power-train variants. Lithium-ion, solid-state and new energy storage technologies as well as their management systems to maximize lifetime and performance are a major area of attention. This study also explores optimization methodologies, control strategies and State of Charge (SoC) estimation methods to improve vehicle performance and energy economy. The use of many filtering techniques, including Kalman filters, particle filters and adaptive filtering methods in EV applications is examined in relation to noise reduction, parameter estimation and vehicle system stability. The aim of this paper is to integrate modern control and optimization techniques in order to help improve EV efficiency, dependability, reliability and sustainability in general.
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© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
