Scientific Reports (Aug 2024)

A novel development of advanced control approach for battery-fed electric vehicle systems

  • K. M. Bhargavi,
  • P. Ashwini Kumari,
  • C. H. Hussain Basha,
  • S. Girija Kanaka Jothi,
  • V. Prashanth,
  • Nayana Shetty

DOI
https://doi.org/10.1038/s41598-024-71167-y
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 14

Abstract

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Abstract In today’s context, there is a clear preference for DC microgrids over AC microgrids due to their better compatibility with generating sources, loads, and battery energy storage systems (BESS). However, the intermittent nature of renewable resources disrupts the balance between power generation and load demand. It raises concerns regarding power management and quality in the power system. Control strategies are essential to address these challenges. This article focuses on developing a novel control strategy to ensure stability in microgrid systems. The proposed control structure utilizes a second-order multi-agent system (MAS) to enhance the power-sharing and coordination in the microgrid network. For effective control of battery energy storage units, a Voltage–Power (V-P) reference-based droop control and leader–follower consensus method is employed. The control approach consists of primary and secondary control layers. The primary layer uses a V-P reference-based droop control strategy to allocate load components to storage units. The secondary control layer aims to restore DC bus voltage using a MAS-based consensus protocol. The MAS approach offers greater flexibility and requires less computational power than other strategies such as Model Predictive Control (MPC). The enhanced control structure incorporates a current ratio modification loop to adjust the current ratio between the converters, thereby modifying gain and improving the voltage profile. This novel control optimizes the reliability and stability of the proposed DC microgrid system. The effectiveness of the enhanced consensus-based secondary control strategy is demonstrated using the MATLAB/Simulink platform.

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