| MS Seminar

Name of the Speaker: Ms. Sravya (EE22S031)
Guide: Prof. Arunkumar D Mahindrakar
Venue: ESB-210B (Conference Hall)
Date/Time: 26th March 2025 (Wednesday), 3:30 PM
Title: AIMD with Time Varying Resource, Saturation Constraints and its Application to EV Charging.

Abstract :

The Additive Increase Multiplicative Decrease (AIMD) algorithm is mainly used for congestion problems where a large number of agents or users share a commonly available resource. In most cases, a linear algorithm is considered and the available resource is a constant value. A nonlinear algorithm where the parameters are a function of the agents' share is highly useful in solving optimization problems. This study analyzes the nonlinear AIMD model where the available resource varies with time. In addition, the nonlinear AIMD model with time-varying resources under saturation constraints on the share of the agents is developed. In both these cases, it is shown that the equilibrium lies in an open ball of a certain radius around the equilibrium of the algorithm when the available resource is constant and bounds on the radius is provided. Additionally, a distributed optimization problem where the sum of the battery degradation costs of the EVs (Electric Vehicles) is solved using the AIMD algorithm. The study provides a mechanism to strategically adjust the Multiplicative Decrease factor of the algorithm to achieve the optimal charge rates for the EVs which minimizes the battery degradation costs.