Cell Balancing Paradigms: Advanced Types, Algorithms, and Optimization Frameworks
Anupama R Itagi, Rakhee Kallimani, Krishna Pai, Sridhar Iyer, Onel L., A. L\'opez, and Sushant Mutagekar

TL;DR
This paper reviews various cell balancing schemes and algorithms for battery management systems, emphasizing optimization methods to improve battery performance, safety, and lifespan in electric transportation and energy storage applications.
Contribution
It provides a comprehensive survey of recent cell balancing algorithms and discusses optimization frameworks, offering selection guidelines and highlighting key parameters involved.
Findings
Survey of recent cell balancing algorithms
Guidelines for selecting appropriate balancing schemes
Discussion of optimization parameters and methods
Abstract
The operation efficiency of the electric transportation, energy storage, and grids mainly depends on the fundamental characteristics of the employed batteries. Fundamental variables like voltage, current, temperature, and estimated parameters, like the State of Charge (SoC) of the battery pack, influence the functionality of the system. This motivates the implementation of a Battery Management System (BMS), critical for managing and maintaining the health, safety, and performance of a battery pack. This is ensured by measuring parameters like temperature, cell voltage, and pack current. It also involves monitoring insulation levels and fire hazards, while assessing the prevailing useful life of the batteries and estimating the SoC and State of Health (SoH). Additionally, the system manages and controls key activities like cell balancing and charge/discharge processes. Thus functioning…
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Taxonomy
TopicsAssembly Line Balancing Optimization · Modular Robots and Swarm Intelligence · Scheduling and Optimization Algorithms
