Experimental Evaluation of Cell Balancing Algorithms with Arduino Based Monitoring System

The trend toward more electric vehicles has demanded the need for high efficiency, high voltage and long life battery systems [1,_2]. Also renewable energy systems carry huge battery backups to overcome the renewable source shortage. Battery systems are affected by many factors, cells unbalancing is one of most important among these factors. Without the balancing system, individual cell voltages will differ over time that will decrease the battery pack capacity quickly. This condition is especially severe when the battery has a long string of cells and frequent regenerative charging is done via battery pack. Cell balancing is a method of designing safer battery solutions that extends battery runtime as well as battery life. Balancing mechanism can help in equalizing the state of charge across the multiple cells, therefore increasing the performance of battery system. Different cell balancing methodologies have been proposed for battery pack in recent years. These methods have some merits and demerits in comparison to each other; e.g. balancing time, complexity and active or passive balancing etc. In this paper, current bypass active cell balancing and Arduino based monitoring system designing and implementation is carried out. In charging process, this balancing technique provides partial current bypass using charging slope for weak cells. Also the passive shunt resistor technique is implemented to compare and verify the proposed system efficient response. Output result shows that this proposed balancing technique can perform cell balancing in much effective and efficient way as compared to previous balancing techniques. Using this cell balancing technique, we can improve overall battery health and lifetime.

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Maximizing Battery Life and Usable Capacity With Battery Management System in Electric Vehicles

Volume 9: 13th ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications ◽

10.1115/detc2017-67939 ◽

2017 ◽

Author(s):

Zoltán Szeli ◽

Gábor Szakállas ◽

Ferenc Szauter

Keyword(s):

Electric Vehicles ◽

Management System ◽

Active Cell ◽

Battery Pack ◽

Research Centre ◽

Battery Life ◽

Battery Management System ◽

Battery Management ◽

Cost Weight ◽

Cell Balancing

In terms of the electric vehicles is an important issue of sizing a battery pack. The designer must take account of parameters such as cost, weight and durability. We can optimize these parameters with the help of a battery management system with integrated active cell balancing function. The article describes the development of a battery management system that developed by the Research Centre of Vehicle Industry at Széchenyi István University, Győr, Hungary.

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Dimensioning and Optimization of Hybrid Li-Ion Battery Systems for EVs

World Electric Vehicle Journal ◽

10.3390/wevj9020019 ◽

2018 ◽

Vol 9 (2) ◽

pp. 19 ◽

Cited By ~ 8

Author(s):

Jan Becker ◽

Thomas Nemeth ◽

Raphael Wegmann ◽

Dirk Sauer

Keyword(s):

Fixed Ratio ◽

Lithium Ion ◽

Maximum Power ◽

Battery Pack ◽

Optimization Approach ◽

System Specification ◽

Control Logic ◽

Battery Cell ◽

Battery System ◽

Battery Systems

Commercial electric vehicles nowadays are powered by a battery system containing one kind of lithium-ion battery cell. Due to the fixed ratio of the cells’ maximum power to nominal energy, the possibilities for designing power and energy of the battery pack independently are limited. The battery system’s energy and maximum power can only be scaled by adapting the number of cells and modules, and the parameters furthermore depend on the characteristics of the cells used. Additional power electronics in the form of one or more dc/dc converters can be used to form a hybrid battery system comprised of more than one pack and different cell technologies. This allows for individually designing each battery pack and thus optimizing the overall battery system specification. This work presents a battery dimensioning and optimization approach for single pack and hybrid battery systems. It is based on an evolutionary optimization algorithm and a detailed, modular Matlab-Simulink vehicle model. Studies on the advantages of hybrid batteries for different vehicle classes were carried out. Results indicate that optimized hybrid battery systems can lead to weight and volume savings and further advantages in total cost of ownership, for example, by enhanced battery life time or reduced investment costs. On the other hand, they require more complex control logic, which is also discussed in this paper.

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Cell Replacement Strategies for Lithium Ion Battery Packs

Batteries ◽

10.3390/batteries6030039 ◽

2020 ◽

Vol 6 (3) ◽

pp. 39

Author(s):

Nenad G. Nenadic ◽

Thomas A. Trabold ◽

Michael G. Thurston

Keyword(s):

Lithium Ion Battery ◽

Early Life ◽

Coulombic Efficiency ◽

Single Cells ◽

Lithium Ion ◽

Battery Pack ◽

Battery Life ◽

Cell Replacement ◽

Battery Systems ◽

Battery Packs

The economic value of high-capacity battery systems, being used in a wide variety of automotive and energy storage applications, is strongly affected by the duration of their service lifetime. Because many battery systems now feature a very large number of individual cells, it is necessary to understand how cell-to-cell interactions can affect durability, and how to best replace poorly performing cells to extend the lifetime of the entire battery pack. This paper first examines the baseline results of aging individual cells, then aging of cells in a representative 3S3P battery pack, and compares them to the results of repaired packs. The baseline results indicate nearly the same rate of capacity fade for single cells and those aged in a pack; however, the capacity variation due to a few degrees changes in room temperature (≃±3 ∘ C) is significant (≃±1.5% of capacity of new cell) compared to the percent change of capacity over the battery life cycle in primary applications (≃20–30%). The cell replacement strategies investigation considers two scenarios: early life failure, where one cell in a pack fails prematurely, and building a pack from used cells for less demanding applications. Early life failure replacement found that, despite mismatches in impedance and capacity, a new cell can perform adequately within a pack of moderately aged cells. The second scenario for reuse of lithium ion battery packs examines the problem of assembling a pack for less-demanding applications from a set of aged cells, which exhibit more variation in capacity and impedance than their new counterparts. The cells used in the aging comparison part of the study were deeply discharged, recovered, assembled in a new pack, and cycled. We discuss the criteria for selecting the aged cells for building a secondary pack and compare the performance and coulombic efficiency of the secondary pack to the pack built from new cells and the repaired pack. The pack that employed aged cells performed well, but its efficiency was reduced.

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ADAPTIVE ALGORITHMS OF CONTROLLING THE SMART LI-ION BATTERY CONTROLLER

Issues of radio electronics ◽

10.21778/2218-5453-2018-5-104-110 ◽

2018 ◽

pp. 104-110

Author(s):

I. A. Borovoy ◽

O. V. Danishevskiy ◽

A. V. Parfenov

Keyword(s):

Power Supply ◽

Power Supply System ◽

Electric Energy ◽

Lithium Ion ◽

Control Device ◽

Control Algorithms ◽

Battery System ◽

Electronic Control Device ◽

Li Ion ◽

Cell Balancing

The article substantiates the necessity of organizing the control system of modern lithium-ion batteries. Passive and active methods of cell balancing are described. The method of increase of efficiency of modes of accumulation of electric energy by means of the special electronic control device (the intellectual controller) and its further use for power supply of the functional equipment is considered. The structure of the intelligent controller as a part of the autonomous power supply system with the description of its main functional units and purpose is presented. Practical results of application in the intellectual controller of original adaptive control algorithms defining modes of operation of lithium-ion drives depending on various environmental conditions are resulted. The results of the analysis obtained by the results of experimental operation of the battery system, reflecting the qualitative and quantitative advantages of the proposed method.

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Estimation of the Hot Swap Circulation Current of a Multiple Parallel Lithium Battery System with an Artificial Neural Network Model

Electronics ◽

10.3390/electronics10121448 ◽

2021 ◽

Vol 10 (12) ◽

pp. 1448

Author(s):

Nam-Gyu Lim ◽

Jae-Yeol Kim ◽

Seongjun Lee

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Lithium Battery ◽

Battery Pack ◽

Battery Management ◽

Ann Model ◽

Battery System ◽

Load Current ◽

Circulating Current ◽

Artificial Neural

Battery applications, such as electric vehicles, electric propulsion ships, and energy storage systems, are developing rapidly, and battery management issues are gaining attention. In this application field, a battery system with a high capacity and high power in which numerous battery cells are connected in series and parallel is used. Therefore, research on a battery management system (BMS) to which various algorithms are applied for efficient use and safe operation of batteries is being conducted. In general, maintenance/replacement of multi-series/multiple parallel battery systems is only possible when there is no load current, or the entire system is shut down. However, if the circulating current generated by the voltage difference between the newly added battery and the existing battery pack is less than the allowable current of the system, the new battery can be connected while the system is running, which is called hot swapping. The circulating current generated during the hot-swap operation is determined by the battery’s state of charge (SOC), the parallel configuration of the battery system, temperature, aging, operating point, and differences in the load current. Therefore, since there is a limit to formulating a circulating current that changes in size according to these various conditions, this paper presents a circulating current estimation method, using an artificial neural network (ANN). The ANN model for estimating the hot-swap circulating current is designed for a 1S4P lithium battery pack system, consisting of one series and four parallel cells. The circulating current of the ANN model proposed in this paper is experimentally verified to be able to estimate the actual value within a 6% error range.

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