IMPROVED STATE OF CHARGE BALANCING SYSTEM PERFORMANCE IN PACK-TO-CELL TOPOLOGY BASED ON FUZZY LOGIC

• Main Author: Reztin Widayaksa, Adhita
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/56835
• Institution: Institut Teknologi Bandung

As the use of electric vehicles develops, energy storage systems also continue to increase on a large scale. Lithium-Ion batteries are the most popular energy storage systems. In EV application, this energy storage system contains a collection of batteries arranged in series and parallel to reach power requirements. However, due to the varying parameters of each battery cell, it results in an imbalance. This study using a pack to cell balancing topology with Fuzzy Logic to overcome the problem in the characteristic curve of lithium-ion batteries with a balancing strategy which is a combination of a voltage-based balancer (PBT) and a state of charge(SoC)-based balancer (PBS) to take advantage of each of the advantages. of the two balancing strategies The study consists of several simulation stages developed in Simulink 2018a software and using actual battery data, i.e., Lithium NMC 18650 cell types with an average nominal capacity of 3000 mAh. Simulations carried out on 20 battery cells arranged in series with the determination of the SoC is divided into three regions, the Low SoC area (0% -20%), Middle SoC area (21% -80%), and High SoC area (81% - 100%). Then from each region determined the initial SoC variation for the 20 battery cells with a different standard deviation of the initial cell maximum SoC are the same. The topology used in this study is pack to cell because of the number of switches and the complexity of the circuit that is simple. The test is carried out on the fill and discharge cycles for PBT, PBS, and Fuzzy Logic until the imbalance reaches a maximum SoC difference of 2%. Based on the research results, Fuzzy Logic-based balancing with a combination of voltage and SoC balancing strategy is superior to conventional balancing strategies, with balancing time being faster than conventional strategies, which is 3.102 seconds faster than PBT and 3.048 seconds compared to PBS. In the middle area, Fuzzy Logic is 3.226 seconds faster than PBT and 3.172 seconds compared to PBS. Then in high areas, Fuzzy Logic is 8.981 seconds faster than PBT and 5.189 seconds compared to PBS. The number of switches is less than conventional balancing strategies, 93% less in the low area, 89% less in the middle area, and 83% less in the high area when compared to conventional balancing. The use of Fuzzy Logic can also increase the switch life by about 12,5 times in the low area, 8 times in the middle area, and 5 times in the high area compared to PBT and PBS. The number of switching will affect the performance of the switch, too many switching transitions will impact the energy losses. The minimum number of switches can increase the efficiency of the balancing system. Thus, Fuzzy Logic can be used as a control to improve the performance of the active balancer with a pack to cell topology in a large number of cells. ?