Capacity Estimation of Lithium-ion Battery by GA-KF Method

Abstract

In this study, the capacity estimation of the lithium-ion battery was successfully proposed using the genetic algorithm-Kalman filter method. During the design phase of electrical devices, lithium-based batteries have begun to be preferred instead of wired electricity transmission due to flexibility, freedom of movement, and portability problems. In addition, from an environmental perspective, the use of electric vehicles has become more important than the use of internal combustion engine vehicles. In this study, the capacity estimation of the 18650 lithium-ion battery, which is the most preferred in electric vehicles, was made quickly and accurately. The performances of the Standard Kalman Filter and the Kalman Filter, whose parameters are determined by the Genetic Algorithm, were compared by estimating the battery capacity. By giving the results obtained by the Genetic Algorithm during the parameter search process, the most appropriate values and the important parameters of the Kalman Filter have been determined. The success of the proposed method is given by the experimental results. In the performance comparison, the success of the proposed method is given using RMSE, MSE, and R2 metrics. When the average of all experiments was calculated using the R2 metric, the Genetic Algorithm-Kalman Filter approach achieved the best results in estimating the capacity of the 18650 lithium-ion battery, with a value of 0.999874.

Keywords

• Lithium-ion Battery
• Genetic Algoithm
• Kalman Filter
• Capacity Estimation
• Electric Vehicle

GA-KF Yöntemiyle Lityum-iyon Bataryanın Kapasite Tahmini

Abstract

Bu çalışmada Lityum iyon bataryanın kapasite tahmini genetik algoritma-kalman filtre yöntemiyle başarılı bir şekilde yapılarak önerilmiştir. Elektrikli cihazların tasarım aşamasında esneklik, hareket özgürlüğü ve taşınabilirlik sorunlarından ötürü elektriği kablolu aktarım yerine lityum tabanlı bataryalar tercih edilmeye başlanmıştır. Ayrıca çevresel açıdan içten yanmalı motorlu araçların kullanımında ziyade elektrikli araçların kullanımı önem kazanmıştır. Bu çalışmada elektrikli araçlarda en çok tercih edilen18650 lityum iyon bataryanın kapasite tahmini hızlı, sağlıklı bir şekilde yapılmıştır. Standart Kalman Filtre ve parametrelerinin Genetik Algoritma tarafından belirlendiği Kalman Filtre ile batarya kapasite tahmini yaparak performansları karşılaştırılmıştır. Genetik algoritmanın parametre arama sürecinde elde ettiği sonuçlar verilerek en uygun değerler ile Kalman Filtrenin önemli parametrelerinin belirlenmiştir. Önerilen yöntemin başarısı deney sonuçlarıyla verilmiştir. Performans karşılaştırmasında RMSE, MSE, R2 metrikleri kullanılarak önerilen yöntemin başarısı verilmiştir. Tüm deneylerin ortalaması R2 metriği kullanılarak hesaplandığında, 18650 Lityum-iyon bataryanın kapasitesini tahmin etmede en iyi sonucu 0.999874 değeriyle Genetik Algoritma-Kalman Filtresi yaklaşımı elde etmiştir.

Keywords

• Lityum-iyon Batarya
• Genetik Algoritma
• Kalman Filtre
• Kapasite Tahmini
• Elektrikli Araç

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