Rancang Bangun Sistem Balancing Empat Sel Baterai Lithium-Ion Berbasis Selective Charge Balancing dan Polynomial Regression - Ridho Sani; Denny Irawan (Journal of Electrical Vocational Education and Technology, 2026)
Abstrak Penelitian ini membahas rancang bangun sistem balancing empat sel baterai lithium-ion berbasis selective charge balancing dan polynomial regression. Permasalahan ketidakseimbangan tegangan antarsel pada baterai multi-sel dapat menurunkan performa, efisiensi, serta mempercepat degradasi baterai. Sistem dirancang menggunakan mikrokontroler ESP32, modul charging individual TP5100, sensor INA219, relay, serta rangkaian corrective discharge balancing. Metode utama balancing dilakukan dengan pengisian selektif pada masing-masing sel hingga mencapai tegangan 4,0 V, kemudian dilanjutkan dengan tahap rest verification selama 30 menit untuk memperoleh kondisi tegangan yang lebih stabil. Apabila masih terdapat selisih tegangan pada rentang tertentu, sistem akan mengaktifkan corrective pulse discharge balancing atau selective recharge balancing. Selain itu, metode polynomial regression digunakan untuk merepresentasikan hubungan nonlinier antara kapasitas muatan (mAh) dan Open Circuit Voltage (OCV) baterai lithium-ion. Hasil pengujian menunjukkan bahwa sistem mampu menurunkan selisih tegangan antarsel hingga mendekati batas toleransi balancing serta menghasilkan representasi karakteristik SOC–OCV yang sesuai dengan perilaku baterai selama proses charging berlangsung. Abstract This research discusses the design and implementation of a four-cell lithium-ion battery balancing system based on selective charge balancing and polynomial regression. Voltage imbalance between cells in multi-cell battery systems can reduce performance, efficiency, and battery lifespan. The proposed system was developed using an ESP32 microcontroller, TP5100 individual charging modules, INA219 sensors, relays, and a corrective discharge balancing circuit. The main balancing method was carried out through selective charging on each cell until reaching a balancing voltage of 4.0 V, followed by a 30-minute rest verification stage to obtain more stable voltage conditions. If voltage differences still existed within a certain range, the system activated corrective pulse discharge balancing or selective recharge balancing. In addition, the polynomial regression method was used to represent the nonlinear relationship between charge capacity (mAh) and the battery’s Open Circuit Voltage (OCV). The experimental results showed that the system was able to reduce voltage differences between cells close to the balancing tolerance limit and successfully represent the SOC–OCV characteristics according to lithium-ion battery behavior during the charging process.