A Novel Electric Vehicle Battery Management System Using an Artificial Neural Network-Based Adaptive Droop Control Theory
نویسندگان
چکیده
The novelty of this research lies in the development a new battery management system (BMS) for electric vehicles, which utilizes an artificial neural network (ANN) and fuzzy logic-based adaptive droop control theory. This innovative approach offers several advantages over traditional BMS systems, such as decentralized architecture, communication-free capability, improved reliability. proposed incorporates virtual admittance, adjusts value admittance based on current state charge (SOC) each cell. allows connected cells to share load evenly during charging discharging, improves overall performance efficiency vehicle. effectiveness structure was verified through simulation experimental prototype testing with three linked cells. small signal model demonstrated stability control, while results confirmed system’s ability distribute among discharging. We introduce unique cars paper. Our suggested implemented tested satisfactorily 100 kWh lithium-ion pack. When compared typical show surprising 15% increase energy efficiency. Furthermore, admission function resulted 20% boost life. These large gains longevity demonstrate our BMS’s efficacy superiority competing systems. Overall, represents significant innovation field vehicle management. combination ANN theory logic provides highly efficient, reliable, economical solution EV cell
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ژورنال
عنوان ژورنال: International Journal of Energy Research
سال: 2023
ISSN: ['0363-907X', '1099-114X']
DOI: https://doi.org/10.1155/2023/2581729