Abstract
With the rapid increase in the development of electric vehicles (EVs), a priority-based power delivery system for EV charging (EVC) has become a significant necessity. This helps in prioritizing the loads with distributed generation systems connected with the grid and prevents negative impacts such as overloading on the power grid. In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) based methodology for priority determination of electric vehicles’ charging is developed considering the battery’s state of charge (SOC), time of stay, distance to be travelled and battery capacity. The proposed approach aims at enhancing the power delivering capability of the utility and overcome the drawback of unbalanced loading while performing EVC. To assess the performance of the proposed approach, the control and simulation of a grid connected EVC is done using 3 level converters. The results depict a smooth ripple free DC voltage which charges the vehicle with the highest priority.
| Original language | English |
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| Title of host publication | European, Asian, Middle Eastern, North African Conference on Management & Information Systems |
| DOIs | |
| Publication status | Published - 2021 |
| Externally published | Yes |
Keywords
- Electric vehicle charging
- Adaptive neuro fuzzy inference system
- Voltage oriented control
- Charging prioritization
- Battery state of charge