An Uncertainty-Aware Joint Sizing and Queue-Constrained Scheduling Framework for Solar-Assisted Electric Three-Wheeler Battery-Swapping Stations: A Field-Informed Dhaka Case Study

This paper proposes an uncertainty-aware joint sizing and queue-constrained scheduling framework for solar-assisted electric three-wheeler battery-swapping stations. The study integrates photovoltaic capacity, charger number, grid capacity, and battery inventory optimization with realistic operational constraints, including finite READY battery availability, FCFS queueing, uncertain vehicle arrivals, battery SOC variation, and solar variability. A field-informed Dhaka case study and discrete-event Monte Carlo simulation framework are developed to evaluate reliability, energy performance, and economic trade-offs. The proposed approach provides a practical planning methodology for designing resilient and cost-effective E3W battery-swapping infrastructure in emerging urban mobility systems.