Paper Title
Optimal Energy Efficiency and Swapping Maps for Minimizing Energy Consumption Per Distance of Electric Two-Wheelers

Abstract
This paper presents an integrated approach to improve energy efficiency of electric two-wheeler (E2W) delivery services through optimal energy efficiency maps and battery swapping maps. As E2W adoption expands in urban delivery services, efficient energy management becomes critical for operational sustainability. We develop a mathematical model using Lotka-Volterra equations to analyze the dynamic interaction between E2Ws and Battery Swapping Stations (BSS). Based on actual delivery rider data covering over 20,000 km in Seoul Gangnam area, we construct an empirical model using a 5×5 grid space with Manhattan distance-based routing. Comparative analysis of Nearest Neighbor (NN) and Breadth-First Search (BFS) algorithms reveals that BFS achieves 14.29% energy savings compared to NN. Among 120 possible routes for 5 delivery points, the optimal route demonstrates 52% energy reduction compared to the worst route. Furthermore, we develop a State-of-Charge (SoC)-based dynamic route planning algorithm for optimal battery swapping strategy, achieving 81.2% effective distance ratio. The proposed framework provides practical energy management solutions applicable to real-world E2W delivery operations. Keywords - Electric Two-Wheeler, Energy Efficiency Map, Battery Swapping Station, Lotka-Volterra Model, Route Optimization, BFS Algorithm