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This study presents an innovative solution for powering electric vehicles,named Charging-as-a-Service (CaaS), that concerns the potential large-scaleadoption of light-duty electric vehicles (LDEV) in the Mobility-as-a-Service(MaaS) industry. Analogous to the MaaS, the core idea of the CaaS is todispatch service vehicles (SVs) that carry modular battery units (MBUs) toprovide LDEVs for mobility service with on-demand battery delivery. The CaaSsystem is expected to tackle major bottlenecks of a large-scale LDEV adoptionin the MaaS industry due to the lack of charging infrastructure and excesswaiting and charging time. A hybrid agent-based simulation model (HABM) isdeveloped to model the dynamics of the CaaS system with SV agents, and atrip-based stationary charging probability distribution is introduced tosimulate the generation of charging demand for LDEVs. Two dispatchingalgorithms are further developed to support the optimal operation of the CaaS.The model is validated by assuming electrifying all 13,000 yellow taxis in NewYork City (NYC) that follow the same daily trip patterns. Multiple scenariosare analyzed under various SV fleet sizes and dispatching strategies. Theresults suggest that optimal deployment of 250 SVs may serve the LDEV fleet inNYC with an average waiting time of 5 minutes, save the travel distance at over50 miles per minute, and gain considerable profits of up to $50 per minute.This study offers significant insights into the feasibility, serviceefficiency, and financial sustainability for deploying city-wide CaaS systemsto power the electric MaaS industry.

Charging-as-a-Service: On-demand battery delivery for light-duty electric vehicles for mobility service