July 2020 - Electrification and autonomous driving are two important trends in transportation systems. The convergence of these two technologies will introduce opportunities to improve transportation systems' operation and energy efficiency. One potential application is the commercial ride-hailing fleet with autonomous electric vehicles (AEVs). In order to harvest promising benefits from introducing AEVs into ride-hailing fleets, some unavoidable challenges will need to be resolved to ensure the fleets operates functionally and efficiently. This paper discusses the challenges of dispatching AEVs and their interactions with charging infrastructure. An integrated decision making framework for dispatching and charging has been designed using a system optimization approach to study the AEVs' management within the period when they drop off passengers and pick up the next passengers. Its potential fleet-wide benefits have been illustrated by comparing operations under a heuristic approach. A simulation platform has been designed to test different decision making strategies for the ride-hailing AEV fleets operational performance. Using this platform, detailed case studies have been performed with different fleet sizes, dispatching strategies, and charging infrastructure network settings. Comprehensive analyses from various aspects have been conducted to understand the AEVs' fleet operation performance, (e.g., zero occupancy vehicle miles traveled, successfully served ratio of ride-hailing requests, fleet vehicle charging downtime, and charging infrastructure utilization). Results have provided a deep understandings on operation's dynamics under various fleet system configurations and also have demonstrated advantages of the optimization-based approach for the AEV fleet management. Studies in this paper inform better designs on the future of sophisticated management strategies and charging infrastructure to support ride-hailing AEV fleet operation.