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Traditional diesel-based airport service vehicles are characterized by aheavy-duty, high-usage-frequency nature and a high carbon intensity per vehicleper hour. Transforming these vehicles into electric vehicles would reduce CO2emissions and potentially save energy costs in the context of rising fuelprices, if a proper energy management of airport service electric vehicles(ASEVs) is performed. To perform such an energy management, this paper proposesa new customized rollout approach, as a near-optimal control method for a newASEV dynamics model, which models the ASEV states, their transitions over time,and how control decisions affect them. The rollout approach yields anear-optimal control strategy for the ASEVs to transport luggage and to chargebatteries, with the objective to minimize the operation cost, whichincentivizes the charging of the ASEVs to match renewable generation. Casestudies demonstrate that the rollout approach effectively overcomes the "curseof dimensionality". On both typical summer and winter days, the rolloutalgorithm results in a total cost approximately 10% less than that of theunderlying "greedy charging" heuristic, which charges a battery whenever itsstate of charge is not the maximum. The rollout algorithm is proven to beadaptive towards flight schedule changes at short notice.

Energy Management of Airport Service Electric Vehicles to Match Renewable Generation through Rollout Approach