Electric vehicle (EV) smart charging can effectively enhance the local power demand-supply balance and help improve the renewable power local utilization. Researchers have developed two categories of EV charging: (i) building/grid-to-vehicle, in which the EV can only be charged; and (ii) building/grid-to-vehicle-to-building/grid, in which the vehicles can be both charged and discharged. Until now, the impacts of intelligent charging of EV (such as form of charging and charging limits) on its battery degradation are rarely studied. In response to the dynamic power profiles of the building community, EVs can have complex charging/discharging profiles, which in turn affect its cycling degradation. With the concern of large battery degradation, being unaware of such effects could reduce the EV owners' willingness to join in the smart charging demand response. This study will fill in this knowledge gap by comprehensively investigate how different ways of EV smart charging and EV usage affects its battery degradation and demand response performances in the built environment. Parametric studies considering 65 scenarios combining various EV charging forms, EV charging limits and commuting distances is conducted using a case building community in Sweden. A particle swarm optimization based EV smart charging control is developed to optimize its charging process to minimize the buildings' grid interactions. The Rainflow Counting algorithm is used for evaluating the cycling degradation of EV battery in different charging scenarios. The comparison results recommend implementing smart EV charging with small charging limits, as it can significantly reduce peak energy exchanges (e.g., 9.3 %–13 %) but will not increase the battery degradation dramatically. The study results can support decision makers in selecting suitable EV charging and usage strategies.