This　paper　investigates　the　hypothesis　test　of　the　parametric　component　in　partial　functional　linear　regression　models.　Based　on　a　rank　score　function,　the　authors　develop　a　rank　test　using　functional　principal　component　analysis,　and　establish　the　asymptotic　properties　of　the　resulting　test　under　null　and　local　alternative　hypotheses.　A　simulation　study　shows　that　the　proposed　test　procedure　has　good　size　and　power　with　finite　sample　sizes.　The　authors　also　present　an　illustration　through　fitting　the　Berkeley　Growth　Data　and　testing　the　effect　of　gender　on　the　height　of　kids.