Optimizing　battery　swapping　station　(BSS)　configuration　is　essential　to　enhance　BSS’s　energy　savings　and　economic　feasibility,　thereby　facilitating　energy　refueling　efficiency　of　electric　taxis　(ETs).　This　study　proposes　a　novel　modular　battery　swapping　mode　(BSM)　that　allows　ET　drivers　to　choose　the　number　of　battery　blocks　to　rent　according　to　their　driving　range　requirements　and　habits,　improving　BSS’s　economic　profitability　and　operational　flexibility.　We　further　develop　a　data-driven　approach　to　optimizing　the　configuration　of　modular　BSS　considering　the　scheduling　of　battery　charging　at　the　operating　stage　under　a　scenario　of　time-of-use　(ToU)　price.　We　use　the　travel　patterns　of　taxis　extracted　from　the　GPS　trajectory　data　on　12,643　actual　taxis　in　Beijing,　China.　Finally,　we　test　the　effectiveness　and　performance　of　our　data-driven　model　and　modular　BSM　in　a　numerical　experiment　with　traditional　BSM　as　the　benchmark.　Results　show　that　the　BSS　with　modular　BSM　can　save　38%　on　the　investment　cost　of　purchasing　ET　battery　blocks　and　is　better　able　to　respond　to　the　ToU　price　than　to　the　benchmark.　The　results　of　the　sensitivity　analysis　suggest　that　when　the　peak　electricity　price　is　too　high,　additional　battery　blocks　must　be　purchased　to　avoid　charging　during　those　peak　periods.　©　2023　by　the　authors.