In　response　to　the　urgent　need　for　improving　distribution　network　resilience　under　frequent　extreme　natural　disasters,　a　dynamic　collaborative　recovery　strategy　incorporating　mobile　fuel　cell　vehicles　(MFCV)　is　proposed.　First,　an　emergency　response　collaborative　optimization　model　is　constructed.　At　the　topology　reconstruction　level,　network　dynamic　partitioning　is　achieved　through　remote　control　switches　(RCS),　coordinating　the　spatiotemporal　coupling　characteristics　of　preset　energy　storage　systems　and　MFCV.　At　the　resource　scheduling　level,　an　MFCV　dynamic　scheduling　model　considering　traffic　network　constraints　is　established,　introducing　hydrogen　replenishment　to　characterize　MFCV＇s　endurance　characteristics.　Second,　for　the　bilinear　non-convex　problem,　the　original　problem　is　transformed　into　mixed-integer　linear　programming　(MILP)　through　linearization　methods,　while　introducing　virtual　power　flow　constraints　to　ensure　network　radial　structure.　Finally,　comparative　experiments　based　on　the　improved　IEEE　33-node　distribution　system　and　coupled　traffic　network　demonstrate　that,　compared　to　traditional　post-disaster　MFCV　scheduling　schemes,　the　proposed　method　can　significantly　reduce　load　loss　and　improve　distribution　network　resilience　and　economics.