This　paper　addresses　a　secured　co-dynamic　model　for　the　energy　management　of　Electrical　Vehicles　(EVs)　within　the　real　community　transportation　system　(RCTS).　The　proposed　model　aims　to　facilitate　interoperability　among　mobile　energy　resources　within　the　smart　city,　enabling　the　RCTS　to　model　the　co-dynamic-static　transportation　systems　(TSs)　simultaneously.　The　energy　management　model　within　the　traffic　flow　system　focuses　on　dynamic　assignment,　considering　the　power　consumption　associated　with　the　density　of　moving　vehicles.　EVs　play　a　key　role　in　economically　managing　energy　in　both　static　and　dynamic　behaviors　within　charging　stations　while　aligning　with　the　current　traffic　flow.　To　enhance　data　security　within　the　smart　city　ecosystem,　a　directed　acyclic　graph　(DAG)-based　decentralized　cyber　security　approach　is　recommended.　This　approach　ensures　that　data　transactions　involving　mobile　energy　resources　are　secured　against　cyber-attacks　through　the　use　of　public,　private,　and　transaction　blocks.　Additionally,　an　uncertainty-based　copula　function　is　presented　to　create　a　precise　management　environment　within　the　smart　city.　The　results　indicate　that　the　proposed　model　for　transportation　energy　resources　tends　to　reduce　energy　costs　by　optimally　controlling　energy　consumption　within　traffic　flow,　compared　to　normal　conditions.