Plug-in　hybrid　electric　vehicles　(PHEVs)　with　fuel　and　electricity　have　demonstrated　the　capability　to　reduce　fuel　consumption　and　emissions　by　adopting　appropriate　energy　management　strategies.　In　the　existing　energy　management　strategies,　the　dynamic　programming　(DP)-based　energy　management　strategy　(EMS)　can　realize　the　global　optimization　of　the　fuel　consumption　if　the　global　vehicle-speed　trajectory　is　known　in　advance.　The　global　vehicle-speed　trajectory　can　be　obtained　by　applying　GPS　data　of　vehicles　when　the　trip　path　is　determined.　However,　for　a　trip　path　without　GPS　data,　the　global　vehicle-speed　trajectory　is　difficult　to　be　gained.　In　this　case,　the　DP-based　EMS　cannot　be　utilized　to　achieve　the　globally　optimal　fuel　consumption,　which　is　the　issue　discussed　in　this　paper.　This　paper　makes　the　following　two　contributions　to　solve　this　issue.　First　of　all,　the　cell　transmission　model　of　the　road　traffic　flow　and　the　vehicle　kinematics　are　introduced　to　obtain　the　traffic　speeds　of　road　segments　and　the　accelerations　of　the　PHEV.　On　this　basis,　a　hybrid　trip　model　is　presented　to　obtain　the　vehicle-speed　trajectory　for　the　trip　path　without　GPS　data.　Next,　a　DP-based　EMS　with　prediction　horizon　is　proposed,　and　moreover,　in　order　to　improve　its　real-time　implementation,　a　search　range　optimization　algorithm　of　the　state　of　charge　(SOC)　is　designed　to　reduce　the　computational　load　of　DP.　In　summary,　we　propose　a　computation-optimized　DP-based　EMS　through　applying　the　hybrid　tripmodel.　Finally,　a　simulation　study　is　conducted　for　applying　the　proposed　EMS　to　a　practical　trip　path　in　Beijing　road　network.　The　results　show　that　the　hybrid　trip　model　can　effectively　construct　the　vehicle-speed　trajectory　online,　and　the　average　accuracy　of　the　vehicle-speed　trajectory　is　more　than　78%.　In　addition,　compared　with　the　existing　optimization　algorithm　for　DP　calculation,　the　SOC　search　range　optimization　algorithm　can　further　reduce　the　calculation　load　of　DP.　More　importantly,　compared　to　the　globally　optimal　DP-based　EMS,　although　the　proposed　EMS　makes　the　fuel　consumption　grow　less　than　5.36%,　it　can　be　implemented　in　real　time.　Moreover,　compared　with　the　existing　real-time　strategies,　it　can　further　reduce　the　fuel　consumption　and　emissions.　Thus,　the　proposed　EMS　can　offer　an　effective　solution　for　the　PHEV　applying　it　online　in　the　trip　path　without　GPS　data.