Due　to　the　poor　dynamic　response　ability　of　the　fuel　cell,　the　battery　is　normally　applied　to　integrate　with　fuel　cell　to　configure　the　hybrid　power　system　in　electric　vehicles.　In　this　paper,　a　vehicle　speed　prediction　model　predictive　control　(SP-MPC)　energy　management　strategy　is　developed　for　the　hybrid　power　system　in　fuel　cell　electric　vehicles.　The　main　principle　of　the　proposed　SP-MPC　is　that　the　future　vehicle　total　power　demand　is　forecasted　via　the　Markov　speed　predictor　and　imported　into　the　energy　management　system　response　prediction　model　to　improve　the　control　performance　by　more　accurate　disturbance　description.　The　objective　function　is　set　for　equivalent　hydrogen　consumption　minimization　and　fuel　cell　degradation　inhibition.　As　a　contrast,　the　normal　MPC　strategy,　the　speed　prediction　dynamic　programming　(SP-DP)　strategy　and　the　DP　offline　strategy　are　formulated.　Comparing　with　the　normal　MPC　strategy,　the　SP-MPC　strategy　has　a　3.74%　reduction　in　the　total　operation　cost　under　MANHATTAN　condition.　The　SP-MPC　strategy　also　has　a　1.39%　reduction　in　the　total　operation　cost　than　the　SP-DP　strategy.　Moreover,　two　scenarios　are　introduced　with　different　disturbance　prediction　accuracy　to　verify　the　influences　of　the　prediction　inaccuracy　on　the　SP-MPC　and　SP-DP　results.　For　SP-DP　strategy,　the　total　operation　cost　under　actual　forecast　scenario　has　increased　by　5.03%　compared　with　the　perfect　forecast　scenario.　The　similar　result　can　be　seen　in　the　SP-MPC,　but　the　increase　between　perfect　and　actual　forecast　scenario　is　only　1.02%,　which　indicates　a　better　robustness　to　the　disturbance　prediction　inaccuracy　compared　with　the　SP-DP　strategy.　A　DSP　hardware　in　loop　(HIL)　test　is　conducted　for　real-time　performance　verification　of　the　proposed　SP-MPC.　©　2021　Elsevier　Ltd