The convergence principle of equivalence factor searching for the adaptive-ECMS is modified and its oscillation is solved. A radial basis function neural network based velocity predictor is constructed, its accuracy and sensitivity is studied. The developed velocity predictor is incorporated with the adaptive-ECMS to improve the fuel economy by comparison study. The fuel consumption is decreased by over 3% compared with traditional adaptive-ECMS when no velocity forecast is employed.