Economic velocity planning in cruise scenario was studied for the power-split hybrid electric vehicle aiming at minimizing the fuel consumption. A reinforced equivalent consumption minimization strategy (R-ECMS) was proposed based on kinetic energy management and equivalent consumption minimization strategy (ECMS). The equivalent coefficient between fuel and electric energy was derived using minimum principle. Meanwhile, the equivalent relationship between kinetic energy and electric energy was established. The vehicle kinetic change and electric consumption were unified into fuel consumption, combined with the equivalent relationship between fuel and electric energy. The non-dominated sorting genetic algorithm was adopted to optimize the parameters in the weight coefficients of the proposed strategy, to ensure battery SOC balance and meet vehicle travel time at the same time. Simulation results demonstrate that R-ECMS can reduce fuel consumption by 8.06% compared with the traditional control strategy ECMS. The proposed R-ECMS not only achieves sub-optimal optimization performance, but also sharply reduces the computing burden, as compared to dynamic programming. Moreover, its performance is robust to various driving scenarios. The simulation using another road profile in reality shows that the R-ECMS can achieve a 6.94% reduction in the corresponding fuel consumption compared to the ECMS. Thus, the R-ECMS has a good application prospect.