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Abstract: The concept of hybrid ships has gained significant attention in recent years, as they offer an effective means of enhancing energy utilization and reducing environmental pollution. However, the navigational environments of ships are often subject to changes, which in turn affects their energy efficiency in a complex manner. It is therefore evident that enhancing the energy efficiency of hybrid ships is a worthwhile goal. In this study, we take a diesel-electric hybrid ship navigating in inland waterways as the research object, and propose a hierarchical optimization method for ship energy efficiency. The upper-layer control establishes a predictive model for propulsion motor speed and fuel consumption through multivariate time series predictions, and employs the model predictive control (MPC) method to optimize the propulsion motor speed. The lower-layer control utilizes an equivalent fuel consumption minimization method which is based on improving the equivalence factor. This involves combining the variation of the supercapacitor ’ s state of charge (SOC) with the propulsion motor speed obtained from the MPC optimization in the upper-layer control. Furthermore, a proportional integral (PI) controller is used to adjust the equivalence factor, in order to adapt the equivalent fuel consumption minimization method to the working conditions. Our results demonstrate that the proposed hierarchical optimization method can reduce the energy efficiency operating indicator (EEOI) by approximately 11.54% and the fuel consumption by approximately 9.47% in comparison to the pre-optimization scenario.