The current paper describes a hybrid control algorithm for fuel consumption minimization of a compound hybrid excavator. The power train of the excavator integrates an engine assist motor, a super capacitor, and a dc/dc converter for hybridization of the original power train. This power train also incorporates an electrically propelled swing motor, which replaces the conventional hydraulic swing motor, to remove hydraulic loss and recuperate the kinetic energy of the swing motion. Since the super capacitor provides the required energy for the electric swing motor, sustaining the charge presents an important consideration in the power management algorithm design. First, the optimal control problem has been applied to the fuel consumption minimization problem, and an algorithm based on the equivalent fuel minimization strategy (ECMS) has been applied by analyzing the behavior of the co-state of the optimal control problem. The ECMS algorithm is integrated with an engine set speed regulator to increase the overall efficiency of the diesel engine. The engine set speed regulator was designed to change the engine set speed, depending on the engine load. Simulations show that the ECMS is near optimum compared to the dynamic programming results, maintaining an approximately 3% fuel improvement compared to a thermostat controller, which determines power distribution based on the state of charge. Excellent charge-sustaining performance was also achieved. The performance of the control algorithm was verified through real-world vehicle tests, resulting in an approximately 30% improvement in fuel economy, compared to the conventional excavator. (C) 2016 Published by Elsevier B.V.