Recent demands to reduce pollutant emissions and improve energy efficiency have driven the implementation of hybrid solutions in mobile machinery. This paper presents the results of a numerical and experimental analysis conducted on a hydraulic hybrid excavator (HHE). The machinery under study is a middle size excavator, whose standard version was modified with the introduction of an energy recovery system (ERS). The proposed ERS layout was designed to recover the potential energy of the boom, using a hydraulic accumulator as a storage device. The recovered energy is utilized through the pilot pump of the machinery which operates as a motor, thus reducing the torque required from the internal combustion engine (ICE). The analysis reported in this paper validates the HHE model by comparing numerical and experimental data in terms of hydraulic and mechanical variables and fuel consumption. The mathematical model shows its capability to reproduce the realistic operating conditions of the realized prototype, tested on the field. A detailed energy analysis comparison between the standard and the hybrid excavator models was carried out to evaluate the energy flows along the system, showing advantages, weaknesses and possibilities to further improve the machinery efficiency. Finally, the fuel consumption estimated by the model and that measured during the experiments are presented to highlight the fuel saving percentages. The HHE model is an important starting point for the development of other energy saving solutions.

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Condition monitoring has been an active area of research in many industrial fields during the last decades, particularly in fluid power systems. This paper presents a solution for the fault diagnosis of a variable displacement axial-piston pump, which is a critical component in many hydraulic systems. The proposed methodology follows a data-driven approach including data acquisition and feature extraction and is based on the analysis of acceleration signals through the theory of cyclostationarity. An experimental campaign was carried out on a laboratory test bench with the pump in the flawless state and in faulty states. Different operating conditions were considered and each test was repeated several times in order to acquire a suitable population to verify data repeatability. Results showed the capability of the proposed approach of detecting a typical fault related to worn slippers. Future works will include tests in order to apply the approach to a wider set of faults and the development of a classifier for accurate fault identification.

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