Abstract

Energy recovery and hybrid power technology are new directions in construction machinery energy-saving research. Thus far, however, no uniform standard method exists to evaluate the efficiency of novel energy-saving concept systems in early stages of development. Efficiency assessment is valuable and credible only by relying on driving cycles that are consistent with actual data. As representative products of construction machinery, hydraulic excavators are multifunctional, object-uncertain, and heavily influenced by operator habits. It is therefore challenging to develop standard excavator driving cycles. Aiming at the energy efficiency evaluation of new energy-saving products characterized by energy recovery and power system optimization, taking medium-sized hydraulic excavator as an example, this paper proposes an evaluation method of energy-saving efficiency and a classification construction method of comprehensive driving cycle of hydraulic excavator based on actual operating data with load demand power and boom recoverable power as combined variables. First, based on the analysis of general driving cycle variables for excavators with different energy-saving schemes, a load demand power model and boom recoverable power model based on machine sensing data are established. Second, 10 excavators were selected at different locations in southern China, and 30 days of real-world working data were recorded. Third, according to the periodic characteristics of working data, a method for dividing microcycle operation structure is proposed. The microcycle sample space based on the data conversion of working data is constructed and classified via the clustering algorithm. Finally, a comprehensive excavator driving cycle based on the classification results is constructed through the Markov method. Results show that the energy-saving efficiency of the three classification driving cycles was 17.45%, 13.60%, and 11.88%, respectively; the comprehensive energy-saving efficiency was 15.76%. The deviations in maximum load demand power and maximum boom recoverable power between the constructed comprehensive cycle and the sample space were 7.81% and 8.61%; the average deviation of characteristic parameters was 4.26%. The comprehensive driving cycles can fairly reflect the general characteristics of real-world working conditions. The proposed construction method of comprehensive driving cycles based on sample space is therefore reliable and holds great promise for evaluating the energy-saving efficiency of new energy-saving concept systems.

Highlights

  • Resource shortages and environmental pollution are increasingly urgent global issues that have promoted the development of energy-saving and emission-reduction technologies [1,2,3,4]

  • In line with aforementioned studies, the main contributions of this work are as follows: (1) a microcycle description method is proposed based on the time-power profile combining load demand and degree of energy recovery; (2) a construction method for the sample space of excavator microcycle based on the conversion of working data is proposed, and the standardization of multifunctional driving cycle of a realworld excavator is realized based on a clustering algorithm; (3) a random problem model is developed based on the Markov method to realize the description of random changes of the operation objects and driver’s habits

  • We performed an energy efficiency assessment of new energy-saving products characterized by energy recovery technology

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Summary

Introduction

Resource shortages and environmental pollution are increasingly urgent global issues that have promoted the development of energy-saving and emission-reduction technologies [1,2,3,4]. Ey assessed the service life of vital welded structures in a bucket-wheel excavator boom subjected to cyclic loading with a variable amplitude Using experimental tests, they determined the operational strength and growth of a fatigue crack for a specific structural part. In line with aforementioned studies, the main contributions of this work are as follows: (1) a microcycle description method is proposed based on the time-power profile combining load demand and degree of energy recovery; (2) a construction method for the sample space of excavator microcycle based on the conversion of working data is proposed, and the standardization of multifunctional driving cycle of a realworld excavator is realized based on a clustering algorithm; (3) a random problem model is developed based on the Markov method to realize the description of random changes of the operation objects and driver’s habits.

Operating Principle and Power Estimation Model of Medium HE System
Microcycle Structure and Cluster Analysis Method
Construction of Comprehensive Driving Cycle Based on Markov Chain
Findings
Conclusion
Full Text
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