Recently, the cooling system of hydraulic excavator is often designed using the thermal and fluid analysis to improve the cooling performance. The reliability of the analysis results is important, since it directly influences on the efficiency of development. In the present study, the uncertain parameters were estimated using the data assimilation method to increase the reliability of the thermal and fluid analysis in an engine room of a hydraulic excavator.
The ensemble Kalman filter (EnKF) was adapted as a data assimilation method, and the thermal and fluid analysis was conducted with the three-dimensional steady simulation based on the Reynolds-average Navier-Stokes equations. The estimated parameters were set to the total heat quantities released by heat exchangers and the flow rates of the coolants. The total heat quantity is a parameter used for the heat release calculation of a heat exchanger, and the flow rate of a coolant is specified at the inlet boundary. As measurement data, temperatures of coolants which were measured at the upstream and downstream of the heat exchangers were used. Initial parameters were generated by setting parameter values in a random manner.
The simulation using estimated parameters successfully predicted temperatures at the heat exchangers, where the maximum error was 3K. In addition, the reductions of the standard deviations of the uncertain parameters were confirmed. That means the reliability of the simulation was increased.