Evaluating wheel loader operating conditions based on radar chart

•The difficulty level of the operating conditions for loader was proposed.•The fuzzy c-means clustering algorithm was used to calculate the eigenvalues of spectrums.•The difficulty level was quantified using the area ratio of the radar chart.•Operation spectrums under different conditions were used to verify the method.

The evaluation of the difficulty level of operating conditions is one of the key problems in intelligent management of the wheel loader engine power. This paper presents a method for evaluating the difficulty level of wheel loader operating conditions based on radar chart. Firstly, we analyze the characteristics of the wheel loader operation spectrum, and determine the boom head cylinder pressure as the analysis object. Then, based on the analysis object we establish the characteristic indexes that can express the operating conditions and determine eigenvalues of the characteristic indexes with clustering analysis algorithms. Lastly, we draw the eigenvalues on the radar chart, and extract the area enclosed by the eigenvalues to compare with the area of the radar chart. The ratio of enclosed area of radar chart is defined as the difficulty level of operating conditions. This method is validated under various industrial conditions (i.e. four types of operating conditions, three power modes and three drivers manipulating the wheel loader). The results indicate that the proposed method to evaluate the difficulty level can accurately quantify the real operating conditions, and is a useful tool for management of engine power modes according to the quantified operating conditions.