A novel phenomenological model for predicting hysteresis loss of rubber compounds obtained from ultra-large off-the-road tires. (January 2023)

• Record Type: Journal Article
• Authors: Ma, Shaosen; Huang, Guangping; Obaia, Khaled; Won Moon, Soon; Victor Liu, Wei
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 237:Number 1(2023)
• Page Start: 207
• Page End: 223
• Publication Date: 2023-01
• Subjects: Phenomenological model -- tire rubber -- hysteresis loss -- strain rate -- strain level -- rubber temperature; Mechanical engineering -- Congresses; Transportation engineering -- Congresses; 629.2
• DOI: 10.1177/09544070211072494
• Languages: English
• ISSNs: 0954-4070

Abstract

The objective of this study was to develop a novel phenomenological model that can predict the hysteresis loss of rubber compounds obtained from ultra-large off-the-road (OTR) tires under typical operating conditions at mine sites. To achieve this, first, cyclic tensile tests were conducted on tire tread compounds to derive the experimental results of hysteresis curves, peak stress, residual strain, and hysteresis loss at 6 strain levels, 8 strain rates, and 14 rubber temperatures. Then, referring to these experimental results, a phenomenological model was developed – the HLSRT model (a hysteresis loss model considering strain levels, strain rates, and rubber temperatures). This HLSRT model was generated based on a novel strain energy function that was modified from the traditional Mooney-Rivlin (MR) function, and the model was used to predict the hysteresis loss of rubber compounds in OTR tires. The prediction results show that the HLSRT model estimated the hysteresis loss of tire tread compounds with average and maximum mean absolute percent errors (MAPEs) of 11.2% and 18.6%, respectively, at strain levels ranging from 10% to 100%, strain rates from 10% to 500% s −1, and rubber temperatures from −30°C to 100°C. These MAPEs were relatively low when compared with previous studies, showing that the HLSRT model has higher prediction accuracy. For the first time, the HLSRT model derived from this study has provided a new approach to predicting the hysteresis loss of OTR tire rubbers to guide the use of OTR tires in truck haulage at mine sites.