Abstract
The reasonable construction of the organic Rankine cycle (ORC) system model under road conditions is the key to analyze, evaluate, and optimize the performance of the ORC system. However, due to the variability of high-temperature waste heat source and the strong coupling correlation of operating parameters, the operation characteristics of the ORC system show evident time-varying characteristics. Based on the coupling correlation and redundancy characteristics of the ORC system in complex environment, this paper presents a nonlinear modeling framework for the multi-scale influence analysis of the ORC system under road conditions. The nonlinear modeling framework can improve the prediction accuracy of ORC model by at least 68.36% and reduce the time cost by 53.37%. Based on the nonlinear model, the synergistic effects of multiple variables on ORC system performance at different scales are studied. The frequent fluctuation of vehicle speed enhances the coupling correlation of operating parameters, resulting in nonlinear, hysteretic dynamic characteristics of ORC thermal efficiency. The maximum thermal efficiency of ORC is only 3.28%. The nonlinear modeling framework proposed in this paper can provide a practical solution for constructing the intelligent analysis, design, and optimization models of ORC systems under complex road conditions.
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