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.