Efficient　construction　and　optimization　of　mapping　correlation　of　organic　Rankine　cycle　(ORC)　system　under　driving　environment　is　the　key　to　obtain　the　actual　waste　heat　recovery　limit.　Under　external　and　internal　disturbances,　the　ORC　operating　characteristics　have　obvious　uncertainty　and　nonlinearity.　Based　on　driving　conditions　and　ORC　operation　characteristics,　this　paper　proposes　an　ensemble　approach　of　self-organizing　adaptive　maps　and　dynamic　multi-objective　optimization　for　ORC　under　driving　environment　from　the　perspectives　of　coupling　ORC　integration　system,　variable　data　selection,　parameter　coupling　correlation,　adaptive　structure　design　and　multi-objective　optimization.　This　approach　can　achieve　efficient　capture,　construction　and　optimization　of　ORC　dynamic　characteristics　in　complex　driving　environment.　Compared　with　direct　modeling,　input　variables　decreased　by　at　least　69.23%.　RMSE　decreased　by　at　least　66.06%.　Approach　can　adjust　operating　parameters　in　real　time　according　to　the　fluctuation　of　actual　driving　environment,　break　through　the　trade-off　effect　between　thermal　efficiency　and　emissions　of　CO2　equivalent　(ECE),　to　keep　the　optimal　state　of　thermal　efficiency　and　ECE　continuously.　The　approach　proposed　in　this　paper　can　provide　a　new　idea　for　efficient　construction　and　rapid　optimization　of　ORC　dynamic　mapping　association　in　driving　environment.