Accurately　identifying　the　unknown　parameters　of　the　Gurson-Tvergaard-Needleman　(GTN)　damage　model　is　essential　to　better　understand　the　damage　behavior　of　materials　and　improve　the　simulation　accuracy.　In　order　to　solve　the　problem　that　traditional　parameter　identification　methods　are　cumbersome　and　inefficient,　this　paper　proposed　an　efficient　damage　parameter　identification　strategy　with　the　combination　of　microscopic　analysis,　finite　element　simulation,　and　response　surface　analysis.　The　relationship　between　the　evolution　of　microvoids　and　plastic　strain　in　DP800　steel　was　quantified　through　the　in-depth　analysis　of　the　microstructure　of　tensile　specimens.　Response　surface　method　and　Box-Behnken　experimental　design　were　adopted　to　efficiently　identify　and　optimize　the　crucial　damage　parameters　(fN,　fC,　fF)　with　the　difference　ratio　of　fracture　strain　as　the　response　variable.　Through　analysis　of　variance,　the　factors　that　have　significant　influence　on　the　damage　parameters　were　further　confirmed.　Through　the　experimental　comparison　with　the　simulation　results　based　on　the　GTN　damage　model,　the　effectiveness　of　the　identified　damage　parameters　was　verified,　and　the　influence　of　these　parameters　on　the　stress-strain　curve　was　deeply　revealed.　The　results　show　that　the　damage　parameter　identification　strategy　has　achieved　remarkable　results　in　accuracy　and　efficiency,　and　has　important　engineering　significance　for　the　accurate　prediction　of　the　actual　dual-phase　steel　sheet　forming　process.　©　2024　Elsevier　Ltd