To　address　the　limitation　of　existing　excavator　optimization　methods,　which　primarily　focus　on　the　force　performance　while　neglecting　energy　consumption　and　fail　to　realize　environmentally　friendly　and　low-carbon　designs,　this　paper　proposes　a　new　multi-objective　collaborative　optimization　method　for　an　excavator　to　reduce　energy　consumption　during　the　working　process　while　maintaining　optimal　performance.　By　formulating　a　mathematical　model　that　quantifies　the　energy　consumption　during　the　working　process,　this　paper　optimizes　the　working　conditions　by　analyzing　the　energy　consumption　characteristics　under　typical　working　conditions.　To　overcome　the　limitation　of　existing　linear　weighting　methods　in　multi-objective　optimization,　such　as　imbalanced　optimization　quality　among　sub-objectives,　this　paper　proposes　a　new　modeling　approach　based　on　the　loss　degree　of　sub-objectives.　A　multi-objective　collaborative　optimization　model　for　the　excavator　with　reduced　energy　consumption　is　established,　and　a　corresponding　multi-objective　collaborative　optimization　algorithm　is　developed　and　applied　to　achieve　optimal　solutions　for　sub-objectives.　The　optimization　results　demonstrate　that　applying　the　new　multi-objective　collaborative　optimization　method　to　the　excavator　achieves　better　optimization　quality　than　traditional　methods.　It　also　provides　a　more　balanced　improvement　in　the　optimization　values　of　each　sub-objective,　resulting　in　a　significant　reduction　in　the　energy　consumption　of　the　excavator　during　operation.　©　2023　by　the　authors.