This　paper　proposes　a　hierarchical　optimization　energy　management　strategy　to　suppress　the　battery　aging　in　plug-in　hybrid　electric　vehicles.　In　the　first-level,　a　variable-threshold　dynamic　programming　algorithm　to　distribute　the　power　between　the　energy　storage　system　and　the　engine　is　proposed.　By　adding　supercapacitor　to　form　the　hybrid　energy　storage　system,　and　using　adaptive　low-pass　filtering　algorithm,　the　power　between　the　battery　and　the　supercapacitor　is　distributed.　To　control　the　supercapacitor　and　battery　to　work　within　the　capacity　range,　a　power　limits　management　module　for　redistributing　the　power　between　the　engine,　the　supercapacitor　and　the　battery　is　considered.　The　adaptive　low-pass　filtering　algorithm　and　power　limits　management　module　constitute　adaptive　power　allocation　method　in　the　second-level.　After　that,　the　rain-flow　counting　algorithm　is　applied　in　this　paper　to　calculate　battery　aging　cost.　By　using　the　rain-flow　counting　algorithm,　the　battery　performances　are　analyzed,　and　the　results　show　that　the　adaptive　power　allocation　method　can　improve　the　battery　service　life　by　about　54.9%　compared　with　the　global　dynamic　programming　algorithm.　Considering　the　initial　cost　of　the　supercapacitor,　the　costs　of　battery　aging,　fuel　consumption,　electricity　consumption,　and　management　cost　of　retired　batteries,　compared　with　the　global　dynamic　programming　algorithm,　the　life　cycle　economy　of　the　vehicle　is　improved　by　12.4%　under　the　proposed　method.　©　2019　Elsevier　Ltd