In　this　article,　an　integrated　＇dual-motor　automated　mechanical　transmission＇configuration　was　proposed　for　battery　electric　vehicles,　and　a　rule-based　energy　management　strategy　based　on　dynamic　programming　(DP)　algorithm　optimization　was　designed.　The　rule-based　energy　management　strategy　was　used　for　online　control,　and　the　DP　algorithm　was　used　to　optimize　the　control　parameters　of　the　rule-based　energy　management　strategy　offline.　Finally,　the　optimization　results　were　validated　online　using　the　hardware-in-the-loop　simulation　platform.　The　results　showed　that　on　average,　the　optimized　rule-based　energy　management　strategy　can　reduce　energy　consumption　by　4.16%　under　the　New　European　Driving　Cycle,　Urban　Dynamometer　Driving　Schedule,　and　Japan　1015　cycle　conditions.　More　importantly,　there　were　evident　energy-saving　effects　on　the　United　States　06,　China　Light-Duty　Vehicle　Test　Cycle-Passenger,　and　Highway　Fuel　Economy　Test　cycle　conditions,　which　did　not　participate　in　the　optimization　of　the　rule-based　energy　management　strategy　by　the　DP　algorithm.　©　2021　SAE　International.