Considering　the　trade-off　on　the　improvement　of　fuel　economy　performance　and　mode　transition　comfort　for　multimode　hybrid　electric　vehicles　(MMHEV),　a　bi-objective　trade-off　control　strategy　is　designed　based　on　the　equivalent　consumption　minimization　strategy　(ECMS)　with　Pareto　method.　Aiming　at　the　problem　of　optimal　economy　of　multimode　working　area　of　vehicles,　the　equivalent　fuel　consumption　cost　and　torque　distribution　MAP　in　different　modes　are　determined　based　on　ECMS.　In　order　to　solve　the　problem　of　torque　instability　caused　by　engine　response　lag　and　demand　torque　fluctuation,　the　motor　torque　optimization　coefficient　(MTOC)　is　introduced　as　the　control　variable　by　taking　advantage　of　the　motor＇s　fast　and　accurate　response　to　torque,　and　the　genetic　algorithm　is　used　to　optimize　the　MTOC,　and　a　smoother　torque　distribution　is　obtained.　Because　there　is　a　coupling　relationship　between　the　economy　and　ride　comfort　of　the　system,　the　trade-off　optimization　is　carried　out　using　the　NSGA-II　algorithm　based　on　Pareto　principle.　The　simulation　verification　conducted　in　nonslope　and　slope　conditions,　as　well　as　hardware-in-the-loop　experiments,　demonstrates　the　effectiveness　of　the　proposed　control　strategy　in　managing　the　trade-off　between　economy　and　ride　comfort　for　the　MMHEV.　This　article　focuses　on　the　trade-off　between　fuel　economy　and　driving　comfort　of　multimode　hybrid　electric　vehicle　(MMHEV).　Based　on　equivalent　consumption　minimization　strategy-Pareto　joint　algorithm,　a　bi-objective　trade-off　control　strategy　is　designed.　The　results　show　that　the　driving　comfort　can　be　greatly　improved　with　a　small　sacrifice　of　economy.image　(c)　2023　WILEY-VCH　GmbH