The　accurate　estimation　of　the　state　of　charge　(SOC)　plays　an　important　role　in　optimizing　the　energy　management　of　electric　vehicles.　To　improve　the　estimation　accuracy　of　SOC,　this　study　proposes　a　SOC　estimation　method　with　the　adaptive　unscented　Kalman　filter　(AUKF)　based　on　an　accurate　equivalent　circuit　model.　First,　combined　with　the　n-RC　equivalent　circuit　model,　the　relationship　curve　between　SOC　and　open-circuit　voltage　(OCV)　is　fitted　via　parameter　identification.　Next,　the　accuracy　advantage　of　the　n-RC　model　is　proven　by　comparing　and　analyzing　the　voltage　response　curves　of　different　n-RC　models　and　several　common　equivalent　circuit　models.　Moreover,　the　accuracy　of　the　n-RC　model　becomes　higher　with　the　increasing　n.　Then　the　numerical　validation　experiments　are　established　based　on　the　AUKF　algorithm,　and　the　constant　current　discharge　experiment,　hybrid　pulse　experiment,　robustness　verification　experiment　are　carried　out.　Finally,　to　effectively　evaluate　this　estimation　approach,　in　addition　to　setting　up　a　control　group　experiment　based　on　the　extended　Kalman　filter　(EKF)　algorithm　and　unscented　Kalman　filter　(UKF)　algorithm.　The　experiment　results　show　that,　compared　with　the　other　two　algorithms,　the　SOC　estimation　method　based　on　AUKF　is　more　accurate.　©　2021　Elsevier　Ltd