Partnership　for　a　new　generation　of　vehicles　(PNGV)　model　is　a　conventional　battery　equivalent　circuit　model　(ECM).　However,　identifying　the　best　parameters　for　this　model　is　a　challenge.　In　this　study,　the　PNGV　model　is　transformed　into　a　directly　identifiable　difference　equation　to　identify　its　parameters.　Subsequently,　the　model　reference　adaptive　system　(MRAS)　is　used　to　realize　the　real-time　identification　of　the　model　parameters.　The　identification　accuracy　of　the　MRAS　is　found　to　be　superior　to　that　of　the　recursive　extended　least　square　algorithm.　For　a　single　hybrid　pulse　power　characterization　(HPPC),　the　PNGV　model　identified　by　the　MRAS　can　achieve　a　high-precision　terminal　voltage　estimation.　For　lithium　iron　phosphate,　lithium　titanate,　and　nickel-metal　hydride　batteries,　the　root　mean　square　errors　are　0.024,　0.048,　and　0.020　V,　respectively.　Besides,　the　real-time　state　of　charge　(SOC)　estimation　can　be　realized　by　the　identified　open-circuit　voltage　(OCV).　The　average　errors　of　the　three　batteries　are　only　−0.02,　−0.01,　and　−0.01,　respectively.　Since　the　PNGV　model　has　a　capacity　of　describing　the　change　of　OCV　with　the　current　accumulation　effect,　the　model　is　only　suitable　for　simulating　single　HPPC　or　positive-negative　pulses　with　equal　amplitude　and　not　for　other　current　pulses.　This　is　a　major　drawback　of　the　PNGV　model.　The　real-time　PNGV　model　parameters　identification　method　proposed　in　this　study　can　provide　a　solid　foundation　for　various　state　estimation　of　a　battery.　Novelty　Statement:　Transformation　of　the　PNGV　model　into　a　difference　equation　that　can　be　directly　identified.　Real-time　identification　of　the　PNGV　model　parameters　via　the　MRAS.　The　identified　OCV　realized　the　real-time　SOC　estimation　and　discussed　the　deficiencies　of　the　PNGV　model.　©　2021　John　Wiley　&　Sons　Ltd