Fossil　fuel　usage　has　a　great　impact　on　the　environment　and　global　climate.　Promoting　new　energy　vehicles　(NEVs)　is　essential　for　green　and　low-carbon　transportation　and　supporting　sustainable　development.　Lithium-ion　power　batteries　(LIPBs)　are　crucial　energy-storage　components　in　NEVs,　directly　influencing　their　performance　and　safety.　Therefore,　exploring　LIPB　reliability　technologies　has　become　a　vital　research　area.　This　paper　aims　to　comprehensively　summarize　the　progress　in　LIPB　reliability　research.　First,　we　analyze　existing　reliability　studies　on　LIPB　components　and　common　estimation　methods.　Second,　we　review　the　state-estimation　methods　used　for　accurate　battery　monitoring.　Third,　we　summarize　the　commonly　used　optimization　methods　in　fault　diagnosis　and　lifetime　prediction.　Fourth,　we　conduct　a　bibliometric　analysis.　Finally,　we　identify　potential　challenges　for　future　LIPB　research.　Through　our　literature　review,　we　find　that:　(1)　model-based　and　data-driven　approaches　are　currently　more　commonly　used　in　state-estimation　methods;　(2)　neural　networks　and　deep　learning　are　the　most　prevalent　methods　in　fault　diagnosis　and　lifetime　prediction;　(3)　bibliometric　analysis　indicates　a　high　interest　in　LIPB　reliability　technology　in　China　compared　to　other　countries;　(4)　this　research　needs　further　development　in　overall　system　reliability,　research　on　real-world　usage　scenarios,　and　advanced　simulation　and　modeling　techniques.