In　practical　electric　vehicle　applications,　the　noise　of　original　discharging/charging　voltage　(DCV)　signals　are　inevitable,　which　comes　from　electromagnetic　interference　and　the　measurement　noise　of　the　sensors.　To　solve　such　problems,　the　Discrete　Wavelet　Transform　(DWT)　based　state　of　charge　(SOC)　estimation　method　is　proposed　in　this　paper.　Through　a　multi-resolution　analysis,　the　original　DCV　signals　with　noise　are　decomposed　into　different　frequency　sub-bands.　The　desired　de-noised　DCV　signals　are　then　reconstructed　by　utilizing　the　inverse　discrete　wavelet　transform,　based　on　the　sure　rule.　With　the　de-noised　DCV　signal,　the　SOC　and　the　parameters　are　obtained　using　the　adaptive　extended　Kalman　Filter　algorithm,　and　the　adaptive　forgetting　factor　recursive　least　square　method.　Simulation　and　experimental　results　show　that　the　SOC　estimation　error　is　less　than　1%,　which　indicates　an　effective　improvement　in　SOC　estimation　accuracy.