Transcranial alternating current stimulation (tACS) is a widely used noninvasive brain stimulation method. However, due to nonlinear electrical stimulation artifacts interference, it is difficult to obtain the real neural activity during stimulation directly. Therefore, an adaptive variational mode decomposition (AVMD) method is proposed to remove the nonlinear tACS artifacts. In this method, the envelope of artifacts is extracted by Hilbert transform (HT), then, the VMD modes is obtained by WFT spectrum analysis. VMD is used to decompose the recorded data to obtain multiple intrinsic mode signals. According to the amplitude characteristics, the artifact components are selected, and the effective EEG components are recovered. AVMD algorithm were tested on the synthetic data and the public experimental data. The correlation coefficient between reconstructed EEG and real EEG was used to measure the artifact removal effect for the synthetic data. The mean absolute error (MAE) of the statistical characteristics between recovered EEG and sham EEG was used to evaluate the artifact removal effect for the experimental data. For the synthetic data, under the conditions of amplitude modulation depth ma∈ [0. 001, 0. 01], phase modulation depth mp∈ [0. 001, 0. 01] and stimulation frequency f arti∈ [10, 100],the average correlation coefficients between reconstructed EEG and real EEG are 0. 988 5, 0. 893 5, 0. 948 4, respectively. The MAE of the statistical characteristics between recovered EEG and sham EEG are 0. 989 6 ( kurtosis), 2. 991 8( root mean square amplitude), 0. 175 1 (sample entropy) for the experimental data with the stimulation frequency 11 Hz, and are 0. 940 7 (kurtosis), 2. 473 1 (root mean square amplitude) and 0. 084 1 (sample entropy) for the experimental data with the stimulation frequency 62 Hz. AVMD method shows more stable and better nonlinear tACS artifact removal performance compared with superposition of moving averages ( SMA), adaptive filtering (AF) and empirical mode decomposition (EMD). This method provides support for the development of closed-loop tACS instrument.