JADE algorithm is an improved algorithm of basic differential evolution algorithm (DE) with better convergence speed and optimization performance, whose self-adaptive parameter adjustment mechanism improves its global optimization ability. In this paper, we use self-adaptive differential evolution algorithm (JADE) for clustering and propose a new automatic clustering algorithm based on JADE，named as AC-JADE. Firstly, it takes double crossover strategy for clustering. Specifying to the encoding mode of DE used for clustering, it adds a new crossover strategy after the conventional two point crossover operation. This new crossover strategy acts directly on two clustering centers derived from parent vector and trial vector separately. Secondly, it makes improvements on the drawbacks that the selected clustering centers may deviate from the data set or they are too close results from the randomness of mode for choosing clustering center. Sifting clustering centers before choosing some of them for clustering results has a better effect. The experimental results carried on 4 UCI datasets verifies effectiveness of the proposed algorithm.