The system of absolute value equations $Ax+B|x|=b$, denoted by AVEs, is proved to be NP-hard, where $A, B$ are arbitrary given $n\times n$ real matrices and $b$ is arbitrary given $n$-dimensional vector. In this paper, we reformulate AVEs as a family of parameterized smooth equations and propose a smoothing-type algorithm to solve AVEs. Under the assumption that the minimal singular value of the matrix $A$ is strictly greater than the maximal singular value of the matrix $B$, we prove that the algorithm is well-defined. In particular, we show that the algorithm is globally convergent and the convergence rate is quadratic without any additional assumption. The preliminary numerical results are reported, which show the effectiveness of the algorithm.