Cyclic voltammetry is one of today's standard electrochemical measurement techniques. What characterizes cyclic voltammetry is that potential is linearly ramped in cycles. In general, in this kind of measurements, the system tends to a stationary state, which is known as limit cycle. The common practice for assessing the voltammogram convergence is to perform a multicycle cyclic voltammetry, and visually compare the sequential cycles in order to see if there are significant changes from one cycle to the following one. The main limitation of visual comparison is its limited accuracy and its dependence on the analyst's subjectivity. In this work, an algorithm for quantitatively assessing the convergence of experimental cyclic voltammograms (CVs) was developed. The algorithm was successfully validated experimentally using two systems: it is able to determine whether the CV converged to its limit cycle, and when it converged. Moreover, the algorithm is able to quantify the measurement noise. The low computational cost of the developed algorithm allows to execute it in real time during the cyclic voltammetry measurement. In this way, it can be used in order to automate the measurement process which would decide, according to predefined convergence criteria, when to stop cycling. (c) 2019 The Electrochemical Society.