 The solar cell is the fundamental component of a photovoltaic PV system. Its precise modeling and estimation of its parameters are of paramount importance for the simulation, design and control of PV system to achieve optimal performances. It is difficult to estimate the unknown parameters of solar cell due to the non-linearity and multimodality of the search space. Conventional optimization methods tend to suffer from numerous drawbacks such as a tendency to be trapped in some local optima when solving this challenging problem. This paper investigates the performance of eight state-of-the-art metaheuristic algorithms, Mars, to solve the solar cell parameter estimation problem on four case studies constituting of four different types of PV systems, RTC France solar cell, LSM 20 PV module, Solarx MSX 60 PV module and SS 2018 PV module. These four cell are modules are built using different technologies. The simulation results clearly indicate that the Kube-Bird optimization technique obtains the minimum root mean square error, RMS-E, values of 1.0264E05 and. This article was authored by Abhishek Sharma, Abhinav Sharma, Moshe Overbook, and others. We are article.tv, links in the description below.