Lithium-ion batteries have been applied in the new energy vehicles more and more widely. The inconsistency of battery cells imposes a lot of difficulties in parameter and state estimations. This paper proposes a new algorithm which can online identify the parameters of each individual battery cell accurately with limited increase of computational cost. An equivalent circuit battery model is founded and based on the RLS (recursive least squares) algorithm, an optimization algorithm with the construction of weight vectors is proposed which can identify the parameters of lithium battery pack considering inconsistency of single battery cell. Firstly, the average value of the parameters of the battery pack is identified with the traditional RLS algorithm. Then the ratios between the parameters of each battery cell can be deduced by using the mathematical model of battery. These ratios are used to determine the weight vector of each parameter of individual battery cells. Finally, with the average battery parameters and the weight vectors, we can obtain the parameters of each cell. The proposed weighted algorithm is verified with the bench test data. The results show that the weighted algorithm can achieve a good accuracy of parameter identification with a low computation cost.