For reliable and safe operation of lithium-ion batteries in electric vehicles, the monitoring of state-of-charge and state-of-health is necessary. However, these internal states cannot be measured directly, which are usually estimated through model-based techniques. Therefore, an accurate application-oriented battery model is of significant importance. The purpose of this paper is to present a novel method on battery modeling and parameter identification. In this work, a state-space model with clear mathematical and electrochemical meanings is proposed on the basis of the electrochemical basics of lithium-ion batteries. The frequency-domain characteristics of the lithium-ion batteries are also investigated. On the basis of the frequency analysis, an identification test profile that can excite the dynamic characteristics of the battery fully and persistently is proposed. A subspace-based algorithm is then adopted to identify the parameters of the battery model. The performance and robustness of the estimated model are validated through some experiments and simulations. The validation results show that the proposed method can achieve an acceptable accuracy with the maximum error being less than 2%. Copyright (c) 2013 John Wiley & Sons, Ltd.