Novel Adaptive Sliding Mode Observer for SOC Estimation of Lithium Batteries in Electric Vehicles
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | Novel Adaptive Sliding Mode Observer for SOC Estimation of Lithium Batteries in Electric Vehicles |
| Type de publication | Conference Paper |
| Year of Publication | 2017 |
| Auteurs | Huangfu Y.G, Xu J.N, Zhuo S.R, Xie M.C, Liu Y.T |
| Editor | Cheng KWE |
| Conference Name | 2017 7TH INTERNATIONAL CONFERENCE ON POWER ELECTRONICS SYSTEMS AND APPLICATIONS - SMART MOBILITY, POWER TRANSFER & SECURITY (PESA) |
| Publisher | Power Elect Res Ctr; S China Univ Technol; CLP; HK Elect; Solarever Holdings Ltd; IEEE Transportat Electrificat Commun; Hong Kong Polytechn Univ; PolyU |
| Conference Location | 345 E 47TH ST, NEW YORK, NY 10017 USA |
| ISBN Number | 978-1-5386-1386-3 |
| Mots-clés | Equivalent circuit model, lithium battery, Sliding mode observer, SOC estimation |
| Résumé | On the basis of the established second order RC equivalent circuit model, a novel adaptive sliding mode observer (ASMO) is proposed to estimate the state of charge (SOC) of lithium battery in the electric vehicle. The ASMO can adaptively adjust the switching gain according to the system output deviation. The Lyapunov stability theory is employed to prove the convergence of ASMO. Three different discharge curves are carried out, and the comparisons with conventional sliding mode observer (CSMO) and adaptive extended Kalman filter (AEKF) are also presented to evaluate the performance of ASMO. The results show that: (1) compared with CSMO, ASMO can solve the contradiction between the SOC convergence speed and the chattering (2) compared with AEKF, ASMO has the similar SOC estimation accuracy, but possesses faster convergence speed, stronger robustness and less computation time. |