Second-Order Discrete-Time Sliding Mode Observer for State of Charge Determination Based on a Dynamic Resistance Li-Ion Battery Model

Abstract

A second-order discrete-time sliding mode observer (DSMO)-based method is proposed to estimate the state of charge (SOC) of a Li-ion battery. Unlike the first-order sliding mode approach, the proposed method eliminates the chattering phenomenon in SOC estimation. Further, a battery model with a dynamic resistance is also proposed to improve the accuracy of the battery model. Similar to actual battery behavior, the resistance parameters in this model are changed by both the magnitude of the discharge current and the SOC level. Validation of the dynamic resistance model is performed through pulse current discharge tests at two different SOC levels. Our experimental results show that the proposed estimation method not only enhances the estimation accuracy but also eliminates the chattering phenomenon. The SOC estimation performance of the second-order DSMO is compared with that of the first-order DSMO.

A Parameter Identification Method for Dynamics of Lithium Iron Phosphate Batteries Based on Step-Change Current Curves and Constant Current Curves

“…Then, Equation (B3) can be derived from Equation (B1). Parameter identification of the ECM under a set of {i 1 , i 2 , SOC j } is to identify the parameters in Equation (10). Define input and output in Equation (10) as: r u ptq " i`t`t j˘´i1 r y ptq " U d`t`t j˘´U c i 2`t`t j˘`U c i 2`t j˘´U c i 1`t j˘(…”

“…It must be noted that identified R 2 or C 2 needs to be divided or multiplied by the proportional coefficient in the last line of Equation (10) to obtain the true value.…”

“…Essentially, these methods are all based on parameter identification of the ECM or current integration, and some of them have sufficient accuracy for applications. This paper utilizes ampere-hour counting method along with open circuit voltage estimation method for SOC estimation, which is similar with the method in [8][9][10]. Estimation error is verified with constant current discharge test to insure the accuracy.…”

A Novel Sliding Mode Observer for State of Charge Estimation of EV Lithium Batteries

“…Sliding mode observer is a kind of iterative algorithm which can be used in battery SOC estimation [15]- [20]. The design of previous sliding mode observers for battery SOC estimation includes: 1.…”

State-of-Charge Estimation and Active Cell Pack Balancing Design of Lithium Battery Power System for Smart Electric Vehicle

“…As a result, a linear model using fewer parameters in the electrochemical model was adopted [30] with Kalman filter (KF) to estimate the SOC. The extended Kalman filter (KF) [31][32][33], sliding-mode observer [34,35], and Luenberger observer [36,37] were applied to estimate the SOC using the ECM model. However, it required an accurate model of the battery and higher computing resource with correct initialization of parameters that changed rapidly.…”