Light-weighted Battery State of Charge Estimation based on the Sigma-delta Technique

Abstract In this paper, a light-weighted state-of-charge (SoC) estimator is proposed to ensure the estimation accuracy as well as significantly reduce the computational effort. Specifically, the sigma-delta (Σ∆) technique is employed to extract battery SoC under noisy measurements (up to ± 100mV and 100mA) and validated under different battery aging conditions. Illustrative results demonstrate that in this circumstance, the proposed estimator presents low sensitivity to model accuracy and is also suitable for the non-Gaussian noises. Besides, the second-order Σ∆ estimator is capable of achieving a satisfactory accuracy (RMSEs are all within 1.5% for different aging batteries), while its computational effort is just 15% of that of the extended Kalman filter. These features pave a solution to the design of a light-weighted SoC estimator based on general micro-controller unit, further making the proposed Σ∆ estimator become suitable for improving the reliability and practicability of battery management especially for electrical vehicle applications.