Cost Reference Particle Filter Combined with Gross Error Detection and Compensation for the State of Charge Estimation of Lithium Battery

The measurement data of the battery obtained by the sensor will be affected by gross errors, which will reduce the estimated accuracy of State of Charge (SOC). In order to solve the above problem, this paper proposes a lithium battery SOC estimation method, CRPF -GEDC, which is based on cost reference particle filter (CRPF) combined with gross error detection and compensation. This method detects the errors in the measurement data of lithium battery real time, classifies them and estimates the true value to compensate the abnormal measurement points to improve the accuracy of state estimation. Compared with the traditional CRPF, CRPF-GEDC has a higher robustness because it does not require accurate noise statistic characteristics of noise and can handle measurement data with different types of gross errors. The experimental results show that the proposed CRPF -GEDC can effectively suppress the impact of gross errors when estimating the SOC of lithium battery.