On Chip Kalman Filtering Strategy-Based for VRLA Battery Control Unit

Abstract:

Based on existing understanding of residual capacity, the paper adopts Kalman filtering method on SOC estimation. The battery control unit(BCU) includes voltage, current and temperature sampling module. Due to Lead-Acid battery charging and discharging are a complex electrochemical process, we suggest a non-linear least squares regression method (NLLSRM) on open circuit voltage (OCV) method is proposed to aim at Lead-Acid battery. At the same time, a detailed hardware circuit schemes transfer module and on chip embedded Kalman filter method are employed. Moreover, A Local Interconnect Network (LIN) Bus Communication Technology is applied to communicate to Electronic Control Unit (ECU). Validation experimental results show that the proposed Lead-Acid BCU is high credible and the state of charge (SOC) estimation average relative error is about 3%.

• Periodical: Applied Mechanics and Materials (Volumes 148-149)
• Pages: 1256-1259
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.148-149.1256
• Online since: December 2011
• Authors: Chang Hao Piao, Ming Liang Liu, Qiang Zhang, Qi Feng Liu
• Keywords: BCU, Kalman, Lead-Acid Battery, LIN, NLLSRM, SoC

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