On Chip Kalman Filtering Strategy-Based for VRLA Battery Control Unit
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 nonlinear 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％.
Lead-Acid Battery BCU SOC LIN NLLSRM Kalman
Changhao Piao Mingliang Liu Qiang Zhang Qifeng Liu
Research Institution of Pattern Recognition and Application, Chongqing University of Posts and Telec Research Institution of Pattern Recognition and Application, Chongqing University of Posts and Telec State Key Laboratory of Vehicle NVH and Safety Technology, Chongqing Changan Automobile Co., LTD., C
国际会议
大连
英文
1256-1259
2011-10-19（万方平台首次上网日期，不代表论文的发表时间）