车用锂离子动力电池剩余电量预测系统研究及开发

Research and Exploitation on Lithiumion Power Battery SOC Estimation System

为实时准确地预测电动汽车动力电池组荷电状态(SOC),首先建立了二阶非线性等效电路模型并提出扩展卡尔曼滤波(EKF)算法,通过Simulink在离线条件下对模型及算法的有效性进行验证;基于Matlab,CANoe,CCP标定及自动代码生成等开发工具和方法,将模型及算法转化为可实时运行的代码,用于电池SOC预测;实车试验结果表明本研究方法具有较高的预测精度及品质,图形化编程语言和自动代码生成技术在保证鲁棒性的同时可快速高效的将复杂模型及算法转化为目标代码,有助于提高科研效率并缩短产品开发研发周期。

For the sake of real time estimating electric vehicle battery packs State of Charge(SOC) well and truly,a nonlinear equivalent circuit model and Extended Kalman Filter arithmetic is presented.Based on Matlab,CANoe,CCP and Real Time Workshop,model is validated off line;code is generated and downloaded to target controller.The real time validation result on battery simulator indicates EKF strategy keeps an excellent precision and character.The advantage of graphics programme language and auto code generation technique not only keeps robustness of the model but also its efficiency in target code generation,which is helpful to improve scientific research efficiency and reduce exploitation time.