基于DSP的电动汽车锂电池荷电状态估算的研究与实现

锂电池荷电状态(SOC)的准确估算是电动汽车能源管理的关键技术。为了提高锂电池SOC的估算精度，将无迹卡尔曼滤波(UKF)应用于锂电池SOC估算，以减小拓展卡尔曼滤波(EKF)简单线性化带来的误差。搭建电池检测系统的硬件平台，以TMS320F28335型数字信号处理器(DSP)为主控芯片(MCU)，实现电压、电流、温度的检测及UKF算法，并设计了相关的电池测试实验。实验结果表明，UKF可以实时估算锂电池SOC，估算误差在4%以内，高于传统的拓展卡尔曼滤波(EKF)。

Research and Realization of EstimatingSSOC ofSthe Electric VehicleS Lithium BatterySbased on DSP

The lithium battery state of charge (SOC) accurate estimation is an important technology of electric vehicle energy management. In order to improve the accuracy of estimating SOC lithium battery,unscentedSKalmanSfilter (UKF) is used to SOC estimation. And this method can also reduce the extended Kalman filter (EKF) to bring a simple linearization error.When make a battery testing system hardware platform, TMS320F28335 type digital signal processor (DSP) is treat as the main control chip (MCU) . It can realize UKF algorithm and the detection of temperature, voltage, current, and the design of the battery test related experiments. The experimental results show that UKF can real-time estimate lithium battery SOC,and the estimation error is less than 4%, which is higher than the traditional extended Kalman filter (EKF) .