摘要
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(LIKF)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)。
The lithium battery state of charge （SOC） accurate estimation is an important technology of electric vehicle energy manage ment. In order to improve the accuracy of estimating SOC lithium battery, unscented Kalman filter （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） . h can realize UKF algo rithm 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） .
出处
《计算机测量与控制》
2015年第10期3533-3535,共3页
Computer Measurement &Control
基金
国家自然基金(61563006)
广西科技攻关项目(桂科攻1598008-2)
广西高校科研基金(KY2015YB165)
广西重点实验室建设项目(14-045-44
14-A-02-05)
广西汽车零部件与整车技术重点实验室开放基金重点项目(2014KFZD01)
国家级大学生创新计划项目(201410594022)
广西研究生创新计划项目(YCSZ2014199)
