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作 者:陈继永 吴兆宏[3] 李金喜 CHEN Jiyong;WU Zhaohong;LI Jinxi(Jiangsu College of Engineering and Technology,Nantong 226007,China;Jiangsu Province Intelligent Network United Automobile Engineering Technology R&D Center,Nantong 226007,China;Mining Products Safety Approval and Certification Center Co.,Ltd.,Beijing 100013,China;School of Information and Control Engineering,China University of Mining and Technology,Xuzhou 221116,China)
机构地区:[1]江苏工程职业技术学院,江苏南通226007 [2]江苏省智能网联汽车工程技术研究开发中心,江苏南通226007 [3]安标国家矿用产品安全标志中心,北京100013 [4]中国矿业大学信息与控制工程学院,江苏徐州221116
出 处:《煤矿安全》2019年第12期102-105,共4页Safety in Coal Mines
基 金:江苏省智能网联汽车工程技术研究开发中心资助项目(苏教科(2018)10号);南通市科技计划资助项目(JCZ18065);江苏工院科研计划资助项目(GYKY/2016/13)
摘 要:针对现有矿用机车防爆锂电池荷电状态(SOC)估算方法累积误差大、受电池模型准确度影响等问题,提出一种以分段开路电压校正安时积分法的SOC估算方法。通过开路电压OCV校正初始SOC值,通过周期性校正克服累积误差,从而保证算法的准确性。使用专用电池监控芯片MC33771实现该算法的硬件设计。经试验,该方法适用于矿用机车防爆锂电池管理系统。Aiming at the problems that existing methods for estimating state of charge(SOC)of explosion-proof lithium battery of mine locomotive has large cumulative errors which are affected by battery model accuracy,a SOC estimation algorithm based on correcting Ahh-total integration method with segmented open-circuit voltage is proposed.This method corrects the initial SOC value by the open-circuit voltage,and overcomes the accumulated error by periodic correction,so as to ensure the accuracy of the algorithm.The hardware design of the algorithm is implemented by using smart battery monitoring chip MC33771.The experiment shows that this method is suitable for the explosion-proof lithium battery management system of mining locomotive.
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