Prognostic Methods for Battery Management Systems

这项研究的目的是开发预测方法，以改善电动汽车和无人驾驶飞行器等电池供电系统的安全性和可用性。电池供电的系统存在两个问题。第一个是里程焦虑问题，指的是在车辆运行过程中害怕电池电量耗尽。第二个问题与电池组的安全有关，在某些条件下，电池组可能会破裂甚至爆炸。为了解决这些问题，将开发一种方法来预测(1)放电结束(电池将耗尽电荷的时间)和(2)具有已知置信度的电池的剩余有用性能。这种方法涉及机器学习算法，以解决未来的加载条件、单元到单元的差异和建模的不确定性。这项研究将提高电池供电系统的运行准备和安全性，这些系统应用于从商业(电动汽车)到国防(无人机)等领域。2011年，奥巴马总统宣布了到2015年让100万辆电动汽车上路的目标。拟议的研究将为实现这一目标做出重大贡献，因为它可以通过实时提供强大的电池状态和健康信息来缓解用户对电动汽车安全性和可靠性的担忧，从而鼓励电动汽车的广泛使用。因此，它还将减少美国对外国石油的依赖，并减少温室气体排放。这项研究的内容将有助于促进预测学和健康管理技术的进步，这些技术将通过在线研究生课程、研讨会、讲习班和短期课程传播给工程界，从而使学术界、工业界和军方的人员受益。

The objective of this research is to develop prognostic methods for improving the safety and availability of battery-powered systems such as electric vehicles and unmanned aerial vehicles. Battery-powered systems suffer from two problems. The first is "range anxiety" problem, which refers to the fear of running out of battery power during vehicle operation. The second problem is related to the safety of a battery pack, which can rupture or even explode under certain conditions. To address these problems, an approach for predicting the (1) end-of-discharge (the time at which a battery will run out of electrical charge), and (2) remaining-useful-performance of a battery with a known level of confidence will be developed. This approach involved machine learning algorithms to address future loading conditions, unit-to-unit variations, and modeling uncertainties. This research will improve the operation readiness and safety of battery-powered systems that are used in applications ranging from commercial (electric vehicles) to defense (unmanned aerial vehicles) sectors. In 2011, President Obama announced his goal of having one million electric vehicles on the road by 2015. The proposed research will make significant contributions to reaching this target, since it can ease user concern about the safety and reliability of electric vehicles by providing robust battery state and health information in real-time, thus encouraging their widespread use. As a result, it will also decrease US dependence on foreign oil and reduce the emission of greenhouse gases. The content of this research will assist in the advancement of prognostics and health management techniques which will be disseminated to the engineering community through online graduate courses, seminars, workshops, and short courses thereby benefiting people from academia, industry and the military.