神经网络在提高锂离子电池检测精度中的研究

随着近些年来锂离子动力电池的广泛应用，作为生产锂离子电池关键设备的检测系统也成为新的研究热点。但由于系统中大量非线性元件的使用，使得设定基准、采样信号和实际的测量值之间存在较大误差。为了减小干扰、提高数据传输准确性和控制精度．必须对传送的数据进行处理。人工神经网络以其任意非线性函数的任意逼近能力和自学习能力，在控制领域内得到了广泛的应用。用人工神经网络对数据进行处理．修正系统误差。结果表明，经神经网络处理后的采样数据检测精度大幅度提高，为提高电池生产质量提供了可靠保证。

Research BP Neural Network in Enhancing the Controlling and Testing Accuracy of Li-Ion Electric Vehicle Battery

In recent years,lithium-ion electric vehicle battery has been more and more widely used,as a key equipment of Li-ion battery production,battery testing system has become a new research hotspot.Because the use of many nonlinear elements in this system,the setting reference and sampling data were distorted during the data transmission.Aiming at reducing the interference and enhancing controlling accuracy,the data should to be processed.BP neural network with excellent nonlinear approximation and self-learning...