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A Novel Battery Diagnostic Method for Smart Electric Vehicle Charger

机译:一种用于智能电动车充电器的新型电池诊断方法

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Indications of mileage, charging-time and residual lifetime of the battery of EV are indispensable to any smart EV. These values have strong relation with the capacity (SoH) and impedance of the battery. Traditional off-board measurement approaches require the battery to be removed from the vehicle and the associated lengthy processing time would cause interruption to the normal operation of the battery driving equipment. A program that is capable of predicting the battery impedance and the internal voltage during its operation is developed in this work for a one-chip microcomputer that is embedded into a smart EV charger. In addition, pulse current is also employed to prolong the battery life. The prediction is performed by a numerical convolution and fitting techniques. This method has an advantage in low memory requirement, because the sampled voltage waveform of a single pulse is used. A comparison to the measurement result by AC superposition method proofed that the accuracy of the proposed method is satisfactory. The average error is less than 6 %.
机译:对EV电池电池的里程,充电时间和剩余寿命的指示对于任何智能EV都是必不可少的。这些值与电池的容量(SOH)和阻抗具有很强的关系。传统的外壳测量方法需要从车辆中移除电池,并且相关的冗长处理时间会导致电池驱动设备的正常操作中断。能够预测电池阻抗和其操作期间的内部电压的程序是开发的,这对于嵌入智能EV充电器的单片机的工作开发。另外,脉冲电流也用于延长电池寿命。通过数值卷积和拟合技术进行预测。该方法在低存储器要求中具有优势,因为使用单个脉冲的采样电压波形。通过AC叠加方法对测量结果进行比较证明所提出的方法的准确性令人满意。平均误差小于6%。

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