运行温度对智能电能表内置电池使用寿命影响

Influence of operating temperature on service life of built-in battery of smart electric energy meter

在现场运行中,很高比例的智能电能表在技术规范要求的使用寿命内出现了电池欠压告警,这会对电能表的正常使用造成严重影响。为找出电池欠压原因,实测了现场不同安装位置计量箱内温度,发现电能表长时间处于高温环境下运行。利用Adaboost算法对传统的遗传算法优化的BP神经网络(GA-BP)预测模型进行改进,建立了智能电能表内置电池容量预测模型。利用该模型进行预测,发现温度升高时,Li/SOCl2电池自放电率将成倍增大,这可能是电池性能加速损降导致欠压的原因。此外,设计了实验室不同环境温度下智能电能表电池耗电回路的电流试验,发现电流随温度变化而略有变化,这种变化主要与电路中电解电容等元器件质量及安装工艺有关。

In the field operation, a high proportion of smart electric energy meters occurred battery under-voltage warning, and these meters were in the service life required by the technical specifications. It will have a serious impact on the normal use. In order to find out the cause of under-voltage of batteries, the temperature in the measuring box at different installation positions was measured, and it was found that the electric energy meter operated under high-temperature environments for a long time. Adaboost algorithm was used to improve the traditional BP neural network prediction model optimized by genetic algorithm (GA-BP). The capacity prediction model of the built-in battery of smart electric energy meter was established. It was found that the self-discharge rate of the Li/SOCl2 battery would increase exponentially when the temperature increased, which may be the reason of under-voltage caused by accelerating loss of battery performance. In addition, the current test of battery circuit of smart electric energy meter under different temperatures in laboratory environment is designed. It is found that the current varies slightly with temperature, which is mainly related to the quality and installation process of electrolytic capacitors and other components in the circuit.