针对目前我国智能电能表寿命衡量标准单一、复杂环境应力条件下寿命预测精度低的问题，对复杂环境应力下智能电能表寿命预测问题进行了深入的研究。研究了智能电能表的失效机理，对影响智能电能表寿命的6种环境应力进行分析，并针对由于智能电能表故障样本偏少、寿命较长导致寿命难以预测的困难，提出了一种利用粒子群算法参数优化的T-S（Takagi-Sugeno）模糊模型智能电能表的寿命预测方法。收集了我国4种典型气候条件下的智能电表应力与寿命数据进行寿命预测实验验证，实验结果表明，该方法可以有效的预测不同环境、多种环境参数影响下的智能电能表的寿命，其精度高于原始T-S模糊模型算法。

In response to the current problem of only single standard to evaluate the meter in China and a lower accuracy in its life prediction under complex environment stress, a deep research on the life prediction of smart meters under complex environment stress is conducted. The failure mechanism of smart meters is studied through the analysis of 6 stresses existing in environment which affect smart meter’s life. In addition, a smart meter’s life prediction solution based on T-S（Takagi-Sugeno） fuzzy model with particle swarm optimization is proposed to address the difficulty of predicting lifespan due to the small number of fault samples and long lifespan of intelligent energy meters. Then stress and lifespan data of smart meters under four typical climatic conditions in China are collected for experimental verification of lifespan prediction, and experiments about the life prediction are made through these data. The experimental results show that the proposed approach is an effective way to predict the life of smart meters under different environments and various environmental parameters, with higher accuracy than the original T-S fuzzy model algorithm.