Abstract: In recent years, the requirement of intelligent appliances of people is higher and higher, and all sorts of intelligent home appliances also emerge in endless. But because of the complexity in the cooking process, it is difficult to achieve precise control of the electric frying pan. To solve this problem, a heat transfer model of the electric frying pan is put forward, which is based on the basic heat transfer equation. Then the parameters of the model are trained using the genetic algorithm, let the model can simulate the change of temperature of the electric frying pan accurately in different circumstances. Based on this model, a control scheme of electric frying pan is put forward. Firstly, the model predicts the change of the temperature of the electric frying pan, then calculates the best power according to the demand, makes it keep the temperature needed all the time, and reduces the power fluctuations as far as possible at the same time, which can reduce the wastage of the electric frying pans power control device. Finally, the control scheme is verified that it can realize the intelligent control to maintain the temperature in the electric frying pan in any stage and improve the energy efficiency through the experiment.

Key words: electric frying pans, intelligent control, genetic algorithm

摘要： 近年来，人们对家电智能化的要求越来越高，而各种智能家电也层出不穷。但因炒制过程较为复杂，难以对其实现较为精确的智能控制。为了解决此问题，通过最基本的热传导公式推导出了电炒锅的热传导模型，通过遗传算法对模型的参数进行训练，使模型在不同的情况下均能较为准确地模拟电炒锅温度的变化情况。基于此模型，提出了电炒锅的控制方案。对电炒锅模型下一时刻的温度变化进行预测，根据需求计算出电炒锅最佳功率，使电炒锅在炒制过程中能够始终保持需要的温度，同时尽可能减少电炒锅功率的波动，从而降低电炒锅功率控制器件的损耗。通过实验验证了此控制方案在不同的烹饪阶段均能够较好地实现炒锅的智能控制，达到维持锅内温度，提高能源利用效率的目的。

关键词: 电炒锅, 智能控制, 遗传算法