基于神经网络的汽车加热器额定放热量参数修正

Rated Heat Parameter Correction of Auto Heater Based on Neural Network

介绍了燃油汽车加热器额定放热量参数的计算方法及其测量系统结构,并针对额定放热量误差产生的原因进行分析,给出了具有三层节点的前馈型BP神经网络结构和训练权值的过程.通过仿真结果对比可知,利用BP算法额定放热量进行修正后,得到了比较精确的额定放热量,能为加热器的生产及应用提供重要的参考依据.

This paper introduces the parameter calculation method and the measurement system struc- ture of auto fuel heater rated discharge. The rated heat error analysis is given and the nodes in three layer feedforward BP neural network structure and weights are discussed. By comparing the simulation results,it is found that the more accurate rated heat can be obtained after using BP algorithm to correct the rated heat release. The result provides important reference data for heater manufacturer and user.