The invention relates to an indoor illumination 
estimation method based on a BP neural network 
algorithm, and belongs to the technical field of 
intelligent algorithms. The method comprises the following steps: S1, analyzing parameters obtained through traditional formula calculation and a sensor to obtain BP neural network input parameters and a training model; S2, based on the 
light flux transferfunction 
matrix model, obtaining the required indoor 
illuminance through LED 
luminous flux calculation; S3, linearly superposing the 
illuminance of the n light sources, calculating the 
illuminance ofthe corresponding point, performing reverse approximation according to a successive approximation rule to obtain the 
luminous flux of the lamp, and obtaining the illuminance of the calculation point;and S4, calculating the illuminance needing to be compensated by utilizing the illuminance data, predicted by the BP neural 
network model, of the natural light at a plurality of point locations of the indoor working face. According to the method, under the condition that 
natural illumination is fully utilized in different seasons, the maximum balance among the three requirements of seeking energyconservation, saving and comfort is met through light supplement.