## 1 Introduction  
Gear honing, a key finishing process in gear manufacturing, has the advantages of high tooth precision, high load-carrying capacity, low transmission noise, and regular tooth texture, etc. [1, 2]. These characteristics make it particularly suitable for gear processing in the production of new energy vehicle drivetrains [3, 4, 5]. The quality of honed teeth plays a crucial role in gear life, transmission noise, and load-carrying capacity. However, the factors affecting the quality of honed teeth are characterized by randomness, complexity, and unpredictability, making a detailed analysis of honing machining characteristics challenging. Compared to traditional grinding methods, the quality of honing is further improved [6]. Honing as a gear finishing method, which uses a pair of staggered-axis cylindrical gears for forced meshing into a movement through the honing wheel on the abrasive grains sliding friction workpiece tooth surface, removes a thin layer of material. Some scholars evaluated the quality improvement of gears with grinding wheels from different perspectives. [PERSON] [7] established the relationship between five input parameters such as spindle speed, machining time, X- and Z-direction feed rate, and spark out time with total profile deviation (f\(\alpha\)), total helix deviation (f\(\beta\)), and total cumulative pitch deviation (fp) by using a grain swarm algorithm. [PERSON] [8] has optimized and actively controlled the spindle speed, axial feed speed, and radial feed speed of the honing process parameters at a constant cutting speed to minimize the total tooth shape error. The above literature focuses on the effect of various factors on the accuracy of the tooth surface. [PERSON] [9] compared five gear finishing processes and comprehensively evaluated the tooth surface quality with parameters such as surface roughness, surface morphology, surface residual stress, surface texture roughness, and peak radius of curvature after machining, The Author highlighted the synergistic optimization of factors such as abrasive grain size and shape as an effective method to improve both machining efficiency and surface quality. [PERSON] [10] designed an orthogonal test of a diamond abrasive grain grinding wheel on silicon carbide grinding to analyze the effects of the processes such as grain size, grinding wheel speed, workpiece speed, and grinding depth on surface roughness, surface topography, and grinding force. The grinding quality was comprehensively analyzed, and the process parameters were optimized based on these factors. The above literature focuses on the effects of various factors on surface quality. [PERSON] [11] studied the effect of honing process parameters such as speed of pinion, speed of the grinding wheel, feed rate, spark out, and cycle time. The experimental results showed that the helix form error and the evolvent profile error were affected by the cycle time and feed rate. [PERSON] [12] evaluated the working efficiency of disc circles through parameters such as grinding power, surface roughness, involute tooth shape accuracy, and wear of the disc circles. The experimental results show that the dimensional wear of the grinding wheel is the main factor affecting the accuracy of grinding processing, and the grinding efficiency is correlated with the depth of cut and the grinding time of a single tooth. [PERSON] [13] proposed a specific energy model for quantitatively evaluating the material removal rate of honed teeth. Experimentally, it was observed that a larger honing depth resulted in an increase in material removal rate. In addition, at the same workpiece speed and honing depth, an increase in both the cross-axis angle and axial feed rate resulted in an increase in specific honing energy and a decrease in material removal rate. The above studies focus on the effects of various factors on processing efficiency.