This study analyzed the engine operating condition curve of the corn kernel harvester. Field experiments identified the feed rate, concave clearance, and cylinder speed as the main factors affecting operating quality and efficiency. A ternary quadratic regression orthogonal center-of-rotation combined optimization test method was used to determine the feed rate, cylinder speed, and concave clearance as the influencing factors, and the engine speed variation rate, crushing rate, impurity rate, loss rate, and cylinder speed variation rate as the objective functions. A mathematical regression model was developed for the combination of operating quality indicators, efficiency indicators, and operating parameters of the corn kernel harvester. A non-linear optimization method was used to optimize the parameters of each influencing factor. The results showed that with a feed rate of 12 kg/s, a forward speed of 5 km/h, a cylinder speed of 360 r/min, and a concave clearance of 30 mm, the average crushing rate was 3.91%, the average impurity rate was 1.71%, and the kernel loss rate was 3.1%. This model could be used for the design and development of intelligent control systems.