Intake and exhaust system optimization of UAV piston engine

To solve the problem of torque decrease and high fuel consumption at 6500r/min flying speed of an unmanned aerial vehicle for plant protection, a multi-parameter optimization method using adaptive genetic algorithm(GA) based on 1-D thermodynamic simulation model was proposed to optimize the intake and exhaust system of single cylinder gasoline engine. GT-Power model of the UAV engine was built to simulate the engine working condition. The model was calibrated by experimental bench data to ensure the accurate simulation. Influence of structure parameters of intake and exhaust system on torque and fuel consumption was analyzed through design of experiment, and length of intake pipe and exhaust pipe, diameter of intake pipe and second cavity volume of air filter were chosen as optimization variables. The model was used to calculate the objective optimization function and limit conditions. Adaptive genetic algorithm was executed by Matlab which exchanged data by interface of Simulink/GT-Power to receive and feedback results. According to the optimization result of adaptive GA, new intake and exhaust system was mounted on the engine to verify optimization result. Result demonstrated that torque and fuel consumption at flying speed of 6500r/min of the engine was obviously improved by adaptive GA, and torque was raised by 5.51% and fuel consumption was improved by 6.31%.