Study of fuel economy optimization for a semi-track air-cushion vehicle based on genetic algorithms and fuzzy control

A semi-track air-cushion vehicle (STACV) which combines an air-cushion lifting system with a semi-track propulsion system is an efficient solution for heavy-duty vehicles working on soft terrain, such as the vehicles for agricultural, oil industrial and military purposes. Focusing on optimizing fuel economy of the vehicle, five main issues are studied in this paper. Firstly, based on the analyses of resistances for the STACV in a sandy loam working condition, a theoretical model for fuel consumption of 100 km, which is an evaluation index for fuel economy, is established. Secondly, through simplified by a group of constraint equations based on the physical structure of the vehicle, the running parameters and control target (fuel consumption of 100 km) could be expressed by the following two measurable and adjustable parameters, fan rotational speed and vehicle forward speed. Thirdly, a genetic algorithms (GA) model is designed to optimize the fuel consumption and to get the relevant parameters off line as control objectives of status variables of a control system. Fourthly, the control system with a fuzzy PID controller and a GA-based PID controller is built to achieve the minimal fuel consumption by regulating fan rotational speed and vehicle forward speed respectively. Fifthly, simulations are performed in a MATLAB/Simulink software environment. The result illustrates that this control system works efficiently and steadily.