Design of Engine Cooling System Using Improved Particle Swarm Optimization Algorithm

The cooling system directly impacts the power output of an engine. The cooling water flow and temperature in the heat exchange process outside the engine exhibit dynamic characteristics of nonlinear, time-varying, and solid coupling, precise control algorithms to optimize the coordination mechanism of the pump and valve with electronic control are crucial factors for the cooling system to handle thermal loads. This article presented a feedforward compensation decoupling control and schedules the fuzzy proportional-integral-differential (FPID) controller optimized through an improved particle swarm algorithm for the engine cooling system. Primarily, the mathematical model of the cooling system’s heat exchange is constructed by gathering relevant data, and the feedforward compensation decouplers are designed to diminish the coupling extent of cooling water flow and temperature in the external cooling cycle. Next, the whole control system model is created in MATLAB/Simulink and functional simulation is performed by incorporating particle swarm optimization (PSO) algorithm with the dynamic adjustment strategy of stochastic inertia weight to optimize the FPID controller’s quantization and proportionality factors. Eventually, the approach’s feasibility is validated on the existing physical experimental platform. The findings demonstrate that this proposed improved control and optimization method is expected to enhance the water flow regulation characteristics as well as temperature control precision of the cooling water and strengthen the stability of the heat exchange efficiency of the cooling system.