加热炉中燃料在燃烧的过程中选择合适的空气系数α是节约能源的关键。只有将α控制在一个合理的范围之内,才能最大程度的降低热损失。由烟气热损失率以及不完全燃烧热损失率与α的函数关系得到寻优函数,使用MATLAB仿真粒子群算法对寻优函数的寻优过程,在燃料热值突变和工况变化时快速找到新的合适的α,达到燃料充分燃烧,提高热效率的目的。仿真结果充分验证算法的可行性和优越性,理论上实现了用相对较少的燃料得到较高的热效率。 Heating furnace fuel in the combustion process to select the appropriate air coefficient α is the key to energy conservation. Only by controlling α within a reasonable range can the heat loss be minimized. The flue gas heat loss rate and the incomplete combustion heat loss rate as a function of α get the optimal function. Using MATLAB simulation Particle Swarm Optimization algorithm to optimize the function of the optimization process, in the sudden changes in fuel heat and condition changes quickly found The new suitable α, to achieve the full combustion of fuel, improve thermal efficiency purposes. Simulation results fully verify the feasibility and superiority of the algorithm, which theoretically achieves higher thermal efficiency with relatively less fuel.