汽车空调鼓风机自适应控制算法的研究

汽车空调的工作条件很复杂,并且取决于许多因素,例如隔热,密封和温湿度.为了提高汽车空调鼓风机的工作效率,改善车内温湿度环境并达到节能减排的目的,通过模糊算法与PID算法相结合,并对粒子群优化算法进改进来对PID参数进行优化的方法.在Matlab的simulink平台上建立鼓风机控制的数学模型,对模型进行仿真,并对仿真结果进行分析.仿真结果表明,改进的粒子群优化算法优化的模糊PID控制策略具有较高的鼓风机控制精度.,鼓风机的响应时间较短且超调量小,能迅速达到稳定状态,达到试验预期效果.

Developing an adaptive control algorithm for the automobile air-conditioning blower

The operating conditions of automobile air-conditioners are complex and are affected by many factors such as ambient temperature and humidity, tightness and heat dissipation. In order to improve the working efficiency of automobile air-conditioning blowers, improve the temperature and humidity environment in the vehicle, and achieve the energy-saving purpose and emission reduction, a fuzzy algorithm and PID algorithm are combined to improve the particle swarm optimization algorithm to optimize PID parameters. A mathematical model of blower control is established on the Simulink platform of Matlab. The model is simulated and the simulation results are analyzed. The simulation results have verified that the fuzzy PID control strategy optimized by the improved particle swarm optimization algorithm has a higher control accuracy for the blower. The response time of the blower is short and the amount of overshoot is small, which can quickly reach stability and achieve the expected effect of the test.