Air conditioning predictive control for rail transit vehicles based on load prediction

This paper proposes a predictive control method for rail vehicle air-conditioning systems. Due to heat transfer and diffusion, the air-conditioning system is a long-time-delay system. However, most air-conditioning systems use feedback control, which has problems such as long transition time, system shock, and mismatch between air cooling capacity and load, resulting in the waste of energy. Combined with feedforward and feedback control, a predictive control method with dynamic correction is proposed to solve this problem. Based on the load prediction, the real-time indoor temperature feedback link is added to send the cold air into the room in advance, which makes the room temperature stable, and the energy-saving effect significant. In the study, variance analysis of environmental factors is performed to improve the accuracy of the load prediction system, and the mean relative error (MRE) of the prediction reached 0.0112. By comparing the simulation results of predictive control and feedback control, it is proved that the predictive control with correction has a smoother room temperature curve. The energy-saving rate is about 25.2%.