Contaminant concentrations dynamic prediction method for aircraft cabin based on estimating emission rates

The probability of air pollution in aircraft cabin will be increased with the prolongation of passenger aircraft pilot time, so it is very important to predict the contaminant concentrations dynamically. The key is source emission rate estimation and concentration dynamic prediction method. For the source emission rate estimation, Minimum mean-square value can only get the static estimate values, while extended Kalman filter (EKF) can realize dynamic parameter estimation, but single EKF couldn't exhibit good ability both for the normal process and fault process. Therefore, a contaminant concentrations dynamic prediction method for aircraft cabin based on estimating emission rates was presented to solve this question. Double model filter was used to trace the steady state and transient state (sudden contaminant source happening) of system. The performance of parameter estimation and state prediction could be improved using this method, and then the accuracy and speed of air quality prediction could also be improved. Simulations were done to demonstrate the performance of algorithm.